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Exploring new ways of Startup Performance Information ManagementEnabling Startups to Manage their Performance Information within Supportive Startup EcosystemsTiemen RoestMaster of Business Informatics Information and Computing Sciences, Utrecht UniversityJanuary 2016Name: Tiemen Roest Contact: T.Roest@students.uu.nl Title: Exploring new ways of Startup Performance Information Management. Enabling Startups to Manage their Performance Information within Supportive Startup EcosystemsResearch period: April 20st, 2015 – January 31st, 2016Date of defence: January 28st, 2016Utrecht University, Information and Computing sciences Master: Business Informatics 1st Supervisor: Dr. Slinger Jansen 2nd Supervisor: Prof. dr. Sjaak BrinkkemperHost institution: Holland Startup B.V. Supervisor: Maurice BakkerAcknowledgementsFirst I want to say many thanks to my both supervisors. Thanks to Slinger Jansen as my guide concerning the scientific part of the research, where his critical academic point of view kept me on track concerning the quality, in the semi-academic world of startup. However since he is a real startup-enthusiastic as well, he has provided many ideas and directions to consider, always with a lot of enthusiasm. Also many thanks to Maurice Bakker, my supervisor at the host company, the venture builder Holland Startup, for providing me the opportunity to do research in my favourite field, which is on startups and entrepreneurial behaviour, and at a fantastic company, which also definitely kept me motivated to finish my thesis on time. His practical point of view on startups, from his broad experience, made me aware of how startups behave and which stakeholders could be important to consider as subjects of research. Most important, I felt being a lucky guy with such enthusiastic supervisors. Also thanks to Sjaak Brinkkemper, who was willing to be my second supervisor and therefore assessing my thesis from a critical standpoint, which contributes to the quality of the research and my experience and knowledge on delivering a well-written thesis.I also must say special thanks to my girlfriend (currently also being my fiancé), Renata Karzijn, for keeping motivated all the time, and for her patience, especially when writing my thesis during the holidays was required.Also many thanks to all of my ‘colleagues’ at Holland Startup for the great time I had together with them during the period of doing my research. Robbert Jan Hanse and Rene Roskamp as experienced guys in entrepreneurship, information systems, metrics, and such. All the other guys as well, the young and brilliant entrepreneurs and researchers. All of them provided me with helpful feedback and made me stay motivated during the whole research period.AbstractDifferent methods of company building exist, both traditional and non-traditional. The non-traditional method, the Lean Startup, combines iterative Agile development and Lean manufacturing, to an iterative build, measure and learn cycle, in order to enable building fast growth companies, i.e. startups.To support and guide trough the startup building process, several startup building programs (e.g. incubators, accelerators, and venture builders) evolved since the 2000 Internet bust. Monitoring and managing the risks in the startup building processes within these programs require Performance Measurement. Performance measurement has shifted the last decades from mainly Financial Accounting to a merely broader measurement of startups, referred to as Innovation Accounting. The traditional investing world can be shifted as well, by applying traditional success factors (similar to risk factors), which can be categorized on Team, Product and Market, and Startup, to a more non-traditional (Lean Startup) perspective on the startup lifecycle and its related success factors. Literature research and field research on startup building organizations and startup investors result in a framework providing insights and metrics on startup building and its performance measurement. Metrics can be divided on category into two types, General and Stage dependent. Metrics can be actionable or vanity metrics. The resulting SPIM Framework consisting of the Stakeholders, General and Stage dependent metrics, and a Framework Application Model, enables Startup Performance Information Management (SPIM) for the different stages and stakeholders in the startup lifecycle.Contents TOC \o "1-3" Acknowledgements PAGEREF _Toc315463979 \h 3Abstract PAGEREF _Toc315463980 \h 41.Introduction PAGEREF _Toc315463981 \h 71.1.Startup Building Organizations PAGEREF _Toc315463982 \h 71.2.Performance Measurement Challenges PAGEREF _Toc315463983 \h 71.3.Lack of Research PAGEREF _Toc315463984 \h 81.4.Scientific Relevance PAGEREF _Toc315463985 \h 81.5.Scope PAGEREF _Toc315463986 \h 101.6.Research Structure PAGEREF _Toc315463987 \h 102.Research Method PAGEREF _Toc315463988 \h 123.Theoretical Background PAGEREF _Toc315463989 \h 143.1.Defining a Startup PAGEREF _Toc315463990 \h 143.2.Startup Building Methods PAGEREF _Toc315463991 \h 163.2.1.Traditional Methods PAGEREF _Toc315463992 \h 163.2.2.Non-Traditional Method: Lean Startup PAGEREF _Toc315463993 \h 163.3.Startup Lifecycle PAGEREF _Toc315463994 \h 193.3.1.Startup Lifecycle Stages PAGEREF _Toc315463995 \h 193.3.2.Startup Lifecycle Phases PAGEREF _Toc315463996 \h 223.3.3.Pivots PAGEREF _Toc315463997 \h 253.4.Startup Building Organizations PAGEREF _Toc315463998 \h 263.5.Startup Building Ecosystem PAGEREF _Toc315463999 \h 293.5.1.Ecosystem Overview PAGEREF _Toc315464000 \h 293.5.2.Investors PAGEREF _Toc315464001 \h 303.6.Startup Performance Information Management PAGEREF _Toc315464002 \h 423.6.1.Defining Performance Measurement PAGEREF _Toc315464003 \h 423.6.1.Performance Measurement Goals PAGEREF _Toc315464004 \h 433.6.2.Financial-to-Innovation Paradigm Shift PAGEREF _Toc315464005 \h 443.6.3.Metrics PAGEREF _Toc315464006 \h 453.7.Performance Measurement Systems PAGEREF _Toc315464007 \h 553.7.1.Performance Measurement System Goals PAGEREF _Toc315464008 \h 553.7.2.State of the Art PAGEREF _Toc315464009 \h 564.Data PAGEREF _Toc315464010 \h 614.1.Qualitative Methods PAGEREF _Toc315464011 \h 614.1.1.Data Collection PAGEREF _Toc315464012 \h 614.1.2.Data Quality PAGEREF _Toc315464013 \h 614.1.3.Data Analysis Method PAGEREF _Toc315464014 \h 624.2.Data PAGEREF _Toc315464015 \h 634.2.1.Concepts Overview PAGEREF _Toc315464016 \h 634.2.2.Interview Data PAGEREF _Toc315464017 \h 644.2.3.Summary PAGEREF _Toc315464018 \h 875.SPIM Framework PAGEREF _Toc315464019 \h 915.1.Conceptual Model PAGEREF _Toc315464020 \h 915.2.The Framework PAGEREF _Toc315464021 \h 925.2.1.Origination PAGEREF _Toc315464022 \h 925.2.2.Framework Description PAGEREF _Toc315464023 \h 925.2.3.Framework Application PAGEREF _Toc315464024 \h 956.Conclusions PAGEREF _Toc315464025 \h 1007.Discussion PAGEREF _Toc315464026 \h 1047.1.Limitations PAGEREF _Toc315464027 \h 1047.2.Further Research PAGEREF _Toc315464028 \h 1058.References PAGEREF _Toc315464029 \h 107Appendix A – Discovery Interview PAGEREF _Toc315464030 \h 113Appendix B – Interview Protocol (Startup Building Organizations) PAGEREF _Toc315464031 \h 114Appendix C – Interview Protocol (Investors) PAGEREF _Toc315464032 \h 115Appendix D - First SDEIF (version 0.1) PAGEREF _Toc315464033 \h 116Appendix E – Second SDEIF (version 0.2) PAGEREF _Toc315464034 \h 117Appendix F – Third SDEIF (version 0.3) PAGEREF _Toc315464035 \h 118Appendix G – Fourth SDEIF (version 0.4) PAGEREF _Toc315464036 \h 119Introduction“If you can’t measure it, you can’t manage it” – Peter Drucker“It is the framework which changes with each new technology and not just the picture within the frame”– Marshall McLuhan Startup Building OrganizationsIn 2005 the ‘accelerator program’ Y Combinator selected eight companies for their first batch of companies (i.e. startups) they would accelerate to growth, through intensive guidance (Miller & Bound, 2011). Y Combinator therefore is considered by Miller & Bound (2011) as the first official accelerator program, followed by Techstars in 2007, and from that moment in time, a lot of other accelerator programs are established, both successful and not successful initiatives. Besides accelerators, other forms of startup building programs do exist, focusing on different parts of the startup lifecycle: incubators to support only the early-stage of a startup, venture builders to cover the complete startup lifecycle (Miller & Bound, 2011; Radojevic-Kelley & Hoffman, 2012; Rohé, 2012). The three different forms of startup building can also be diversified in industry-focus (for example: healthcare startups), restrictions in their participant application (for example: university-affiliated startups) or focussed on product usage or complementary products (for example: using Microsoft) (Cohen & Hochberg, 2014).Performance Measurement ChallengesHow do these accelerators and other building programs look like, i.e. in which ways are they building their startups? What criteria are used to measure how successful these startups are, to estimate, increase and perhaps predict their success? For example, how do you know if a startup is on track reaching their Product/Market fit milestone and when to act if it seems the startup does not reach its milestone? Because, as Peter Druckers’ quote says, measuring is necessary in order to manage the way you run your business, i.e. managing the path to (potential) success through realising improvements. Performance measurement systems like accounting systems have been a central topic in previous research, on both financial reporting as well as on management accounting (Davila and Foster, 2005). Davila and Foster (2005) describe how still from the early 2000s the research towards management accounting in younger (i.e. early-stage) firms has begun to receive attention. In these firms, little systems, architecture, or any kind of frameworks are in place. However, decisions on the central topics within a company, supported through management accounting systems, build up the operational framework of a company. Therefore the need for insights in better (management) accounting systems in early-stage companies (i.e. startups) seems clear. Lack of ResearchTo know how the young firms (in case of this research: venture builders consisting of internally located startups) look like and how to improve them, first a theoretical background on these programs is needed, since Cocca and Alberti (2010) describe that to be able to develop a tool to do performance measurement, you need to understand the needs of a small and medium size enterprise (SME) in detail, gaining insights in their characteristics (which obviously also applies to venture builders and startups as being SMEs).However, as claimed by Cohen and Hochberg (2014), unfortunately little research is done in the field of startup building programs, both descriptive and result oriented, caused by the heterogeneity as well as lacking definitions of the startup building programs. Therefore, this research will try to provide clearer insights in how startup-building organizations like these programs look like, in an exploratory way, both on the content (the startups and their building methods and techniques) as well as the environment (i.e. ecosystem) they operate in. Obviously also a lot of startups are built without the support of these programs, but this research will focus on those who are particularly built within the organized building programs. Scientific RelevanceObviously, as mentioned, the performance and measuring this performance at the startups being build within a program is important, both for the existence and performance of the startup-building program itself. As research shows, building programs (thus venture builders and investors too) interpret the performance of startups on several company portfolio criteria, in order to know which startups can apply for their program and are worth the investment (Chang, 2013; Megginson and Weiss, 1991). However, still low growth small or medium sized businesses do not use as many customer metrics for example, and their performance management systems are often not based on best practices from the literature (Cocca and Alberti, 2010; Ates et al., 2013). Steve Blank (2012) refers to Evidence Based Entrepreneurship and Investor Readiness to describe respectively the importance of the knowledge of how a startup is performing, related to the knowledge where startups should be in order to meet the investing criteria.Previous research on startup success is, among others, done by Cann, Brinkkemper, and Jansen (2012). They have done an extensive research towards the key decisions in the startup phases that might have contributed to success within sixteen large Dutch software companies. Although they did include theory on startup phases, success factors and investing criteria, their research focuses mainly on the key decisions of the entrepreneurs of traditionally built companies, concerning shaping the company, the product development, entering the market and going international, influenced the company success.Marshall McLuhan as quoted above the start of the introduction was right: changes in technology (and methods) from, for example, traditional to non-traditional, needs new frameworks. Therefore, the main goal of this research is to provide more insights in the startup ecosystem criteria for performance measurement, tied to the different startup phases, from both the information management and performance measurement points of view, in a Startup Performance Information Management (SPIM) Framework. The underlying goal of this research is to contribute to transparency and knowledge within startup ecosystems, to in the end strengthen the relationships between stakeholders and startups within those ecosystems.Which particular criteria need to be considered as important by startups and investors, will be based on literature and evaluated in the environment of the ecosystem. Research on the investment decision process of Business Angels (BA’s) shows that criteria can be unknown or ignored when assessing a startup, where BA’s tend to rely on their gut feeling instead of relying on a formal startup evaluation approach, which makes the evaluation process quite unclear (Maxwell, Jeffrey & Lévesque, 2011). The potential economic impact of startups makes that same problem concerning to Maxwell et al. (2011) whereas they describe, based on other research, for example 95% of the entrepreneurs in Canada fail to attract BA funding, similar as observed in the U.S. an the U.K.. Maxwell et al. (2011) ascribe that substantial amount of failure to misunderstanding of the decision process. Also research on the investment decision process of Venture Capitalists (VCs) shows entrepreneurs and VCs are facing similar decision process knowledge problems. As Miloud, Aspelund and Cabrol (2012) describe through strong findings of actual Venture Capitalists’ (VC) valuations, for example the factors Industry structure, Founder/Team and Network, consisting of several specific criteria, are the most important ones, unfortunately they have not found a relative importance yet between those factors. Therefore they suggest further research as required in order to use these highly relevant findings to become beneficial to startups and their investors.Scope The framework will consist of information and data both for venture builders as well as for external stakeholders (in this research: investors), focused on Software-as-a-Service (SaaS) startups. It mainly aims at quicker and easier provision of useful insights in the company portfolio of a venture builder (which consists of a management team and individual startups) as well as improving the assessment and prediction of success of the startups involved in those startup-building programs, which is relevant to investors as well. Therefore, the venture builder can be seen as the primary stakeholder, where the investors are the (most important) secondary stakeholders. Baum and Silvermann (2004) describe financial intermediaries such as VC firms as the dominant ones shaping the environment (i.e. ecosystem) the startups (or venture builder) operate in. To put the importance of the different roles into perspective, the research also will describe how the level of dominance of a particular stakeholder depends on the stage of a startup. Although the framework tries to improve the information and data management (performance measurement) in and around all kinds of (SaaS) startups, keep in mind that the framework is not built to serve as a ‘one-size-fits-all’ solution. Also, the performance measurement cannot be seen as a smaller version of tools being already developed for large enterprises, like Cocca and Alberti (2010) warn for in the context of inappropriate design of SME tools. Therefore it will focus on startups particularly in the SaaS domain.Research StructureThe structure of the research will be build upon one main research question, separated into three parts with six research sub-questions. The main research question:center1905RQ How can Startup Performance Information Management (SPIM) support Startup Building in a Venture Builder Ecosystem?00RQ How can Startup Performance Information Management (SPIM) support Startup Building in a Venture Builder Ecosystem?The first part is the startup part, necessary in order to gain insights in the characteristics of startups and the venture builder ecosystem they operate in. The first question to answer is what startup building methods do exist (SRQ 1). Followed by how a startup lifecycle is structured (phases and stages) (SRQ 2). The second part concerns the descriptive question on how the environment of a startup looks like, the venture builder ecosystem (SRQ 3), elaborating on the stakeholders and their relationship with a startup being built within a venture builder.The third part will focus on the startup performance information, the corresponding metrics and existing startup information systems, which might support the startup building process within the venture builder ecosystem. It starts describing why and how SPIM supports startup building (SRQ 4). Followed by describing which existing information systems could support SPIM (SRQ 5). Each of the chapters concerning the research questions will close with a summary on those particular chapters.All previous questions sum up to a whole description of startups and their ecosystem performance information demand, where the remaining question is how that information can be modelled into a SPIM framework, consisting of both a SPIM stakeholders and metrics overview, as well as a related application model (SRQ 6). Research MethodAfter the topic is introduced in the previous chapter, this chapter will elaborate on which research methods will be used. A schematic overview of the subsequence of the different methods is depicted in figure 1, designed according to the Process Deliverable Diagram modelling technique developed by Weerd and Brinkkemper (2008).The research will first start with an exploratory literature research to provide a theoretical background on startup building, the venture building ecosystem, funding, success criteria, and performance information management. This theory will provide information on framework requirements, which will be described in the framework requirements section. The requirements will be completed through an extensive field research in two fields. First, (internal) interviews in the field of venture building itself: at venture builders, incubators and accelerators. Second, (external) interviews on other startup stakeholders. Due to limitations of the research period, the scope of these external stakeholders only includes the investors as a target group, whereas Business Angels (informal investors) and Venture Capitalists (formal investors) are selected as focus groups within the investor ecosystem, therefore excluding other forms of informal investing, like family & friends, crowdfunding, etc. (see chapter. 3.5 for a more detailed view on a startup ecosystem). Besides the limitation mentioned, the investors are selected due to their important (or even necessary) role in the startup lifecycle, since financing events are necessary to startup survival and do have a positive effect on firm growth as well as predicting growth (Davila, Foster & Gupta, 2003). The qualitative interview results will be transcribed, coded and used as a basis to formulate a grounded theory, based on a comparison method, comparing the different stakeholder groups to each other (Boeije, 2002; Singer, Sim, & Lethbridge, 2008). The field research will be executed in an iterative way: the findings will be processed in the framework during the field research.Fig. SEQ Fig. \* ARABIC 1 - Research methodTheoretical BackgroundTo start providing the background of this particular research, this chapter will provide the existing relevant theory on venture building and the related information management and performance measurement. The theory will be discussed in three separated parts: first on what a startup and venture building actually is, secondly on business information management and thirdly why business performance measurement is considered as crucial in managing venture building. Defining a StartupBefore discussing startups and their building process, a definition of a startup is needed. Different definitions are used in the recent years. Blank and Dorf (2012) define a startup as “an organization formed to search for a scalable and repeatable business model”. Graham (2012) defines a startup as “a company designed to grow fast”. Both terms in essence relate startup to growth, through scaling and repeating. Seen from a sales perspective is selling something to a big market to reach rapid growth what a startup differentiates from a traditional business (Graham, 2012). Blank covered the difference in an overview, see figure 2, which shows the transition, or difference, between a startup, which is considered in the experimentation phase, working on a scalable business model, to a revenue generating company. The main parts changing are the main company focus, finances and human resources.Fig. SEQ Fig. \* ARABIC 2 - Startup to Company transition process (Blank, 2012)Startup Commons, a global non-profit initiative to support governments in startup ecosystem building, managing, measuring and benchmarking, also contributes to startup insights by (among others) providing the overview as shown in figure 2 (Startup Commons, 2015). The figure shows how a startup evolves from Ideation (identifying a potential idea/product) to Establishing (achieved great company growth). These stages will be discussed in more detail when discussing several similar startups lifecycle descriptions in chapter 3.2. The bumpy line symbolizes the major entrepreneurial factor ‘uncertainty’ over a substantial period of time. As described in the introduction, this research aims at providing more clarifying insights at what happens during that period and how to act while under a certain level of uncertainty, both applicable to internal as well as external stakeholders, which will be elaborated on in the pivot section in 3.3.1.Fig. SEQ Fig. \* ARABIC 3 – Startup Development phases (Startup Commons, 2015)02048510Summary Startup Definitions“an organization formed to search for a scalable and repeatable business model” “a company designed to grow fast”Startup ProcessPhases from Pre-Startup (idea phase) to Startup (validation phase) to Growth (scaling up the company).In order to discover, evaluate and exploit opportunities of creating goods and service.00Summary Startup Definitions“an organization formed to search for a scalable and repeatable business model” “a company designed to grow fast”Startup ProcessPhases from Pre-Startup (idea phase) to Startup (validation phase) to Growth (scaling up the company).In order to discover, evaluate and exploit opportunities of creating goods and service.Defining entrepreneurship will give some additional insights in the background and effort related to building a startup. Gelderen, Thurik and Bosma (2006) refer to the person undertaking the activities of creating a business as the nascent entrepreneur, where nascent entrepreneurship is the definition for the effort needed to found a business. Shane and Venkataraman (2000, p.218) define entrepreneurship as “the scholarly examination of how, by whom, and with what effects opportunities to create future goods and services are discovered, evaluated, and exploited”. Startup Building MethodsTraditional MethodsTwo traditional used building methods, originating from software development, are the Waterfall development method and the Agile development method (Larman & Basili, 2003) The main difference is the iteration frequency. The waterfall method as a stepwise approach, avoids processing changes during (at least) the first development round (Larman & Basili, 2003). The opposite is the agile development approach, functioning as an iterative approach, focussed on processing and communicating feedback every step of the process, to adapt rapidly to changing consumer requirements, in order to do incremental delivery of the software (Fowler & Highsmith, 2001). The agile approach is important in the transition to the recent (iterative) lean development methods, as will be disused in the next section.Advantages and disadvantages of both methods are described in table 1. The overview is included in order to have a better understanding of the history of the recently developed methods.Waterfall (stepwise)Agile (iterative)AdvantagesDocumented requirement gatheringLess time & costs on requirement gathering Customer feedback simultaneously with developmentDisadvantagesChanging requirements require documentation changesUnstructuredTable SEQ Table \* ARABIC 1 – Waterfall Development versus Agile Development (Fowler & Highsmith, 2001; Larman & Basili, 2003)Non-Traditional Method: Lean StartupRoyce (1970) already figured out that, besides analysis and coding, the development process of large software systems require a lot of extra steps, contributing to waste of effort rather than the main goal: "[While] many additional development steps are required, none contribute as directly to the final product as analysis and coding, and all drive up the development costs” (Royce, 1970, p.1). That is what the most recent company building methodology, the Lean Startup, also is about. The term Lean was used for the first time in the Japanese industry, as in Lean manufacturing. A lean manufacturing system is focused on value creation for the end customer, considering the expenditure of resources for other goals, as waste. This lean manufacturing originates from Ohno, who introduced the Toyota Production System in Japan, aiming primarily at cost reduction (or, waste elimination), introduced in the U.S. in 1984 (Shah and Ward, 2007). However, this lean method is focused on manufacturing. In the process of company building the lean method also evolves, when in 2005, Steve Blank published his book called ‘the Four Steps to Epiphany: Successful Strategies for Products that Win’. He introduced the new methodology on company building, called Customer Development. This methodology is, like lean manufacturing, focussed on only using resources to reach you primary goals, in the case of company building defined by blank Blank as finding primarily the right market, through Customer Discovery and Customer Validation in an iterative way (Blank, 2006). Eric Ries further defined the Lean Startup process, combining customer development (Steve Blank, The Four Steps to Epiphany), Agile software development methodologies, and Lean manufacturing practices into a framework for developing products and businesses quickly and efficiently (Croll and Yoskovitz, 2013, p.12). He published his findings in ‘The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses’ (Ries, 2011). This renewed Lean Startup building approach methodology created a whole new movement in the startup world, where even business schools adapt their curricula to teach this particular approach (Blank, 2013).3980180-8985250041148001078865Fig. SEQ Fig. \* ARABIC 4 - The Lean Startup cycle (Ries, 2011)0Fig. SEQ Fig. \* ARABIC 4 - The Lean Startup cycle (Ries, 2011)Core of the method is ‘Build -> Measure -> Learn’—the process by which order you do everything, from establishing a vision to building product features to developing channels and marketing strategies, as shown in figure 2. The faster your organization iterates through the cycle, the more quickly you’ll find the right product and market. Main part of that cycle building the Minimum Viable Product (MVP), necessary to perform what Eric Ries calls ‘innovation accounting’, which helps you objectively measure how you’re doing (Ries, 2011).In addition to that cycle, the Lean Analytics methodology is developed, as a practical guide to quantify your innovation, by providing metrics for the different stages, “getting you closer and closer to a reality check—in other words, to reality itself” (Croll and Yoskovitz, 2013, p.13). Thus within the Lean Startup cycle, Lean Analytics focuses on measuring the outcome of the stages (notify that not only the measure-stage is captured by Lean Analytics). As the methodology says: “If you measure better, you’re more likely to succeed” (Croll and Yoskovitz, 2013, p.12).01028700Summary Building methods have shifted over time from traditional approaches (Waterfall and Agile) towards a non-traditional approach, the Lean Startup. Where the traditional ones focused on building the right product, the Lean Startup focuses on building, testing and measuring product ideas through an MVP as soon as possible, which process also is called Continuous Innovation.00Summary Building methods have shifted over time from traditional approaches (Waterfall and Agile) towards a non-traditional approach, the Lean Startup. Where the traditional ones focused on building the right product, the Lean Startup focuses on building, testing and measuring product ideas through an MVP as soon as possible, which process also is called Continuous Innovation.This chapter covered the evolution of the different building approaches over time. To see how this latest developments work in practice, the next chapter will describe the lifecycle of a startup, including the different existing lean-based lifecycle frameworks.Startup LifecycleHow does a startup life cycle look like? Which stages contribute to fast growth, in order to be a startup according to the startup definitions? Which phases can a startup life be divided in? This section will first elaborate on the stages, or, the frameworks representing the stages, after which will be elaborated on the three main phases of a startup.Startup Lifecycle StagesDifferent frameworks are created over the last decade (see figure 4): Maurya (2010) created the Lean Canvas, followed by the Lean Startup by Ries (2011), McClure (2007) created the five Pirate Metrics stages AARRR, Ellis (2009) the three-tier Growth Pyramid, and most recently Croll and Yoskovitz (2013) the five Lean Analytics Stages. As shown by the framework overview below (figure 5), there is a lot of overlap in the existing frameworks. An important part missing, due to the design of this particular figure, but worth to mention, is the iterative way (characteristic of the Lean approach) in which all the steps of the different methods are executed.Fig. SEQ Fig. \* ARABIC 5 – Startup lifecycle/building frameworks (Croll and Yoskovitz, 2013) Another relevant startup-building framework is developed in the Startup Genome project by Marmer, Herrmann, Dogrultan, Berman, Eesley & Blank (2011), who created four top level stages called the Marmer Stages, based on the Four Steps to Epiphany, developed by Blank (2006). The next section will elaborate on the reason this framework is included and its content, first an overview of these particular stages will be provided (figure 6).Fig. SEQ Fig. \* ARABIC 6 – The four Marmer Stages (Marmer et al., 2011)The researchers of this research have created a new building methods overview, based on figure 5, to summarize all the frameworks as described above in one picture (see figure 7). Also, three main phases (represented by three milestones), according to Maurya (2012), are added at the right side of the picture, to increase the overall understanding of the several stages. And the Exit is included as a general ‘end-stage’, like is mentioned as being the last step in figure 5. Where Exit means: going public through an Initial Public Offering (IPO) or being acquired by another company (Davila et al., 2003). The picture immediately shows that milestones do fit to some of the frameworks, but not to all of them (especially Sean Ellis’ Growth Pyramid). Due to this inconsistency can be concluded that the content of the startup stages and target phases are not always as consistent relative to other frameworks as their names do expect.Fig. SEQ Fig. \* ARABIC 7 – Overview of all the relevant lifecycle frameworks (stages & phases)Before discussing the three main milestones of the startup lifecycle, two of the six frameworks will be highlighted in detail here: first the Lean Analytics framework, followed by the Startup Genome framework. The reason for highlighting in particular these frameworks are chosen here based on their goals and novelty, in line with this research). Lean Analytics stagesThe Lean Analytics framework, developed by Croll and Yoskovitz (2013), focuses on startup performance measurement in particular, i.e. startup analytics (therefore, this framework will be used for defining metrics in the remaining theory). Lean Analytics consists of five stages (as depicted in figure 2). (1) The goal of the Empathy stage is to identify a need, which can be solved, and where people tell they are willing to pay for a solution. Most of the results in this first stage are qualitative, some of which can be quantified. Part of the result of this stage is also known as ‘Problem/Solution Fit’ (Maurya, 2012), which will be discussed later. (2) The Stickiness phase aims at proving that a proposed solution (a MVP, not an end product), solves the problem and keeps people coming back. This stage can be quantified through measuring engagement. During this stage, you are reaching ‘Product/Market Fit’ (Maurya, 2012), which will be discussed later. (3) The next stage is Virality, which means the user growth from existing users to new users. Measuring that virality can tell the stakeholders whether user acquisition and growth can be accomplished. (4) The Revenue stage is about the money a user (customer) brings in. The core equation is the money that customer brings in minus the cost of acquiring that customer. For example: SaaS businesses can use the calculation resulting in the CLV:CAC ratio, the Customer Lifetime Value versus the Customer Acquisition Cost. (5) The last stage is Scale. From now on you can focus on large growth, for example by entering new markets. From now on more metrics at the same time needs to taken into account. Set up metrics on strategy, tactics and implementation, aligned to a consistent set of goals. The exact metrics for the particular Lean Analytics stages will be elaborated on in more detail in chapter 3.6 when discussing startup performance measurement.Marmer stagesThe second framework worth highlighting is the Startup Genome project framework, i.e. Marmer stages, consisting of four stages (see figure 2)(Marmer et al., 2011). This framework stages will be used in the remaining for the reason of simplicity and clarity of both the naming and content of the stages, compared to the other frameworks. Stage 1. It starts with Discovery of the problem: is the identified problem a meaningful problem and is anybody interested? That is what is called the Problem/Solution Fit. The discovery stage also covers the development of a MVP, Minimum Viable Product: a product with just enough functionality to test assumptions. An alternative definition on MVP is provided by Maurya (2012), as: “the minimum feature set that let’s you?start?learning about customers”. Stage 2. The discovery phase is followed by Validation of the proposed solution, resulting in feedback and money or attention, in order to refine the product and do first analytics. This validation is the search for Product /Market Fit. Stage 3. In the Efficiency phase the business model is improved to increase efficiency, through, for example, creating viral (i.e. self-sustaining) growth, according to Blank (2006, p.16) as ‘customer creation’: “creating and driving end user demand”. Stage 4. The Scale phase is all about big ‘aggressive’ growth, through, for example, massive customer acquisition and hiring the first employees, which Blank (2006, p.16) defines as ‘company building’: "transitioning the organization from one designed for learning and discovery to a well-oiled machine engineered for execution”.Startup Lifecycle PhasesAs shown in figure 3, Problem/Solution Fit (P/S Fit), Product/Market Fit (P/M Fit) and Growth are in general the three main milestones (or targets) a startup focuses on, as being three phases a startup is in. These milestones are important in the research since they represent measurable outcomes, which is a major part of this research.The first target to reach is Problem/Solution Fit: validating “there is a problem worth solving” (Maurya, 2012). Since Maurya (2012) argues that Problem validation, Solution validation and Discovery cover that same validation process, the Problem/Solution Fit in figure 3 can be considered as reached at the point in time depicted by the first horizontal border. The Product/Market Fit phase is about “building something people want and validate your business model” (Maurya, 2012). Since Retention, MVP iteration, (partly) Stickiness and Validation align to the defined phase of Product/Market Fit, the second milestone in figure 3 is drawn after this four phases. After Product/Market Fit is found, startup growth, scaling the startup, is the next phase. (Maurya, 2012). More on the three phases, including their associated techniques will be discussed in more detail here. Problem/Solution FitA startup ideally starts with a problem, not primarily an idea; therefore you need to identify the problem behind the idea to be able to work on a real problem (Maurya, 2012). This is done through the ‘Discovery’ of a potential customer segment (Marmer et al., 2011), also defined as Customer Discovery (Blank, 2006). The main part of Customer Discovery is hypotheses testing: state a customer and problem hypothesis and get in contact with these potential customers to test through interviews whether the hypothesis holds or does not hold (this is called: an experiment). Which potential customers to test, are stated in the ‘diffusion of innovations’ as the ‘Early Adopters’ (Rogers, 2010). Rogers already in 1963 started with his research and founded the theory of how innovations are adopted by a potential market. See figure 6 for the innovation adoption theory distribution and lifecycle.Fig. SEQ Fig. \* ARABIC 8 – Innovations Distribution and Lifecycle (Rogers, 2010)Thus, in this phase a startup needs to identify and validate who the innovators will be. If you have executed enough experiments to say you have significantly identified your customer segment, their problem, and a vision on a possible solution, Problem/Solution Fit is reached (Maurya, 2012; Blank, 2006). Interview results are obviously qualitative, where chapter 3.6. on performance measurement will describe metrics to validate these results quantitatively. Besides identifying the customer segment and potential solution, the P/S Fit can be used to build the test group before launching the MVP in de next phase, and deciding what goes into that MVP (Croll & Yoskovitz, 2013).Product/Market FitAs the name says, this is the search for validating your product in the market you are targeting (Maurya, 2012). In the previous phase, the startup identified the customer segment and a possible solution. This solution needs to be validated in the market, the reason why the stage similar to this phase is called the ‘Validation phase’ (Marmer et al, 2011). Therefore, industry expert and senior investor Andreessen?(2007) states the following: “The only thing that matters is getting to Product/Market fit”. Also Blank (2012) highlights the importance of Product/Market fit in the startup building process. As can be seen in 3.3.1., Ellis (2009) defines Product/Market fit as the basis of a startup. To test whether the startup has reached that validation of Product/Market fit, you need to know your customer segment as defined in the Problem/Solution fit stage and you start building your MVP, as described in 3.3.1. as “the minimum feature set that let’s you?start?learning about customers” (Ries, 2011; Maurya, 2012). Both industry experts and venture capitalists Feld and Horowitz agree on 4 P/M fit myths when discussing P/M fit for SaaS companies (Feld, 2015):Myth #1: Product market fit is always a discrete, big bang eventMyth #2: It’s patently obvious when you have product market fitMyth #3: Once you achieve product market fit, you can’t lose it.Myth #4: Once you have product-market fit, you don’t have to sweat the competitionGrowthThe growth phase consists of Efficiency and Scale (Marmer et al., 2011), quite similarly to respectively the Viral and Scale stage of Croll and Yoskovitz (2013). Ellis (2009) uses the broad description ‘Stacking the odds’, although this one will not be used in this research due to its unspecific character. Research shows that assuming too early Product/Market Fit is found, is one of the leading factors for failure. Marmer et al. (2011) define this problem as pre-mature scaling: assuming you have found Product/Market Fit and go to the Scale phase, or in that case the Growth phase. Marmer et al. (2011, p.5):“Premature scaling is the most common reason for startups to perform worse. They tend to lose the battle early on by getting ahead of themselves.”This same problem is defined by Croll and Yoskovitz (2013) as pre-mature virality: assuming there is Product/Market Fit and leaving the Stickiness phase going to the Virality (i.e. Growth) phase. Deloitte and THNK (2015) also found out in a research among 400.000 startups, that scale-ups, top-performing startups with 10M dollar revenue take twice the time a startup takes on entering a market, in order to be better prepared for growth. Therefore, this research considers the Efficiency stage as defined in Marmer et al. (2011) as a necessary part of the Growth phase , where, as chapter 3.3. describes, the business model will be “improved to increase efficiency, through, for example, creating viral (i.e. self-sustaining) growth”. This first stage in the growth phase therefore focuses on making the startup ‘growth-ready’, in order to avoid pre-mature scaling. Two methods to stabilize/ the business model for sustainable growth is through choosing the right ‘Engine of Growth’, a concept defined by Ries (2011), consisting of three possible engines (depending on the business model): the Sticky, Viral and Paid Engine of Growth. Sticky focuses on retention, keeping customers coming back on the long term, Viral focuses on the product advertising itself, through word-of-mouth, and Paid focuses on using the value created by new customers to pay acquisition for new customers (Ries, 2011). Croll & Yoskovitz (2013) are approaching the same kinds of engines through their Virality phase, distinguishing Inherent virality, Artificial virality and Word-of-mouth virality. For the three kinds of virality, they also included some examples. Inherent virality for example happens when a business promotes users to share specific content with colleagues, who also can install the software to have a better view of the content. Artificial virality for example is when inherent virality is combined with rewarding its’ users to share the content, which could be additional functions for promoting a service on social media. Word-of-mouth can use blogs for example, to spread the word.The Scale stage within the Growth phase just focuses on large growth (Croll and Yoskovitz, 2013), as Blank defines as (2006, p.16) “transitioning the organization from one designed for learning and discovery to a well-oiled machine engineered for execution”. This stage will not be elaborated on in detail.PivotsAs mentioned earlier, the phases of the four different Marmer stages are, as the Lean Startup approach prescribe, iterative: based on measuring and learning. This same approach therefore applies in the search for reaching the main milestones in the three different main phases. Through using that iterative approach, based on information (qualitative) or data (quantitative) measurement, a startup team is able to make a (fundamental) change in the business, seeing that a hypothesis they formed about one of the topics in the definition, is based on the wrong assumptions. This is what is called a ‘pivot’. A pivot is defined by Ries (2011) as “a structured course correction designed to test a new fundamental hypothesis about the product, strategy, and engine of growth”. As written, knowledge about pivots is necessary, because firstly, this explains the bumpy line figure 2 showed in section 3.1., secondly, is important to keep in mind while using and reading schematic figures (like figure 3 and figure 4) which are a model of how reality occurs and thirdly, provides an understanding in the necessity of performance measurement to avoid making fundamental mistakes during startup building, i.e. reducing risk. The importance of making those pivots, i.e. adapting to the information/data you received through measurement, is one of the major findings on startup success of Marmer et al. (2011, p.5): “Startups that pivot once or twice times raise 2.5x more money, have 3.6x better user growth, and are 52% less likely to scale prematurely than startups that pivot more than 2 times or not at all.” Like the definition of Ries provided above, a pivot in this context is defined as “a major change in the business. For example a new market or a new value proposition.” (Marmer et al., 2011, p.25).01668145Summary The startup lifecycle can be described in two complementary ways: Lifecycle framework s consisting of different Stages and Lifecycle Phases.Lifecycle StagesSix different frameworks based on the Lean approach describe the stages of startup building, whereas two are highlighted due to the clear naming and approach: the Lean Analytics stages and the Marmer stages.Lifecycle PhasesThree different phases (or milestones) are described: Problem/Solution Fit, Product/Market Fit, and Growth. Pivots are a necessary part of improving the business in an iterative way.00Summary The startup lifecycle can be described in two complementary ways: Lifecycle framework s consisting of different Stages and Lifecycle Phases.Lifecycle StagesSix different frameworks based on the Lean approach describe the stages of startup building, whereas two are highlighted due to the clear naming and approach: the Lean Analytics stages and the Marmer stages.Lifecycle PhasesThree different phases (or milestones) are described: Problem/Solution Fit, Product/Market Fit, and Growth. Pivots are a necessary part of improving the business in an iterative way.The next question is, what measures (i.e. metrics) are needed for monitoring whether a startup reaches the necessary three milestones described in the previous section, in order to manage the transition through the different stages from being a startup towards an established company? Before discussing those measures, the stakeholders (startup building programs and the ecosystem they operate in) who demand for access to information on those measures, will be discussed in the next two chapters. Startup Building OrganizationsAs mentioned in the introduction, little research is done in the field of startup building organizations, and Cohen and Hochberg (2014) do also claim that definitions on startup building organizations are unclear. This section tries to elaborate on the different forms of organizations that support startup building (the incubators, accelerators and venture builders), followed by a short description of the ecosystem where a startup operates in. HistoryBefore 2000, in the 80’s and 90’s ventures were built with help of research labs. After the Internet bust of 2000, most angel investors reduced their investments to decrease their risk. However, the starting ventures still needed their capital for launching and growing their business. This gap was the trigger of the emerging of investment firms, known as accelerators. These accelerators were led by experienced and successful entrepreneurs, to coach and mentor new ventures to reduce risk and failure rate (Radojevic-Kelley & Hoffman, 2012). Global examples of accelerators are TechStars in Colorado, Y Combinator in San Francisco, Rocket Internet in Berlin and StartupBootcamp in Amsterdam. Incubator or AcceleratorAs mentioned, there is little descriptive research on building programs, resulting in confusing definitions of incubators and accelerators (terms are even used interchangeably) (Cohen & Hochberch, 2014). However, this section tries to elaborate on the differences between both forms. An incubator in majority of the cases is an organization providing office space to starting ventures, and in some occasions access to support and/or a business network; a facilitating role towards ventures considered started from scratch, with the ability to grow (the fragile phase) (Miller & Bound, 2011). Accelerators however, are fully committed organizations, as a partnership, through investing in business and product development (Fishback, Gulbranson, Litan, Mitchell & Porzig, 2007). Accelerators are defined by Cohen and Hochberg (2014, p.4) as “a fixed-term, cohort-based program, including mentorship and educational components that culminates in a public pitch event or demo-day”. Cohort-based since they process batches of a pre-defined maximum number of startups per program period. Demo day is the final program day, designed for investors to come and see the startups, where founders can pitch their startup resulting in a chance to launch their product and service (Miller and Bound, 2011). One of the critics on the accelerator approach is that finishing a 90 days program is not an insurance that the company is strong enough to survive on its own, resulting in failure (Miller and Bound, 2011). Therefore, another program is created, the Venture builder.Venture builderThe other form of building companies is through a venture builder. It is an extended form, supporting both incubation and acceleration, and even beyond acceleration, towards growth. Venture builders are the ones providing ideas, supposed to be built by other persons; therefore these persons will become co-founders of the starting venture, i.e. startup. You closely work with/for them, in an entrepreneurial environment, for an unknown period of time (Rohé, 2012). Venture builders do not only incubate, they also accelerate and go even further, beyond acceleration to growth. The Management Team (MT) within such a venture builder can be considered as the primary stakeholder of a startup. Definitions on building organizations like a venture builder are unclear as Cohen & Hochberch (2014) found. A new definition therefore on a venture builder could be: an organization with startup ideas designed to guide entrepreneurs in building a startup for an unknown period of time. Table 1 provides a complete overview of the differences. IncubatorAcceleratorVenture builderIdeaYou bring your idea and ideally already your team.Investing cash for equity in return (usually max. € 20k).In the majority of the cases, it’s not your idea and not your company: it’s theirs.ResourcesThey give supporting resources, maybe some money, infrastructure and advice trough a mentor network.Sometimes providing Infrastructure in a program-like setup.You’re a share incentivized CEO/COO/etc.You work for/with “them” in a Entrepreneurial environment.Time periodRuns (usually) a?limited period of time.Runs a?limited period of time.Runs for an indefinite period of time.ExampleHarvard Innovation-LabY CombinatorRocket InternetTable SEQ Table \* ARABIC 2 - Different organizational forms of venture support/building (Rohé, 2012)056515Summary Mainly three types of startup building organizations exist,IncubatorIdea + Validation phase, mostly facilitating role (support and/or network).Limited period of time (therefore called Building program).AcceleratorIncreased organization commitment, main goal is receiving funding at an organized demo-day.Limited period of time (therefore called Building program).Venture BuilderIncubation + Acceleration + GrowthIndefinite period of time.00Summary Mainly three types of startup building organizations exist,IncubatorIdea + Validation phase, mostly facilitating role (support and/or network).Limited period of time (therefore called Building program).AcceleratorIncreased organization commitment, main goal is receiving funding at an organized demo-day.Limited period of time (therefore called Building program).Venture BuilderIncubation + Acceleration + GrowthIndefinite period of time.Startup Building EcosystemEcosystem OverviewObservations at the research host company as case company show the structure of the ecosystem a venture builder operates in (figure 7). Universities are involved to recruit co-founders from, Corporates to cooperate with regarding to corporate entrepreneurship, Investors to receive investments from, a local Economic Board to receive investments and other resources from, the (primarily) local Government supporting local ecosystems and defining and regulating legislation on entrepreneurship, the Suppliers are partners supplying resources necessary for startups to grow (for example: a developer team) and finally the Customers are the individuals or businesses required to buy the startup products or services. As described in 3.4., the primary stakeholder of a startup is the venture builder Management Team. The secondary stakeholder, the investor, will be discussed in the next section.Fig. SEQ Fig. \* ARABIC 9 – Venture Builder Ecosystem overviewInvestorsAs mentioned in the introduction, this research will, besides the Venture Builder as the intern stakeholder, only focus on one external stakeholder group in the ecosystem, namely the Investors. This section will describe why they play such an important role, what types of investors are involved in the startup-building field and the role of the risk factor. Before diving into those details, some background from a startup perspective. Investments and Startup Growth Hellman and Puri (2000) have found that venture-backed companies are more innovative companies compared to non-venture-backed companies. They have made a distinction between firms as innovators, which are “the first to introduce new products or services for which no close substitute is yet offered in the market”, and firms acting as imitators, which are “also engaged in relatively new products and technologies, but they are not the first movers in their markets, and therefore tend to compete on aspects other than innovation” (Hellmann & Puri, 2000, p2.) The results suggest that innovators rather than imitators do receive funding. They also found that funding is positively related to shorten the time to market, especially for the innovators. Davila et al. (2003) found that VC’s involvement increase reputation and skills for a startup. The signal of passing through the screening of a venture capitalist and receiving funding is perceived powerful by the stakeholders in the ecosystem, also inside the startup itself. Result of these positive factors is easier attraction of high quality employees, increase in the number of customers as well as an advantage in making deals with external parties. Based on a database of 494 companies in Silicon Valley, Davila et al. (2003) have found that there is a significant difference in growth of startups without venture capital, compared to startups that received venture capital (see Figure 9). The positive consequence of receiving funding is important to keep in mind. Notion: since it is hard to define growth according to revenue or even profit increase for early-stage startups, growth in their research is defined as the increase of people working for a startup (Davila et al., 2003). Fig. SEQ Fig. \* ARABIC 10 – Startups with venture-capital vs. Startups without venture-capital (Davila et al, 2003)Investor TypesHellmann and Puri (2000) distinguish six different types of funding: self-financing entrepreneurs, corporations, banks, government, angels (wealthy private individuals) and venture capitalists. This section consists of two parts: it starts with the first four types which will be discussed shortly, mainly based on Hellmann and Puri (2000), followed by the latter two types, the business angels and venture capitalists, which will be discussed more in detail, Self-financing is financing from the founders, their families and their friends. Corporate investors may also be in good position to invest and add value, due to for example their knowledge about a particular market. However, Hellman and Puri (2000) also mention that incentive problems may occur, and bureaucracy of a corporate is frequently seen as a reason for less usefulness of such a corporate investor. Here the distinction between financial and strategic types of investors comes into play (Hellmann, 2002). The incentive problems occur when corporates invest mainly for strategic reasons, where financial returns are not that important as for other types of investors. To provide an insight of how large the portion of strategic investors is, Hellman (2002) describes a survey done by Yost and Devlin (1993), who found that 93% of all the corporate investors invest for strategic returns as their main objective. Banks can be seen as a more infrequent provider of funding (Hellmann & Puri, 2000). They invest through loans and sometimes through ‘wholly owned subsidiaries’. Hellmann and Puri (2000) point out that regulatory constraints are the main reason why banks are more conservative investors. A special type of bank is an investment bank: they are particularly focussed on future transactions (an IPO for example). Also government do funding, but typically they are entirely passive and their funding mainly consists of grants (Hellmann & Puri, 2000). Now the first group stakeholders are described, the ones less important for this research, the two other stakeholders will be described in more detail: the Angel investors (interchangeably terms used in literature are Private Investors or Business Angels, which will be used from now on) and Venture Capitalists. Business Angels vs. Venture CapitalistsThis section will start shortly describing both groups, based on previous literature. First the Business Angels, followed by a description of the Venture Capitalists. The second part will elaborate more on the differences through comparison.Business AngelsBusiness Angel investors independently diversify their wealth through investing in new companies. They act in a less formal way compared to the institutional investors, for example, they mostly do not have any staff for supervising their investments and to find deals they mostly rely on their pre-existing networks. And for many of them it’s not their main professional activity. Important to keep in mind that the group of Angel investors can be considered as a heterogeneous group, therefore drawing conclusions is a delicate process.Venture CapitalistsHellman and Puri (2000) provide eleven characteristics of Venture Capitalists, the relevant ones in this research context will be highlighted here.Venture Capitalists are full-time professional investors who invest for their partnership fundsVenture capitalists tend to closely follow the technology and market developments in their area of expertise in order to stay in the deal flow and to be able to make an informed investment decisionBefore making an investment, they carefully scrutinize the founders and their business concepts They also continuously monitor their companies, both formally through participation at the board level and informallyAs monitors and through their access to private information, like banks, they can help provide certification to outside stakeholdersThey can provide valuable mentoring and strategic advice for the entrepreneurs and they frequently assist companies in providing business contacts and recruiting senior managersThey often take an active role in guiding the exit decision, such as influencing a company’s initial public offeringSimilarities and DifferencesEhrlich, Noble, More and Weaver (1994) did a literature review focused on similarities and differences between Business Angels (BAs) and Venture Capitalists (VCs). More recent research is from Maxwell et al. (2011), on Business Angels early stage decision-making. This section will describe the similarities and differences between the two types of investors.Similarities they found in theory are first on the market or technology type, where they tend to invest both in markets or technologies they are familiar with. And second on the time-period, where both BAs and VCs prefer to liquidate their investment in period of five to ten years. Both of the groups invest money in exchange for equity (Ehrlich et al., 1994; Maxwell et al., 2011).Differences they found were among others in stage and size of investment, the ownership of the investment money, geographic location of the firm, and the motivation to invest in a particular company. We will discuss those differences in more detail, mainly the investment stage and size.Investment stageFirst, the investment stages. Before reading the stage descriptions, be aware that definitions of stages differ in literature (similar problem as it is the case in the various startup lifecycle descriptions in 3.3.). BAs invest much more frequent, twenty times as many as VCs do. Therefore, they invest more money accumulated, but they tend to invest much more smaller amounts per investment, and in a earlier stage than VCs do, where in later stages the perceived risk is much lower than in the early stage (which factor will be discussed in more detail later on) (Maxwell et al., 2011). Ehrlich et al. (1994) also found that the company stages BAs tend to be involved in through funding are mainly the seed and startup stages. Also the U.S. Angel Capital Association (2014) figured out that indeed most business angels (or, angels in groups) mainly invest in the early stage of a company, a large portion in the seed stage and much fewer investments in the later stages.Fig. SEQ Fig. \* ARABIC 11 – Preferred Business Angel Investment stages (Angel Capital Association, 2014)Closing remark on the investment stages is concerning the naming of the stages: the stages are consistently different in the (traditional) investing field (like in figure 9), compared to the stages in the (non-traditional) Lean Startup lifecycle descriptions (as described in sections 3.3. and 3.4.).Investment sizeSecond, the different sizes of investment deals. The investment stage and investment size are closely related. If a company grows over time, they are likely to need a larger amount of funding. An interesting difference occurs when looking closely at how investment size has changed over time. In early investment research, done in 1994, the investment size for the early stages was less than $500.000. If the required investment increases beyond that number, VCs involvement increases. In the first stages of investment, they found that the amounts of BA investment ranges between $100.000 and $300.000, where VCs tend to participate in a range of $1 million to $3 million (Ehrlich et al., 1994). However, as research in 2014 shows, the BA investment size is increased to $1 million, however, more important, the VC investment size also has changed, starting from 4 million (Angel Capital Association, 2014). Important to keep in mind is that the results apply for the US market, where VCs are continuously growing caused by a huge growth in the startup population attracting increased investments (figure 10). An example is the increased Series A amounts of investments in startups at Y Combinator (the example accelerator in 3.4.): on a sample of 92 startups, the average Series A size in 2014 is five times larger than an average Series A in 2008 (Mattermark, 2014). Fig. SEQ Fig. \* ARABIC 12 – Increased funding sizes by stage over the last decade (Mattermark, 2015)It seems positive that funding deal sizes are increasing, related to the positive influence on startup growth as discussed earlier. However, the Angel Capital Association found when VCs are able and willing to invest larger amounts of money, due to their growing funds, and BAs do not tend to invest larger amounts per investment deal, a funding gap appears, as shown in figure 11 (Angel Capital Association, 2014). This gap can result in a increasing toughness of survival for startups during their transition process from startup to company, since receiving financing influences the startup continuity and growth (as described before, in figure 8).Fig. SEQ Fig. \* ARABIC 13 – Investors per stage, including the Funding Gap (Angel Capital Association, 2014)Remaining DifferencesOne of the other distinctions Maxwell et al. (2011) make is that BAs tend to invest their own money, because they are those wealthy individuals Hellmann and Puri (2000) talk about, where VCs tend to invest other people’s money. Geographic location is point of difference too. Where BAs tend to look at startups within 50 miles of where they live, VCs focus on seeking startups in specific areas like major cities where they are able to network with other VCs as well (Ehrlich et al., 1994). The motivation to invest differs for both groups where BAs are more likely to help a family member or friend or deriving non-monetary appreciation as a result of assisting other entrepreneurs in building companies, since they (mostly) were entrepreneurs themselves before they started investing (Ehrlich et al., 1994; Hellmann & Puri, 2000).Mason and Harrison (2002) compared BAs to VCs. They found that BAs focus more on avoiding bad investments, which is related to less ability for diversification. However, their gains from their investments are high. That could be caused by a better selection process or by their higher degree of involvement through for example value adding by knowledge. BAs have more entrepreneurial experience, whereas VCs have more investing experience. They also found that in terms of meeting frequency, BAs meet companies less often before investing than VCs do. As the characteristics describe, investors are closely involved in the company. They evaluate and monitor the companies intensively and continuously. The next chapter on Performance Measurement will discuss in detail which criteria are being used by both types of investors. Before that, one other important phenomenon needs some description. That is the factor of ‘risk’, which stands for the risk of losing your investment money invested in a startup.Investment Risk and Startup SuccessAs described earlier, Ruhnka and Young (1987) already described that particular risk phenomenon (Figure 11). Interesting to see is that already did research in 1987 investigating stages of company development, as can be seen in figure 12, where they have segregated a startup in phases. Slightly comparable to the four stages of Marmer et al. (2011), as described in chapter 3.3., and an additional fifth stage, the Exit. Fig. SEQ Fig. \* ARABIC 14 – Risk of Loss of Investment (Ruhnka & Young, 1987)As Ruhnka & Young (1987) does the risk decrease over the period of the life of a startup, related to information availability and therefore an improved ability to predict the startup success. An example of an implication of risk related to investor actions, is one of the findings of Kaplan and Stromberg (2004) who analysed 67 investments by 11 VC’s, where a higher (internal, i.e. team and product) risk is related to: the VC desiring more control, VC’s providing higher compensation to the entrepreneur and a higher contingency of a financing round.But why is that risk phenomenon that important to investors (and to the startups as their subjects)? Previous research towards investing criteria, consider venture capitalists as experts on the evaluation of companies, and the factors of risk defined by those VC’s are directly interpretable as success factors for those companies (Tyebjee and Bruno, 1984; Franke, Gruber, Harhoff and Henkel, 2008). Therefore this research will consider risk factors as a necessary part to be involved in this research, needed in the descriptive as well as the practical implications in in the following sections. Startup Evaluation As Franke et al. (2008) describe, research towards startup evaluation criteria has a long history, started in 1970 already, and still considered as a topic of interest in the present. They structured the evaluation criteria of previous research, in order of relative importance of several criteria, in a range from 1974 until 1999. This theoretical background will focus on literature in startup evaluation research from 2000 until now. The risks (i.e. evaluation criteria) appear in different categories, Maxwell et al. (2011) found. They listed four different risk categories (see figure 15), where Endogenous consists of the internal risk effects and Exogenous consists of the external risk effects. As discussed, these factors are equal to startup evaluation factors when establishing a potential relationship with those particular startups as a stakeholder, e.g. an investor. Fig. SEQ Fig. \* ARABIC 15 – Risk categories and related Endogenous and Exogenous examples (Maxwell et al., 2011)In an overview consisting of previous research on company evaluation can be seen that these risk factors are similar to the success factors (see table 3). The sources are chosen based on authority of the authors, diversity in investor type (including BA and VC), startup type (including digital and biotech), and publication year (> 2000).Author(s)PerspectivesFactorsOrder / WeightMiloud et alIndustry Organization economicsProduct differentiationn.a.2012Industry growth raten.a.Venture CapitalistsRecource-based viewIndustry experiencen.a.?Top Management experiencen.a.?Startup experiencen.a.?Top Management team (TMT)n.a.?Team completenessn.a.?Network theoryNetwork sizen.a.Baum & SilvermannAlliance capitalDownstream alliancesn.a.2004Upstream alliancesn.a.Biotech startupsHorizontal alliancesn.a.?Intellectual capitalPatent applicationsn.a.?Patents grantedn.a.?Human capital (TMT)Size TMTn.a.?President no of rolesn.a.?President entrepreneurial activityn.a.?President entrepreneurial abilitiesn.a.Maxwell et alV1 – Market potential (market size)Is there a large market for this product?A Large market potential (i.e. over $20 million)2011B Medium market potential (i.e. over $5 million)Business AngelsC Unable to predict — likely less than $5 million.?V2 – Product adoption (market share)Will customers in target market easily adopt this product?A Customers will easily adopt product or service?B Benefits harder to identify, some adoption issues?C No clear benefits, or major adoption issues?V3 – Protectability (profitability)How easy will it be for other people to copy the product or service?A Product patented or significant other barrier?B It will not be easy to replicate.?C Anyone could copy it easily.?V4 – Entrepreneur experience (reputation)Does management have direct and relevant experience?A Significant relevant experience?B Limited experience, but appropriate knowledge?C No evidence of required experience?V5 – Product status (for technology risk)Product ready for market, or major work required before it ships?A Finished product?B Design complete all technical issues addressed?C Needs more research and development?V6 – Route to market (for operational risk)Is there a realistic marketing plan and route to market?A Realistic marketing plan / distribution partner?B Options identified — no agreements in place?C Limited thought given to distribution issues?V7 – Customer engagement (for market risk)Is a first customer identified? Does product meet need?A Customers in place, or committed to purchasing?B Customers engaged in development project?C No first customers identified.?V8 – Financial projections (for financial risk)Profitable and sustainable cash flow?A Sound business model and cash management?B Unclear profitability, limited cash management?C No evidence of profit or cash management?Where [V1 - V4 : Forecasted venture value (ROI), aggregated to Va] [V5 - V8 : Risk assessment values, aggregated to Vb]??No trade-off between Va & Vb???Kaplan & Stromberg ??Reason to Invest (Strength)Risk of Investment (Weakness)2004 Internal FactorsQuality of management 59,7%61,2%Venture CapitalistsPerformance to date26,9%7,5%?Funds at risk/downside19,4%13,4%?Influence of other investors6,0%6,0%?VC portfolio fit and monitoring cost17,9%14,9%?Valuation20,9%19,4%?External FactorsMarket size and growth68,7%31,3%?Competition and barriers to entry32,8%40,3%?Likelihood of customer adoption29,9%22,4%?Financial markets and exit conditions16,4%7,5%?Difficulty of ExecutionProduct and/or technology40,3%31,3%?Business strategy/model53,7%50,7%Gompers et al ??Success Probability/Prediction2010 Venture CapitalistsEntrepreneur - prior experienceSecond/later venture vs. First venture20,9% vs. 25,0 %Entrepreneur-Company prior successSuccessful serial vs. Failing serial vs. First-time30,6% vs. 22,1% vs. 20,9%?Company-Entrepreneur prior successSuccessful serial vs. Failing serial vs. First-time30,9% vs. 21,2% vs. 17,1%?VC experience & Successful serial entrepreneurExperienced vs. Less experienced32,4% vs. 31,9%?VC experience & Failed serial entrepreneurExperienced vs. Less experienced25,9% vs. 17,7%?VC experience & First-time entrepreneurExperienced vs. Less experienced20,9% vs. 14,2%?Market timing (i.e. predicted success)Industry success rate High vs. Low31,4% vs. 25,0%?Managerial skill (i.e. residual success)Past success High vs. Low34,9% vs. 26,6% Table SEQ Table \* ARABIC 3 - Research overview on company success/risk factors of the last decadeWhat immediately can be noticed are the comparable categories of startup success factors over the years of research. These success factors will be categorized into factors taking their priority into consideration. The first main category is the Team factor, represented by factors like top management experience, team completeness, size top management team, quality of management, entrepreneur prior success, etc. The second main category is the Product & Market, represented by factors like product differentiation, patents, product status, industry growth rate, several types of alliances, market potential, product adoption, competition and barriers to entry, etc. The third main category is the sum of the activities/results within the startup itself, which will referred to as the Startup, represented by factors like cash flow, business strategy/model, etc. As Davila et al. (2003) describe does the due diligence process, the investors’ evaluation/screening process of a startup, focus in a very detailed manner on the different factors as described above. Another moment of startup evaluation is the so-called ‘post-money valuation’, which is “the standard way of valuing firms in the venture capital industry”, after a financing round has taken place (Hellman, 2002, p.287). Hellman (2002) however, points out the lack of reliability of a post-money valuation, since it does not reflect the support a investor provides, which is an intangible company asset and therefore hard to evaluate.Performance MonitoringGompers (1995) describes why capital infusions, i.e. financing rounds, the most powerful control mechanism is for a venture capitalist, doing a major review of the progress, the due diligence and their decision to continue with follow-up funding. Therefore, the duration of a financing round can be considered as a metric for the monitoring intensity. For example: the shorter the financing rounds are, the greater the information need for monitoring a startup and entrepreneur’s progress is. Monitoring can be considered as valuable, useful to track the progress of a firm and possibly cut off financing in future rounds when there is negative information about the future of a firm. Gompers (1995) also found that monitoring intensity decreases due to increases in financing duration and tangibility of assets within a firm.Gompers (1995) does also describe the claim of venture capitalists on generating information and providing services as being as important as their financing, in contrast to what entrepreneurs believe. Early-stage startups do not have a track record, and therefore no historical information to provide. Thus does Gompers (1995) argue, VC’s should invest in those companies to increase the companies’ information oversight since they lack that particular information oversight. Gompers (1995) also found that firms in industries with significant growth opportunities and high R&D intensity results in close monitoring. Monitoring costs can be substantial for a VC when reading reports takes time away from other activities (Gompers, 1995). Although VCs monitor companies frequently, entrepreneurs still do have private information about their company. The frequency of monitoring checks is researched by Gorman and Sahlman (1989), through a survey among 49 VCs in 1984. They found that between financing rounds the lead VC visits the portfolio company once a month, for about four to five hours on an average visit. The other non-lead VCs do their check-up less frequently, typically once a quarter, for about two to three hours on an average visit. VCs request for monthly reports, and do not prefer to become involved in the management of the portfolio company. Gompers (1995) concludes that corporate control can be seen as “a fundamental concern of investors”.Davila & Foster (2005) indicate that the involvement of venture capital becomes mostly for the first time the request for formal monitoring. According to Gorman and Sahlman, this can be related to monitoring (i.e. agency) costs. Therefore, this is the point in time that through encouragement of VCs, the use formal information systems to monitor the startup performance comes into play. This is part of the professionalization VCs bring to early-stage startups they invest in (Hellman & Puri, 2000). Figure 14 shows the findings of Davila and Foster (2005) and Hellman and Puri (2000) on increasing adoption of Information Systems (ISs) after a startup receives VC funding. Fig. SEQ Fig. \* ARABIC 16 – Percentage of companies adopting different types of ISs since receiving VC funding (Davila & Foster, 2005)-114300114300Summary A positive association exists between receiving funding and startup growth, for example through increasing reputation and skills of a startup. Six different investor types do exist, whereas the most important ones considering this research scope are the Business Angels (BAs) and Venture Capitalits (VCs). These latter two types differ in: investment stage, investment size, geographical preference, investment motivation, and risk avoidance. Investment risk decreases related to startup maturity. Risk factors are similar to success factors, which can be used in startup evaluation. To know more about the success factors from literature, an overview of previous literature on risk factors is provided, which factors can be categorized into Team, Product & Market, and Startup.Related to those risk (i.e. success) factors is the performance monitoring of startups. Information on those factors is necessary, where financing rounds are the most powerful events to gather that particular information. Information Systems (ISs) are useful for that, which is shown by the increasing adoption of ISs.00Summary A positive association exists between receiving funding and startup growth, for example through increasing reputation and skills of a startup. Six different investor types do exist, whereas the most important ones considering this research scope are the Business Angels (BAs) and Venture Capitalits (VCs). These latter two types differ in: investment stage, investment size, geographical preference, investment motivation, and risk avoidance. Investment risk decreases related to startup maturity. Risk factors are similar to success factors, which can be used in startup evaluation. To know more about the success factors from literature, an overview of previous literature on risk factors is provided, which factors can be categorized into Team, Product & Market, and Startup.Related to those risk (i.e. success) factors is the performance monitoring of startups. Information on those factors is necessary, where financing rounds are the most powerful events to gather that particular information. Information Systems (ISs) are useful for that, which is shown by the increasing adoption of ISs.Startup Performance Information ManagementHow will startups survive and grow in the programs and ecosystems described in the previous section? What relevant information is needed and available to monitor and manage the startup lifecycle? The previous section on monitoring startup success factors will be elaborated in this chapter. In addition to that, different stakeholders (different types of investors in this research) require different types of information. This section will discuss Startup Performance Information Management (SPIM) to support defining, measuring and communicating progress of startups through their lifecycle. Defining Performance MeasurementThe online business dictionary defines Information Management as the “application of?management?techniques?to collect information, communicate it within and outside the organization, and?process?it to enable?managers?to make quicker and better?decisions” (Business Dictionary, 2015). Many terms are used in processes concerning information management within companies, thus first some clarification between the two most relevant ones, Business Intelligence and Business Performance Management, is needed. Business Intelligence stands for the process and information to help managers reviewing the performance of an organization, whereas Business Performance Management focuses on both the quality of the information and the performance of an organization (Chaffey & Wood, 2004). Bringing the definitions on Information Management and Business Performance Management together makes Performance Information Management the collection and communication of the performance information produced through the execution of Business Performance Management, in order to make quicker and better decisions. In the context of this research those terms will be merged into a new term, in order to improve clarity concerning that context: Startup Performance Information Management (SPIM). SPIM is introduced before as the main topic of this research, where Performance Measurement serves as the process behind collecting data within SPIM.To make information management easier and faster by digitalizing it, i.e. digitalizing the management processes, Information Systems are developed. Laudon and Laudon (2006) did research towards managing ‘the digital firm’. However, they point out that before digitalizing firms, i.e. implementing information systems, “one must understand the problems they are designed to solve, their architectural and design elements, and the organizational processes that lead to these solutions” (Laudon & Laudon, 2006, p.8). Therefore this chapter will focus on two parts. First the exploration of the needs for performance measurement for internal and external stakeholders. This can be seen as a theoretical background of a hypothetical performance information management system, in order to be able to provide the second part, a high-level advice on a design approach for that particular information system.Performance Measurement GoalsWhy performance measurement? To improve startup (or ‘business’) performance, performance measurement is a crucial element (Taticchi, Tonelli & Cagnazzo, 2010). Also taking into consideration that, as described in the previous section, collecting information through information management is a crucial part of making quicker and better decisions. Franco-Santos, Kennerley, Micheli, Martinez, Mason, Marr, Neely (2007, p.9) define the performance measurement objectives as: “organizations measure their performance in order to check their position (as a means to establish position, compare position or benchmarking, monitor progress), communicate their position (as a means to communicate performance internally and with the regulator), confirm priorities (as a means to manage performance, cost and control, focus investment and actions), and compel progress (as a means of motivation and rewards)”.Wickman (2011) describes eight company (internal) advantages of having numbers on performance measurement in a company:Numbers cut through murky subjective communication between manager and direct reports. They become a communication tool between manager and direct reports, creating the basis of comparison, unemotional dialogue and results.Numbers create accountability. When you set a number, everyone knows what the expectation is. Accountability begins with clear expectations and nothing is clearer than a number.Accountability people appreciate numbers. Wrong people in the wrong seats usually resist measurables. Right people in the right seats love clarity. Knowing the numbers they need to hit, they enjoy being part of a culture where all are held accountable.Numbers create clarity and commitment. When an employee is clear on his or her number and agrees that he or she can achieve it, you have commitment. There is no grey area.Numbers create competition. There’s nothing wrong with a little pressure.Numbers produce results. What gets watched improves.Numbers create teamwork. When a team composed of the right people in the right seats agree to a number to hit, they ask themselves “how can we hit it,” creating camaraderie and peer pressure.You solve problems faster. When an activity-based number is off track, you can attack it and solve the problem proactively; unlike with an end-result based number that shows up after it’s too late to change it. In addition, the use of hard data cuts through all of the subjective and emotional opinions that create murkiness and lengthen the amount of time it takes to make the right decision.These eight advantages clearly explain how metrics contribute to clear communication between employees and drives to company success. The Startup Genome Project, in collaboration with the Stanford University and Berkeley University, performed an in-depth research into the success factors of 650+ web startups located in Silicon Valley, from 2004 till now. Their first key finding also highlights the importance of performance measurement, in this case combined with mentoring and proven methods usage (Marmer et al., 2011, p.5):“Founders that learn are more successful: Startups that have helpful mentors, track metrics effectively, and learn from startup thought leaders raise 7x more money and have 3.5x better user growth.”The way to track these metrics is what performance measurement is. Performance measurement consists of measures defined by Neely, Mills, Gregory and Platts (1995, p.1) as: “metrics used to quantify the efficiency and/or effectiveness of action”. Note: from now on those measures will be referred to as ‘metrics’.Financial-to-Innovation Paradigm ShiftIn traditional companies, Neely (2002), identified three different business perspectives (i.e. business functions), which can be used for performance measurement: The Accounting perspective, Marketing perspective and Operations perspective. However, as discussed in chapter 3.1, startups transitioning towards high growth companies do not have these mature business functions in place yet as traditional companies do have. Instead, as described in previous chapters, the Lean Startup building approach focuses primarily on the early stage of a company, when creating and managing the startup, to get the desired product to the customer as quick as possible, using innovation accounting: objectively measuring how you are doing (Ries, 2011). Maurya (2012) does also describe the movement where accounting has shifted from Financial accounting, focused on the cost and revenue part, used for late-stage companies, to Innovation Accounting, focused on the early stage of a company. Therefore, the Lean Startup loop is created as an approach to continuously test and measure whether the hypotheses (i.e. assumptions) of a startup, about their problem, customers and solution, can be proven by customer discovery and validation (Blank & Dorf, 2012). To eliminate uncertainty as much as possible, the Measure part is included in the iterative loop of Lean Startup as shown in chapter 3.2 (Ries, 2011). An interesting link to the changing paradigm shift and the investors perception on these paradigms is one of the findings of Marmer et al. (2011, p.13), who found that “better performing VCs understood that startups are a search process for product market fit and a scalable business model. As a result, they drew conclusions based on more subtle data points (..)”. In line with the performance measurement as described in the introduction of this section, this proves the need for (non-traditional) performance measurement during startup building. MetricsNext reasonable question following from preceding theory then will be: which metrics can be considered as relevant for measuring the performance of startups? And how to apply those metrics, what is the usability of those metrics? Therefore this chapter will first elaborate on the metrics itself, followed by describing how to focus on the right metrics.The metrics descriptions will be divided into two parts: the general metrics and the stage-dependent metrics. General aims at the metrics involved at all stages of a startup, where stage-dependent metrics are about metrics only tied to one or (maximum) two specific phases. Both sections will conclude with a metric overview.General MetricsThe general metrics are divided into three main categories, aligned to the risk/success factors as found in section 3.5.2.: Team, Product & Market and Startup. TeamThe startup team is one of the main variables of interest in a research from Deloitte and THNK, among a population of 400.000 companies, founded since 2005, over 24 countries (Deloitte & THNK, 2015). In their research they focused on the scale-ups and unicorns among these startups, where they define a scale-up as a company with a revenue level of 10 million dollar in their fifth year, and being classified as a unicorn requires a valuation above 1 billion dollar (like Facebook, Google, and ?ber). The set of global unicorns consists only of 104 startups at the time of research (early 2015), where nowadays 144 unicorns do exist (late 2015) (CBInsights, 2015).SizeA team of at least two persons versus a single founder starting the company is the case in approximately 50% of the scale-up population (Deloitte & THNK, 2015). ExperienceOne of the major findings is that 78% of the scale-ups is founded by a team consisting of at least one person with corporate or entrepreneurial experience. In the case of the unicorns, that’s even the case in 89% of their teams. For the remaining startups, called survivors, the number is 57%. Having industry specialists on board is perceived as effective since 61% of the scale-up leaders in the UK state this as a grow accelerating team component. For the unicorns, even 85% of the teams have at least one experienced specialist on board (Deloitte & THNK, 2015).BackgroundThe university dropout becoming a billionaire by launching a startup is rarely the case. Most of the founders of scale-ups have an academic degree, e.g. a bachelor diploma, master diploma or PhD (Deloitte & THNK, 2015). Product & MarketExisting AlternativesAs Chaffey and Wood (2004) describe, one of the goals of management information gathering is being aware of the external environment and respond to activities in that particular environment, monitoring for example competitor activity like new product releases. In line with Blank and Dorf (2012) above, this research will focus mainly on entering new markets, a continuously monitoring for new entrants on a particular (new) market will be useful, according to Chaffey and Wood (2004). However, the competitor focus also receives critics from Lean startup focused leaders, whereas Maurya (2012) focuses more on existing alternatives used by customers than primarily on competitors. Especially in new markets, competitors enter that particular market from the moment of initial startup success, thus not at the early early-stage (or seed stage) of a startup (Maurya, 2012). Therefore this metric is called existing alternatives instead of the traditional competitor focus.Target Market As discussed in 3.3.2.2., Product/Market cannot be considered being a bing bang event or something you cannot lose as a startup. Therefore, the search for the right target market will be discussed both as a general metric as well as a stage-dependent metric.43434001684655Fig. SEQ Fig. \* ARABIC 17 – TAM, SAM, and Target Market (Blank & Dorf, 2012)Fig. SEQ Fig. \* ARABIC 17 – TAM, SAM, and Target Market (Blank & Dorf, 2012)42976802413000As Blank & Dorf (2012) show in figure 14, the market of a startup can be distinguished into three different types: TAM corresponds to the whole ‘universe’, Served Available Market (SAM) corresponds to the reach of a startup Sales channel, and Target Market describes the number of startup prospects, i.e. potential buyers of your product. Blank and Dorf (2012) suggest in their theory that startups need to focus on the latter only.These markets are quantifiable in terms of size for existing markets, however, most startups focus in particular on new markets, where they don’t know who their target customers will be (Blank & Dorf, 2012). This is where the search for the business model in the startup definition in 3.1. corresponds to. Therefore the key is not primarily competing, like discussed at the previous metric, but getting an understanding where a large customer base exists and how those customers behave (Blank & Dorf, 2012). StartupThis section will describe which metrics are involved as startup general metrics, concerning financials and the business model.FinancialsJust since some years, more knowledge about useful metrics for early-stage startups evolved. Where traditional measures were for example profit and loss, balance sheet, cash-flow forecast, etc., early-stage startups are more focused on testing customer and market hypotheses rather than these (quite static) financial metrics (Blank & Dorf, 2012). Blank and Dorf (2012) argue that a startup only needs to focus on a few financial metrics: cash-burn rate (or burn-rate), number of months’ worth of cash left (defined by Ries (2011) as ‘runway’), short-term hiring plans and time needed to reach the cash-flow break-even point. PivotsAs 3.3.1. describes, the number of pivots is crucial, where startups pivoting once or twice are much more successful than startups pivoting more than two times or pivoting not at all. According to Ries (2011) and Marmer et al. (2011), business changes can be considered as pivots when there is a major change in the business (e.g. a new market) LearningSince theory as discussed in 3.6.1. shows that tracking metrics effectively and learning from startup thought leaders (i.e. mentors and usage of proven building methods) leads to better growth, these both learning parts can be considered as relevant to track if they are used in the startup daily activities as well. Tracking metrics effectively sounds subjective, however theory has made a distinction between vanity and actionable metrics, it is possible to measure whether metrics are used in an effective way (3.6.3.5. will elaborate on picking the right metrics). Also checking whether a startup receives help from mentors and usage of proven building methods is easy to check.ConclusionThis section will describe the quantify equivalent of the metrics described in the preceding theory above, on Team, Market, and Startup.Team Size: no. of founders Experience: corporate/entrepreneurial/none; no. of industry specialistsBackground: academic degreeMarketExisting Alternatives: no. of existing alternativesTarget Market: no. of potential customersStartupFinancials: burn rate; runway; short-term hiring plan; time-to-break-evenPivots: no. of pivotsLearning: effective metrics implemented; mentor help + usage of proven building methods Stage-Dependent MetricsBased on 3.3.2., this section will discuss the relevant metrics in the order of the four stages of the Startup Genome framework (Discovery, Validation, Efficiency, Scale), which are tied to the three thresholds (i.e. milestones) defined by Maurya (2012) (Problem/Solution fit, Product/Market fit, Growth). Each of these parts will first provide a short recap on the particular phase, followed by providing potential metrics. As proposed in 3.3.1., the Lean Analytics framework will be incorporated here, to use the best practices (metrics) from that particular (state-of-the-art) framework, since they particularly focus on startup performance measurement, i.e. measuring the different phases of the Lean Startup method.DiscoveryTo measure whether a startup has reached the P/S Fit, i.e. as 3.3.2. describes, a startup has to discover (i.e. identify) the problem and the customer segment experiencing that particular problem, executing experiments is the major activity of this phase. The results experiments results are mainly qualitative (Croll & Yoskovitz, 2013). To have data to base the next action upon, an entrepreneur needs to verify those results quantitatively on people he assumes as being prospects. Therefore McClure (2007) relates the metric Acquisition to this particular phase, as the metric to monitor an increasing (potential) user base, i.e. prospects.Qualitative research done in a scientific manner, as the method part of this research describes in chapter 2, uses extensive processing steps in order to form a grounded theory derived from interviews. The Lean Startup movement has developed their own way of qualitative research, in order to be as quick as possible and still paying much attention to interview results. Two ways of using an actionable metric to quantify the qualitative results within the P/S fit phase are provided by Maurya (2013) and Croll and Yoskovitz (2013). The first one, is the Customer Factory created by Maurya (2013), using four of the five AARRR (pirate) metrics as defined by McClure (2007) (see figure 16). From these P/S Fit phase-tailored metrics, the most important rate to measure whether the startup is on track on reaching P/S Fit, is the Revenue, in this particular case 20%, symbolizing what Maurya (2013) calls the ‘production-rate’, i.e. problem/solution interview success-rate. This rate is derived from the percentage of persons interviewed who want to pay for a potential solution, as part of the group of persons interviewed about a possible solution, the Activation number, which is the remaining part of the first step, the problem interviews, which is described by the Acquisition number. A Business-to-Business (B2B) startup requires other numbers than a Business-to-Consumer (B2C) startup, an example could be that a B2B startup requires 100 interviews to start with, where a B2C startup needs 1000 interviews to start with (Maurya, 2013). Referral describes the number of prospects referred to by persons interviewed in the solution interviews, which can be used as acquisition prospects for the next iteration. After enough iteration steps the startup needs to reach an 80% ‘production rate’ as a signal for reaching P/S Fit, which in the example of figure 16 is 20% (Maurya, 2013). -5080000Fig. SEQ Fig. \* ARABIC 18 – Example Problem/Solution fit interview conversion metricsThe second possible way of verifying your P/S Fit discovery in a quantitative manner is provided by Croll and Yoskovitz (2013). Scoring a list of six questions can tell a startup whether the problem they want to solve is painful enough to solve. Attachment A shows the whole list including the scores; one example is provided in table 4 (see next page). Question 1. Did the interviewee successfully rank the problems you presented?ScoreYesThe interviewee ranked the problems with strong interest (irrespective of the ranking)10Sort of He couldn’t decide which problem was really painful, but he was still really interested in the problems5NoHe struggled with this, or he spent more time talking about other problems he has0Table SEQ Table \* ARABIC 4 – First out of six question to calculate the interview score in the P/S Fit (Croll & Yoskovitz, 2013)The sum of the six question scores can tell whether a startup has found a P/S Fit, explained by a score of a range between 0 and 35, where a score of at least 31 proves P/S Fit is found.Assuming a startup has discovered P/S Fit, the next phase can be entered, which will be the validation of an MVP in order to reach P/M Fit.ValidationAs 3.3.2. describes, this phase is about validating your potential solution, explained by terms like MVP iteration (Ries, 2008), Stickiness (Croll & Yoskovitz, 2013) and Validation (Marmer et al., 2011). This phase mainly focuses on testing the MVP, therefore data on MVP testing is the core part (Croll & Yoskovitz, 2013). MVPs can appear in different types (video’s, prototypes, etc.). To narrow down the focus on MVPs in order to be able to provide example metrics, the SaaS focus of this research will be used. A SaaS MVP could be a prototype of the potential solution, for example, an investing platform, accessible trough the internet, reaching the target customer segment via associated channels, which could be the mailing-list of the customer segment the startup already gathered in the Discovery phase. The startup can measure and learn how its’ MVP is doing, by tracking users’ Activation and Retention, in SaaS solutions measured by the so-called metric on Engagement (McClure, 2007; Croll & Yoskovitz, 2013). The metrics are, compared to the previous phase, of increased usefulness due to their quantitative character. When should a startup consider P/M Fit as reached? Maurya (2012) advocates using the threshold Ellis (2009) has defined, proven through usage among 100+ startups. The startup has to ask their prospects the following multiple-choice question: “How would you feel if you could no longer use product X?” His rule dictates prospects to choose one of the following answers:Very disappointedSomewhat disappointedNot disappointed (It isn’t really that useful)N/A – I no longer use Product XP/M Fit can considered as being reached “at least 40% of users saying they would be “very disappointed” without your product”, whereas his research shows that startups scoring below 40% always struggle on their following lifetime (Ellis, 2009).Gross (2015) did research among 100+ startups started within Idealab, a venture builder organization, and presented his findings at a TEDTalk. He found out that finding the right market at the right time in matters most, compared to the idea and the execution of that particular idea: “execution definitely matters a lot.?The idea matters a lot.?But timing might matter even more.?And the best way to really assess timing?is to really look at whether consumers are really ready?for what you have to offer them” (Gross, 2015).As the above has shown, the first customers start using the product in this stage. Startup performance metrics provided by Croll and Yoskovitz (2013) are shown in table 5. Which are comparable to the characteristics of Acquisition and Activation (McClure, 2007). Note that revenue-related (monetizing) metrics are not applied by the authors yet.MetricDescriptionAttentionHow effectively the business attracts visitorsEnrolment (conversion)Number of visitors becoming free or trial users (first conversion), if you’re relying on one of these models to market the service StickinessNumber of customers using productChurnHow many users leave in a given time period. Bottom-line: for early-stage companies churn should be 5%, to consider business as sticky. Feature UtilizationWhat features are used and therefore ask yourself what to build next into your MVP. Table SEQ Table \* ARABIC 5 – Usage validation metrics (Croll and Yoskovitz, 2013)Skok (2013), SaaS expert and five-time serial entrepreneur, currently VC, describes the acquisition and activation metrics as funnel metrics, where conversion is the link between the several metrics. Therefore, the previous P/S Fit related Customer Factory (Maurya, 2013), can be used in this P/M validation stage as a visualization of funnel metrics as well. The funnel metrics can be used in forward planning, for example calculating how many sales people are required in order to attract more visitors and turning them into users and possibly paying customers. After finding (the first) P/M Fit and having the first metrics in place, a startup can proceed to the next phase, Efficiency.EfficiencyThis particular phase is included, as discussed in 3.3.2., to avoid pre-mature scaling (Marmer et al., 2011) or pre-mature virality (Croll & Yoskovitz, 2013), which are described as one of the major reasons for startup failure. If a startup invests in user growth, but still has a high churn (i.e. low retention), return on investment will be (dangerously) low (Croll & Yoskovitz, 2013). Therefore, this phase will focus on increasing efficiency, by creating self-sustaining growth (i.e. virality). However, still do Croll and Yoskovitz (2013) warn for only focussing on reaching that efficiency/virality, on the expense of engagement: getting new users is great, however losing engagement is possible when new users are different from your first users, the early adopters. This corresponds to Skok (2013), who defines three main goals of SaaS businesses: Acquiring customers, Retaining customers and Monetizing customers. He provides metrics for startups to monitor how they are doing in reaching these three goals. The Efficiency stage needs to focus on Retaining customers effectively, as Skok (2013) describes as avoiding churn through negative-churn, to be able to recover revenue from loosing through churn, in order to keep a startup growing. A method to enable negative churn is for example through upselling when growing. Therefore a startup needs to identify the churn problem in time, in order to be able to define a roadmap (strategy) for negative-churn on time (Skok, 2013), in the Efficiency stage. Ries (2011) provided a method to realise self-sustaining growth, through the so-called Engine of Growth (EoG) (Ries, 2011), or similar the different types of Virality (Croll & Yoskovitz, 2013), as 3.3.2.3. describes. Stakeholders want to know for this particular stage whether user acquisition and growth can be accomplished as 3.3.2. describes. Therefore, Croll and Yoskovitz (2013) define the key quantifying measurement here as the ‘viral coefficient’: the growth number of new users per existing user. Where a viral coefficient above 1 means that every single user is inviting at least another user. Besides focusing on that particular coefficient, the cycle-time of virality is important too, which explains the time it takes for a user to invite another user, which determines fast or slow growth in the user base (Croll & Yoskovitz, 2013). Since prospects are turned into users and possibly even paying users in this phase, when the MVP is validated and the product is live, from now on financial metrics (like Revenue) need to be monitored as well. The metrics are listed in table 5, some including bottom-lines describing what numbers represent a healthy SaaS business. Those bottom-line numbers are based on Skok (2013) and Croll and Yoskovitz (2013) (the latter also use the experience of Skok to form their theories). MetricDescriptionRevenue-per-customerHow much money a customer brings in within a given time period. Bottom-line: Grow 20% from year to year, trough: series of tiered offerings and easy upselling path.Total (recurring) RevenueMonthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR).ConversionNumber of users becoming paying customers, and how many of those switch to a higher-paying tierChurnHow many users and customers leave in a given time period. You have to see a clear path to getting churn below 2% if you want to scale significantly. Negative churn roadmapThere must be a roadmap in place explaining the strategy for negative churn for the next phase. Methods: product expansions, upselling, and cross-sells, to your current customer base.Customer Acquisition Cost (CAC)How much it costs to get a paying userCustomer Lifetime Value (CLV)How much customers are worth from cradle to graveCLV : CAC (value)The CLV to CAC ratio, meaning the ratio of the costs of customer acquisition and the value a customer brings into the company.Bottom-line: CLV > 3 x CAC. In optimal form higher than 3, sometimes even 7 or 8.CLV : CAC (time)A time-bound CLV:CAC ratio is about profitability and cash flow. Bottom-line: Months to recover CAC < 12. A well-performing startup needs to recover from the CAC within 12 months after acquiring that particular customer, where many of the best recover in 5-7 months. Larger businesses can afford to have a longer recovery-time.BillingsThe amount that you have invoiced that is due for payment shortly.Uptime and ReliabilityHow many complaints, problem escalations, or outages the company has.Table SEQ Table \* ARABIC 6 – SaaS startup metrics - Efficiency (Croll & Yoskovitz, 2013; Skok, 2013)A calculation example on recovering from CAC till a customer breakeven point is reached, is provided by Croll and Yoskovitz (2013). They calculate that the CAC of $14 is recovered through monthly revenue of $2.45 in (14/2.45) 5.7 months to customer breakeven, which is related to burn categorized in general metrics.ScaleThis phase will add extra metrics to the existing phase. The metrics a startup already tracks from the previous phases can be put into an accounting system. And, metrics that were seen as being distractions before become useful now. For example: metrics concerning competitors. Therefore, metrics provided by Croll & Yoskovitz are on now also focused on the ecosystem.MetricDescriptionNegative ChurnA path to negative churn needs to be in place to recover revenue from loosing through churn, in order to scale a startup.Bottom-line: a startup needs to get 2% of the paying subscribers to increase what they pay each month. Up-sellingWhat makes customers increase their spending, and how often that happens, focused on up-selling: upgrades, maintenance, licensing-deals, etc.Cross-sellingWhat makes customers increase their spending, and how often that happens, focused on cross-selling: extra related useful products, services.Application Programming Interface (API) trafficTraffic in APIs show how your data or services are integrated on the web into other modules or applications. That network effect is important in supporting growth.Ecosystem Channel RelationshipsThe number and effectiveness of ecosystem channel relationships, on for example resellers selling your product for you, is an important factor to enable a network effect and therefore supports growth. CompetitorsThe number of relevant competitors now becomes important, since from this phase on it is signalled to others you do sell the right product in the right market.Support CostsSupport costs in order to be able to serve your existing customers in doing maintenance, becomes a relevant metric plianceThe ability to deliver what is promised, or, are you in control as a software supplier. Can be reported quarterly for example.Market ExpansionEntering new markets. Could be the ones already existing, or creating the market where it does not exist yet.Sales ForceTotal number of FTEs of the new sales people supporting growth (scaling-up) at most of the above metrics Table SEQ Table \* ARABIC 7 - SaaS startup metrics – Scale (Croll & Yoskovitz, 2013; Skok, 2013)ConclusionThis part has clarified the insights in what happens in each stage of a startup, aiming at metrics to support increasing the understanding of startup performance for both entrepreneurs as investors. A clear development shown through metrics can be seen from the first stage, Discovery, focused on interviews, to Validation, merely focused on testing the MVP, to Efficiency, which metrics show preparation for Scale to avoid pre-mature scaling, and in the end Scale, which focuses more on fast growth and the ecosystem. The following chapters will first describe what systems are currently used to track what happens in the startup stages, followed by data concerning startup stakeholders considerations on relevant startup evaluation factors or metrics, closed by a chapter where it all will be concluded in a framework functioning as a metrics base, making the theoretical defined metrics applicable. Performance Measurement Systems Performance Measurement System GoalsTo perform business performance measurement, a system to perform that task is necessary. That business performance measurement system functions as a management system (management system is a term for all kind of management assisting systems, like business performance measurement systems). What are the internal organizational benefits of implementing those business performance systems as management systems? Antonio Davila, George Foster and Ning Jia (2010) did research on ways of building sustainable high-growth startup companies. They prove that at a certain point in time, the so-called ‘entrepreneurial crisis’, where 50-100 employees are involved, organization management has to transform from ‘personal’ to ‘professional’. In this increasing so-called ‘professional’ management, management systems play a critical role (Davila et al., 2010). As 3.5.2. describes, VCs are able to bring that professionalization to early-stage startups, resulting in the increasing adoption of information systems.Little background on the purpose of a information system, will be provided first. Besides internal organizational information, information systems also can provide information on the external world of customers, suppliers, etc. The Hawley committee (Hawley, 1995) defined several information groupings, like market and customer information, business process information, etc. According to Chaffey and Wood (2004, p.14), these groupings can be used by information systems to:Research demand for new products – customers in different markets can be surveyed for their needs for products. Exchange information with partners such as suppliers as part of their operational municate messages about brands and products externally.Monitor and control operating processes for efficiency and improve them to save time or money.Sense what is happening in the external environment and respond accordingly through their strategy and tactics. For example, it can monitor competitor activity such as the introduction of new products or the winning of new contracts.Davila and Foster (2005) found out that financial planning systems are the earliest set of systems adopted. However, as the startup lifecycle and the corresponding metrics have shown in the previous chapters, traditional financial planning systems should not be the earliest set of systems, since they are not sufficient in managing the product and market focused performance information in the early-stage. This is related to the paradigm shift currently happening, from Financial focus to Innovation focus, as is described in 3.6.2. Therefore it might be useful to clarify definitions on such (traditional) management systems first, where Management Accounting Systems (MAS), focused on the financial aspects of a company, can be defined as a subset of Management Control Systems (MCS) (Davila & Foster, 2005).The advantage Davila and Foster (2005) found is the positive association between the adoption of management control systems and startup growth. Related is the CEOs position, where adopting fewer information systems result in shorter tenures for CEOs. Therefore, the execution of business performance measurement, in the industry also known as business performance management (BPM), needs a management (control) system, taking all different company stages into consideration. A detailed definition on performance measurement system and related goals and methods is provided by Franco-Santos et al. (2007, p.9): “A performance measurement system enables informed decisions to be made and actions to be taken because it quantifies the efficiency and effectiveness of past actions through the acquisition, collation, sorting, analysis, interpretation, and dissemination of appropriate data.” Useful requirements for such a system are provided by Stair, Reynolds and Chesney (2008, p.239), describing seven characteristics of Executive Support Systems (ESS): Tailored to individual executivesAre easy to useHave drill-down abilitiesSupport the need for external dataCan help with situations that have a high degree of uncertainty Have a future orientationAre linked with value-added business processesState of the ArtAs discussed in chapter 3.6. on general and stage-dependent metrics, this research uses the four Startup Genome-stages. This section will elaborate on the available tools designed to reach the associated milestones P/S Fit, P/M Fit, and Growth as quick as possible, taking into consideration it needs to fit early-stage startups. Not only do the tools fulfil requirements on early-stage fit, the performance information in the tool needs to be available to external viewers (i.e. stakeholders) too. All of them are online available. The state-of-the-art consists of mainly three tools (or frameworks), developed by leaders within the lean startup movement, to guide a startup through their early-stages process (Maurya, 2012; Ries, 2011): First the Lean Canvas (Maurya, 2012), second the Validation Board (Lean Startup Machine, 2012) and third the Lean Dashboard (Maurya, 2013). A fourth tool looked very useful, but since they are releasing at the moment this research is done, no evaluation can be done yet.Lean CanvasThe Lean Canvas, depicted in figure 17, is designed by Maurya (2012), as an adoption from the Business Model Canvas, to primarily enable entrepreneurs to clearly capture that what is most uncertain and most risky in a startup, for both the product and market side of a startup. The sequence a startup defines the Lean Canvas is as follows: (1) Problem (2) Customer Segments, (3) Unique Value Proposition (UVP), (4) Solution, (6) Channels, (6) Revenue Streams, (7) Cost Structure, (8) Key Metrics, and (9) Unfair Advantage (Maurya, 2012).Some of the concepts will be highlighted here. Keeping the Solution box small compared to the Problem box corresponds to the concept of a MVP instead of a detailed solution and the importance of focusing on the problem a startup wants to solve. Key metrics are important concerning defining a few key actions (or key macro metrics) that matter, in order to be able to focus. Unfair Advantage is also known as competitive advantage, whereas Maurya (2012) notes that few startups have a true Unfair Advantage from day one. The UVP is different than the Problem: the UVP is the marketing promise of combining the problem and solution.The model can be used in different stages of a startup, Maurya (2012) argues, where the risks documented evolve over the lifecycle of a startup. Fig. SEQ Fig. \* ARABIC 19 – The Lean Canvas (Maurya, 2012)Validation BoardThe Validation Board, or Experimentation Board, is used to document the testing of hypotheses, i.e. documenting the validation process of experiments. It provides a structured overview, focused on the main Lean Canvas parts, Customer, Problem and Solution, thereby driving the entrepreneurs’ behaviour towards ‘getting out of the building’ and talking to potential customers, to validate the hypotheses (i.e. assumptions). The process is done step by step through the Pivots at the upper half, to be able to test the assumptions in an iterative way.Fig. SEQ Fig. \* ARABIC 20 – Validation Board (Lean Startup Machine, 2012)Lean Dashboard.The Lean Dashboard, also developed by Maurya (2013), is like the Validation Board designed to do experimentations in a structured manner, however this tool is combined with the Customer Factory. The Customer Factory is described in 3.6.3.3. when discussing metrics concerning P/S Fit. The dashboard is shown in figure 19, an example filled in for a SaaS startup in the P/M Fit phase. The process starts on the upper level by defining how many customers are needed to reach the Scale target, from which P/M Fit is a smaller version, and P/S Fit an even smaller version. A Scale target of 2000 customers is a customer production rate is derived from the key metric of $10M ARR, where the revenue stream is $200 MRR, with a customer LTV of 2 years, which means the need for approximately 2000 new customers/year. The experiments show the validation of the different experiments, which are time-bound since the entrepreneur can appoint an end-date to each objective and experiment. The metrics show the numbers and conversion of the leads, users, customers, and referrals (new leads). The completed experiments show the validated or invalidated experiments. Fig. SEQ Fig. \* ARABIC 21 – Lean Dashboard (Maurya, 2013)The three online tools as described in this section support a part of the Lean Startup methods in their own way, based on best practices, whereas two of them are developed by a startup thought leader (Maurya). However, since they only support a part of the process, they cannot be considered as solutions feasible to all the stages, in particular concerning SPIM and its related metrics implementation.-1143000Summary To improve startup (or ‘business’) performance, performance measurement is necessary. Therefore Startup Performance Information Management (SPIM) is introduced in this chapter. First performance measurement is defined, bringing Information Management and Business Performance Management together. Subsequently the main goals and advantages of performance measurement are described.Important is the paradigm shift from a (traditional) Financial approach towards an (non-traditional) Innovation approach, which has consequences on the information stakeholders are communicating through SPIM.The information concerning SPIM mainly is about defining metrics. Both general and stage-dependent metrics are described, to provide more insights to startups and their stakeholders, in order to bring the traditional stakeholders and non-traditional startups together. To support SPIM, performance measurement systems are required. Different goals of these systems are provided, among others: helping a startup in its transition towards a professional company. Financial planning systems are the earliest set of systems adopted, however this is contradictory what lean methods prescribe (notice the Financial-to-Innovation Paradigm shift). Three different systems (i.e. online tools) are described, to provide insights in the state of the art concerning tools supporting the Lean approach. Although they are useful, they do not sufficiently provide required functionalities to support SPIM.00Summary To improve startup (or ‘business’) performance, performance measurement is necessary. Therefore Startup Performance Information Management (SPIM) is introduced in this chapter. First performance measurement is defined, bringing Information Management and Business Performance Management together. Subsequently the main goals and advantages of performance measurement are described.Important is the paradigm shift from a (traditional) Financial approach towards an (non-traditional) Innovation approach, which has consequences on the information stakeholders are communicating through SPIM.The information concerning SPIM mainly is about defining metrics. Both general and stage-dependent metrics are described, to provide more insights to startups and their stakeholders, in order to bring the traditional stakeholders and non-traditional startups together. To support SPIM, performance measurement systems are required. Different goals of these systems are provided, among others: helping a startup in its transition towards a professional company. Financial planning systems are the earliest set of systems adopted, however this is contradictory what lean methods prescribe (notice the Financial-to-Innovation Paradigm shift). Three different systems (i.e. online tools) are described, to provide insights in the state of the art concerning tools supporting the Lean approach. Although they are useful, they do not sufficiently provide required functionalities to support SPIM.DataNow the underlying theory as discussed in the previous chapter will be used in this chapter, to support the results: the interview data and the framework. This chapter will firstly describe the interview data: the descriptions of data collection, data processing and analysis method, followed by the data. Secondly, the framework based upon the theory and interview results will be presented.Qualitative MethodsData CollectionAs described in chapter 2, qualitative data is gathered through interviews, in order to build a grounded theory on the topic of SPIM within a startup ecosystem. The interview protocols are attached to this research in the appendices, specified for the different stakeholder groups: Appendix B on Building Programs (Incubators/Accelerators/Venture Builders) and Appendix C on Investors (Business Angels/Venture Capitalists).The interviews are semi-structured, i.e. consisting of both specific questions aiming at short answers as well as open questions aiming at unexpected responses, which tend to be more highly interactive and provide the ability to the researcher to clarify questions (Singer, Sim & Lethbridge, 2008). However, interviews are time and cost consuming, concerning scheduling, attending the meeting, and transcribing and coding the audio recordings (Singer et al., 2008). This resulted in a much longer period of time invested in this specific part of the research than anticipated in planning the research milestones. Data QualityFirst some elaboration on which stakeholders participated, and how the selection process is done. Four different categories of stakeholders are included: one consists of experts in the startup field and three consist of ecosystem stakeholders. The experts will be used as a starting point of the research, exploring which scope would be appropriate, which stakeholders needs to be considered as relevant, etc. The goal concerning ecosystem stakeholders is to enhance existing startup and stakeholder theories, by bringing new insights to the field of research.To optimally serve the research, several criteria need to be met. The experts need to have experience in doing research towards large populations of startups over multiple years. The criteria used for the ecosystem stakeholders obviously are different. There must be at least one set of building organizations (incubators, accelerators or venture builders), which have a track-record in building multiple startups over multiple years. Also needed is one set of Business Angels and one set of Venture Capitalists, who both can show a proven track-record, i.e. have invested in multiple startups over multiple years, including investing in at least one SaaS startup. As the theory discussed, Business Angels belong to a group of considerable heterogeneous wealthy individuals. In order to be able to draw conclusions on such a wide group of individuals, formal founded Business Angel networks will be used to gather data from.These criteria are needed in order to be able to justify usage of the data, through guaranteeing quality of that data. The right quantity of the data in order to be useful to include in the research is subjective, either little field notes while doing an interview, or an explorative unstructured interview will not be considered as useful. Table 7 below, shows the descriptive data on the quantitative data gathered through the interviews, including three data sources which are excluded after analysing the data, based on the quantitative criteria mentioned above. Stakeholder TypeCompanyInterviewee OccupationInvestment size (euros)Company Age (years)Interview time (min)Building Program IncubatorINC 1Head Europe Relations21.000 (GBP)< 10 35INC 2Incubation ManagerN.a.> 10 60INC 3CoachN.a.< 10 40INC 4Business AnalystN.a.N.a.30Investor BA (matching)BA 1Partner200K - 1M> 10 25BA 2Director50K - 2.5M< 10 55BA 3DirectorUnknown< 10 55Investor VC (seed - growth)VC 1Investment Manager100K – 500KUnknown75VC 2Managing Partner100K – 500KUnknown60VC 3Investment Manager2.5M - 10M< 10 40VC 4Director1M- 5M< 10 60ExpertExpert 1Scientific DirectorN.a.N.a.35Expert 2Business AnalystN.a.N.a.40Performance Tool CompanyToolBusiness AnalystN.a.< 10 80Table SEQ Table \* ARABIC 8 – Descriptive data (including excluded sets)Data Analysis MethodThe qualitative interview results are transcribed and coded, in order to be able to formulate a grounded theory, based on analysis and conceptualization of the coded data. Some interview recordings are transcribed using Microsoft Word and VLC media player, and some by using the qualitative research tool NVIVO. The coding of those transcripts is based on both selective coding (pre-formed codes), in line with the structure of the interviews, which are tied to the concepts used in the research questions, as well as coding open to the context and conditions of the interview (post-formed codes) to support the emergent nature of grounded theory. The level of coding is detailed, on a sentence level, since the number of participants is small and still to be able to get most out of the data. The analysis and conceptualization is done through practices derived from literature on information systems qualitative research methods: cross-case analysis of data slices, in order to compare the different stakeholders within similar and between the different groups (stakeholder types functioning as cases), to build the theory (Urquhart, Lehmann & Myers, 2010). DataConcepts OverviewBefore diving into the detailed results, an overview of the used codes (i.e. nodes or topics) will be provided. This is included prior to the data belonging to these particular codes, to provide a preview on the topics and corresponding structure as emerged and used in the interview data. The nodes of the data set are shown in table 8, consisting of nodes and sub-nodes, for the stakeholders, the experts, descriptive data on the framework, and general tips, hints and references received during the interviews. Building Programs?Business Angels?Venture CapitalistsStakeholder focus?Stakeholder focus?Stakeholder FocusStartup Sectors ?Startup Sectors?Startup Sectors?Startup Stages??Startup Stages??Startup StagesBuilding Methods?Engagement?EngagementInvestor Involvement?Governance (Board/MT/Coach)?Governance (Board/MT/Coach)Program Reporting??BA Knowledge??VC Knowledge?Establishing Relationship?Establishing Relationship?Formal Agreements ?Formal Agreements ????Exit Strategy??Exit StrategySPIM?SPIM?SPIMSPIM before ?SPIM before?SPIM beforeAssessment Information?Assessment Method?Assessment MethodSPIM afterAssessment InformationAssessment InformationReporting FormatTeamSPIM afterReporting FrequencyProduct + MarketReporting FormatReporting RequestFunding SizeReporting FrequencyInformation SPIM afterInformationInterventionReporting FormatInformation Asymmetry?Reporting Frequency?Intervention?Information??Information Asymmetry??Intervention??BA (network) Assessment?Experts?Framework?Tips/Hints/ReferencesResearch Focus?General?Stakeholders?Choosing Stakeholders?Startup Population?Startup Type?Research goals??Building Methods??Coaching??Evaluation Criteria??Table SEQ Table \* ARABIC 9 – Interview Data StructureTwo main topics are Stakeholder (or Research) Focus and SPIM. The first main topic, Stakeholder (or Research) Focus, aims at the type and maturity of startups a stakeholder or expert is involved in. The second main topic, SPIM, obviously is about the performance information management, both after and before a stakeholder-startup relationship starts. The other topics are stakeholder-specific topics. For building programs, those are the Building Methods, Investor Involvement and Program Reporting. For investors the Engagement and Establishing a Relationship are important. For Business Angels in particular, Usage BA Funding and BA (network) Assessment are two very specific topics emerged in the data. What interview data belongs to the different code groupings will be discussed in the next section. Interview DataThis section will elaborate on the data, by describing what qualitative data is collected, in a structured way of conceptualization. The first part of the interview data will be on the three primary startup stakeholders (Building Programs, BAs, VCs), using the distinctive character of ‘main topics’ (Stakeholder Focus and SPIM) and ‘stakeholder-specific topics’ as a structure. The second part will consist of a short description on the remaining groupings (Experts, Framework and Tips/Hints/References). Although this section conceptualizes the raw data, it still is a lot of data. Therefore the subsequent section (4.2.3.) will summarize the most important part, the stakeholder part (including some references to the remaining groupings). 0457200Stakeholder Focus Startup StagesIt seems incubators are quite broad and unspecified in their startup stages application demands, as INC 2 describes. People do enter their incubator in every possible stage, from idea to functioning product. This seems to be different for INC 4, stating they support startups in early early-stage stage, where experiments are key, founding the basis for a company, and where no funding is needed yet. However, INC 2 also describes startups leaving the program when receiving significant funding.Startup SectorsNo data available. SPIM beforeAssessment InformationOnly INC 2 mentions something on assessing the applicants (with their value propositions, i.e. ideas/business models) who wants to apply for their programme. Fit and Viability are the two measures, respectively assessing the fit of the value proposition to the building program and the viability of the value proposition in the market. The assessment is performed by a committee, on which INC 2 explicitly notes that less focus is on the applying team compared to other building programs, since this could result in a bad Fit, resulting in declining a potentially great value proposition.SPIM afterReporting FormatSearching for a feasible reporting format in incubators seems to be different for both incubators. Tangible tools acting as reporting tools are the Experimentation (i.e. Validation) Board, Lean Canvas, Business Model Canvas, or Microsoft Powerpoint presentation formats. Intangible is the information transfer through conversations in meetings. These are two ways to communicate implicit and explicit performance information. In line with the previous topic on request for information, the dilemma on reporting will be elaborated here at the level of the information format. INC 2 tells that coaches monitor performance through tools (Experimentation Board and Lean Canvas) and conversations, although they currently are mainly focused on tracking performance through the00Stakeholder Focus Startup StagesIt seems incubators are quite broad and unspecified in their startup stages application demands, as INC 2 describes. People do enter their incubator in every possible stage, from idea to functioning product. This seems to be different for INC 4, stating they support startups in early early-stage stage, where experiments are key, founding the basis for a company, and where no funding is needed yet. However, INC 2 also describes startups leaving the program when receiving significant funding.Startup SectorsNo data available. SPIM beforeAssessment InformationOnly INC 2 mentions something on assessing the applicants (with their value propositions, i.e. ideas/business models) who wants to apply for their programme. Fit and Viability are the two measures, respectively assessing the fit of the value proposition to the building program and the viability of the value proposition in the market. The assessment is performed by a committee, on which INC 2 explicitly notes that less focus is on the applying team compared to other building programs, since this could result in a bad Fit, resulting in declining a potentially great value proposition.SPIM afterReporting FormatSearching for a feasible reporting format in incubators seems to be different for both incubators. Tangible tools acting as reporting tools are the Experimentation (i.e. Validation) Board, Lean Canvas, Business Model Canvas, or Microsoft Powerpoint presentation formats. Intangible is the information transfer through conversations in meetings. These are two ways to communicate implicit and explicit performance information. In line with the previous topic on request for information, the dilemma on reporting will be elaborated here at the level of the information format. INC 2 tells that coaches monitor performance through tools (Experimentation Board and Lean Canvas) and conversations, although they currently are mainly focused on tracking performance through theStakeholder 1 - Building Programs [Incubators]30861004800600“That progress is the most important thing there is”“That progress is the most important thing there is”1143004800600 “I want to open that box: which phase are we in?” “I want to open that box: which phase are we in?”0-18415conversations. INC 4 tells tools and conversations are key as well. Reporting FrequencyBoth incubators have a reporting frequency of once in two weeks, where a startup has to report on agreements they commit on, agreements they make together when sitting together in these bi-weekly meetings with the incubator. Reporting RequestAt the one hand, incubators do not believe requesting for reports to communicate performance information is suitable, at the other hand they are able to tell why monitoring the performance is both important and necessary. INC 4 tells the importance lies in the fact that an incubator needs to collect data aligned to the goals a startup wants to reach, because an incubator can assist in the process of starting a company, however the entrepreneurs mainly will execute the process by rmation Which information is needed to be able to monitor the performance of a startup has its similarities and differences for both incubators. Both incubators agree on the importance as well as the challenge of tracking startup performance.The information for both incubators consists mainly of information concerning the business model and experimentation results. The business model information consists of data as described by components of the Lean Canvas (or quite similar, the Business Model Canvas). Experimentation results through the Experimentation (i.e. Validation) Board, guiding the testing of hypotheses, considered as very important by INC 2. Both information topics are forced to be communicated on their characterising meta-level, since both incubators consider the early-stage of a startup difficult to define metrics on. However, some metrics are discussed:Both incubators mention customer data, although INC 2 explicitly mentions traction as an example metric, the metric that expresses product demand. INC 2 warns that using the speed of doing experimentations does not seem to be a good metric for a performance indication, because that speed depends on the startup context too much. They suggest benchmarking is more reliable, for example an average no. of pivots leading to success. INC 4 mentions 00conversations. INC 4 tells tools and conversations are key as well. Reporting FrequencyBoth incubators have a reporting frequency of once in two weeks, where a startup has to report on agreements they commit on, agreements they make together when sitting together in these bi-weekly meetings with the incubator. Reporting RequestAt the one hand, incubators do not believe requesting for reports to communicate performance information is suitable, at the other hand they are able to tell why monitoring the performance is both important and necessary. INC 4 tells the importance lies in the fact that an incubator needs to collect data aligned to the goals a startup wants to reach, because an incubator can assist in the process of starting a company, however the entrepreneurs mainly will execute the process by rmation Which information is needed to be able to monitor the performance of a startup has its similarities and differences for both incubators. Both incubators agree on the importance as well as the challenge of tracking startup performance.The information for both incubators consists mainly of information concerning the business model and experimentation results. The business model information consists of data as described by components of the Lean Canvas (or quite similar, the Business Model Canvas). Experimentation results through the Experimentation (i.e. Validation) Board, guiding the testing of hypotheses, considered as very important by INC 2. Both information topics are forced to be communicated on their characterising meta-level, since both incubators consider the early-stage of a startup difficult to define metrics on. However, some metrics are discussed:Both incubators mention customer data, although INC 2 explicitly mentions traction as an example metric, the metric that expresses product demand. INC 2 warns that using the speed of doing experimentations does not seem to be a good metric for a performance indication, because that speed depends on the startup context too much. They suggest benchmarking is more reliable, for example an average no. of pivots leading to success. INC 4 mentions 1486535876935“The more concrete the data, the easier it is to say: “okay, you are doing well” or “you are not doing well yet””.00“The more concrete the data, the easier it is to say: “okay, you are doing well” or “you are not doing well yet””.00measuring startup data on Team, Customer, Product and Finances. The Pirate metrics, AAARR, are considered as useful by both of them, where INC 2 notes that these metrics are useful in the case of IT startups.Both incubators emphasize using milestones is useful to track progress, by applying milestones such as Problem/Solution fit and Product/Market fit. They state that performance information on these milestones communicated through conversations is considered as feasible and valuable for the stages their startups are in.Team evaluation is something INC 4 considers as the startup teams’ own responsibility to take care of, something to leave its course. However, an incubator might better be able to look what is missing in a team (in the context of functions), how the intercourse between team members is, and what is captured in contracts.InterventionTaking action based upon the performance information is the last part of SPIM. INC 2 mentions the importance on 1-on-1 coaching, where much intervention can take place. If entrepreneurs get stuck into specific elements, they can be forwarded to a coach. Even a workshop does exist on personal development. INC 4 uses the bi-weekly meetings to manage the startup progress, by providing feedback on that progress.00measuring startup data on Team, Customer, Product and Finances. The Pirate metrics, AAARR, are considered as useful by both of them, where INC 2 notes that these metrics are useful in the case of IT startups.Both incubators emphasize using milestones is useful to track progress, by applying milestones such as Problem/Solution fit and Product/Market fit. They state that performance information on these milestones communicated through conversations is considered as feasible and valuable for the stages their startups are in.Team evaluation is something INC 4 considers as the startup teams’ own responsibility to take care of, something to leave its course. However, an incubator might better be able to look what is missing in a team (in the context of functions), how the intercourse between team members is, and what is captured in contracts.InterventionTaking action based upon the performance information is the last part of SPIM. INC 2 mentions the importance on 1-on-1 coaching, where much intervention can take place. If entrepreneurs get stuck into specific elements, they can be forwarded to a coach. Even a workshop does exist on personal development. INC 4 uses the bi-weekly meetings to manage the startup progress, by providing feedback on that progress.13716003886200“In the beginning, every founder thinks he needs an investor. Instead, you need to know and focus on the current most urgent/important problem.”“00“In the beginning, every founder thinks he needs an investor. Instead, you need to know and focus on the current most urgent/important problem.”“00Stakeholder-specific Building MethodsBoth incubators emphasize on using the best practices from the Lean Startup method, combined with the Lean Canvas or similar Business Model Canvas (see Reporting Format), and the Experimentation (i.e. Validation) Board, where focus and iterations are mentioned by INC 4 as the major advantages. Both incubators use Running Lean as a method to focus on the right stage.Investor InvolvementInvestors are not involved in the early stages an incubator startup is in, and may not distract the entrepreneurs in their focus as well: entrepreneurs always think funding is needed. Therefore startups receiving funding are not in the program of INC 4, but go to pursue their growth in other environments. INC 2 does have startups that receive funding by angels and funds, although startups entering the growth stage leave their program as well.Program ReportingBoth incubators are connected to knowledge centres (universities and universities of applied sciences). The main performance measures they need to report on are Revenue and Full Time Equivalent (FTE).00Stakeholder-specific Building MethodsBoth incubators emphasize on using the best practices from the Lean Startup method, combined with the Lean Canvas or similar Business Model Canvas (see Reporting Format), and the Experimentation (i.e. Validation) Board, where focus and iterations are mentioned by INC 4 as the major advantages. Both incubators use Running Lean as a method to focus on the right stage.Investor InvolvementInvestors are not involved in the early stages an incubator startup is in, and may not distract the entrepreneurs in their focus as well: entrepreneurs always think funding is needed. Therefore startups receiving funding are not in the program of INC 4, but go to pursue their growth in other environments. INC 2 does have startups that receive funding by angels and funds, although startups entering the growth stage leave their program as well.Program ReportingBoth incubators are connected to knowledge centres (universities and universities of applied sciences). The main performance measures they need to report on are Revenue and Full Time Equivalent (FTE).Stakeholder 2 - Investors [Business Angels] 4572007279640“We do screening (..) on three main factors (..) de Vent de Tent en de Cent” (i.e. respectively: the Entrepreneur, the Company, and the Penny (funding size))00“We do screening (..) on three main factors (..) de Vent de Tent en de Cent” (i.e. respectively: the Entrepreneur, the Company, and the Penny (funding size))Stakeholder Focus Startup StagesBusiness Angels invest in the early-stages, although no exact answer exists: from vague idea to detailed business plans. It is mostly seed capital, until later rounds, where they dilute or being bought-out.Startup SectorsBA 1 focuses mostly on Business-to-Business (80% of portfolio) software and high-tech companies. BA 2 mentions specialisation as a trend in informal investing, 60% of BAs tend to invest in familiar sectors. When a sector is unfamiliar, which is 40% of the cases, there might be a known sufficient societal relevance, where knowledge is added in a following syndicate investment with a new expert lead-investor. BA 3 refers to every type of startup, matching these with BAs or Management Buy-inners. SPIM beforeAssessment MethodBA 1 shortly mentions the template developed together with an external party, to assess the management team. BA 2 and 3 provide more detailed insights on the process of how BAs are being matched with startups. The first contact is via phone or email, after which the application is sent via email. Than the matching starts, where a first sketch of the business is needed, followed by meeting the suitable BA, which requires a more detailed business plan, where the BA chooses whether he wants to participate or not (mainly an emotional decision). If the BA wants to participate, they end up with a term-sheet, where the participation starts. Assessment InformationThis section will elaborate on the information a BA requires in order to evaluate a startup, divided into three parts: Team, Product + Market, and Funding Size. Stakeholder Focus Startup StagesBusiness Angels invest in the early-stages, although no exact answer exists: from vague idea to detailed business plans. It is mostly seed capital, until later rounds, where they dilute or being bought-out.Startup SectorsBA 1 focuses mostly on Business-to-Business (80% of portfolio) software and high-tech companies. BA 2 mentions specialisation as a trend in informal investing, 60% of BAs tend to invest in familiar sectors. When a sector is unfamiliar, which is 40% of the cases, there might be a known sufficient societal relevance, where knowledge is added in a following syndicate investment with a new expert lead-investor. BA 3 refers to every type of startup, matching these with BAs or Management Buy-inners. SPIM beforeAssessment MethodBA 1 shortly mentions the template developed together with an external party, to assess the management team. BA 2 and 3 provide more detailed insights on the process of how BAs are being matched with startups. The first contact is via phone or email, after which the application is sent via email. Than the matching starts, where a first sketch of the business is needed, followed by meeting the suitable BA, which requires a more detailed business plan, where the BA chooses whether he wants to participate or not (mainly an emotional decision). If the BA wants to participate, they end up with a term-sheet, where the participation starts. Assessment InformationThis section will elaborate on the information a BA requires in order to evaluate a startup, divided into three parts: Team, Product + Market, and Funding Size. 16002002057400“The best team comes up with the best proposition. In that particular order.”00“The best team comes up with the best proposition. In that particular order.” 00TeamMore detailed is their information on how they evaluate a startup. All three BAs mention the entrepreneur (or management team/founders/team) as the most important factor. The teams’ power to execute, flexibility, qualities (and being aware of it), and completeness determine the feeling BA 1 has about a team. Although they have a template for assessing the team, they mention judging whether a person seems to be entrepreneurial is a tough process, since it is hard to define a good entrepreneur.BA 2 states that the best team brings the best proposition in (not counting exceptions), proven by parts like strategy, patents, market approach; comparing it to the Holy Grail. However, a team can be influenced and improved along the way, or completed through BA knowledge.BA 3 has de Vent (i.e. the Guy) as the first evaluation factor, on which he says, screening is highly subjective, and therefore states that BA decisions are fully based on an emotional (i.e. personal) connection. BA 3 values extravert above introvert, although introverts might have more product knowledge, extraverts are better being able to sell themselves. That is required for getting exposure by pitching, and showing his performance.Product + MarketEstimating a startup market size depends on the product or service being offered: in traditional (or old) economies it is easier, due to existing players on an existing market, whereas online (or new) economies raise more difficulties. Detailed market assessment and descriptions are not required by BAs, however it is a nice-to-have to be able to show there is research in a particular target market. An estimation of potential customers is sufficient.Funding SizeBA 3 explicitly mentions the size of required funding (de Cent, i.e. the Penny) as a third evaluation factor. If a startup seeks funding for an amount more than 250.000 euros, it will be hard to find a BA willing to participate, since the majority of early-stage companies only have an idea, business sketch or business plan. 00TeamMore detailed is their information on how they evaluate a startup. All three BAs mention the entrepreneur (or management team/founders/team) as the most important factor. The teams’ power to execute, flexibility, qualities (and being aware of it), and completeness determine the feeling BA 1 has about a team. Although they have a template for assessing the team, they mention judging whether a person seems to be entrepreneurial is a tough process, since it is hard to define a good entrepreneur.BA 2 states that the best team brings the best proposition in (not counting exceptions), proven by parts like strategy, patents, market approach; comparing it to the Holy Grail. However, a team can be influenced and improved along the way, or completed through BA knowledge.BA 3 has de Vent (i.e. the Guy) as the first evaluation factor, on which he says, screening is highly subjective, and therefore states that BA decisions are fully based on an emotional (i.e. personal) connection. BA 3 values extravert above introvert, although introverts might have more product knowledge, extraverts are better being able to sell themselves. That is required for getting exposure by pitching, and showing his performance.Product + MarketEstimating a startup market size depends on the product or service being offered: in traditional (or old) economies it is easier, due to existing players on an existing market, whereas online (or new) economies raise more difficulties. Detailed market assessment and descriptions are not required by BAs, however it is a nice-to-have to be able to show there is research in a particular target market. An estimation of potential customers is sufficient.Funding SizeBA 3 explicitly mentions the size of required funding (de Cent, i.e. the Penny) as a third evaluation factor. If a startup seeks funding for an amount more than 250.000 euros, it will be hard to find a BA willing to participate, since the majority of early-stage companies only have an idea, business sketch or business plan. 2857500-2493010“Angels want to see proof (..) to see whether claims on market, product, technology, strategy, are true ”00“Angels want to see proof (..) to see whether claims on market, product, technology, strategy, are true ”00SPIM afterReporting Format and FrequencyBA 1 is quite formal, where once a quarter a written report on management issues, organization, finances, strategy execution and technology, is required. Finances consist of the profit and loss statement, the balance sheet and cash flow forecast. Eventually several KPIs they agreed on, are included, to be able to steer on. BA 2 states that most BAs have there own approach, although in general they need a bi-weekly or monthly financial overview. Overall, the approach is characterized by direct involvement to be able to add value, and therefore directly informing a BA on a regular basis (monthly or quarterly, depending on the BA or participation). Perhaps frequency corresponds to the BA experience and the right investment decisions, both requiring less coaching. InformationThe Business Angels mainly talked about assessing the risk factors for their investment. However, since information on SPIM after the investment is required too, some findings are derived from the data. BA 1 does have experience in SaaS investing, where monthly revenue and the number of users is considered as important. Therefore it needs to be scalable to as much users as possible. Another important measure for quality is number of wishes (mostly complaints) from customers, resulting in customer-driven updates. The other measure should be Crunch, the number of customers leaving, where research is needed on the reasons why those customers are leaving and why newer versions should be considered. BA 2 focuses more on the high-level, mentioning BAs wants to see proof on claims made about product, technology, strategy, etc.; possibly learned through the crisis some years ago. This results in a possibly increasing formal approach of BAs in the rmation AsymmetryInformation asymmetry, i.e. startup information not known by investors, does not need to be considered as a problem for investors, as BA 3 says. Imagine a few guys working on a product, where a BA participates. He probably knows for 80% as much as the others do, which might be on management and operations, where that 20% has to do with specific technological knowledge, which might be the component he does not have experience to deal with.00SPIM afterReporting Format and FrequencyBA 1 is quite formal, where once a quarter a written report on management issues, organization, finances, strategy execution and technology, is required. Finances consist of the profit and loss statement, the balance sheet and cash flow forecast. Eventually several KPIs they agreed on, are included, to be able to steer on. BA 2 states that most BAs have there own approach, although in general they need a bi-weekly or monthly financial overview. Overall, the approach is characterized by direct involvement to be able to add value, and therefore directly informing a BA on a regular basis (monthly or quarterly, depending on the BA or participation). Perhaps frequency corresponds to the BA experience and the right investment decisions, both requiring less coaching. InformationThe Business Angels mainly talked about assessing the risk factors for their investment. However, since information on SPIM after the investment is required too, some findings are derived from the data. BA 1 does have experience in SaaS investing, where monthly revenue and the number of users is considered as important. Therefore it needs to be scalable to as much users as possible. Another important measure for quality is number of wishes (mostly complaints) from customers, resulting in customer-driven updates. The other measure should be Crunch, the number of customers leaving, where research is needed on the reasons why those customers are leaving and why newer versions should be considered. BA 2 focuses more on the high-level, mentioning BAs wants to see proof on claims made about product, technology, strategy, etc.; possibly learned through the crisis some years ago. This results in a possibly increasing formal approach of BAs in the rmation AsymmetryInformation asymmetry, i.e. startup information not known by investors, does not need to be considered as a problem for investors, as BA 3 says. Imagine a few guys working on a product, where a BA participates. He probably knows for 80% as much as the others do, which might be on management and operations, where that 20% has to do with specific technological knowledge, which might be the component he does not have experience to deal with.2171700-7407910“Some wants to be there once a month, on a Friday afternoon (..) or people saying (..) I want to do it three days a week. And everything in between ”00“Some wants to be there once a month, on a Friday afternoon (..) or people saying (..) I want to do it three days a week. And everything in between ”00InterventionIf a startup turns out to perform really bad or the trust in its management team decreases, BA 1 considers if the issue can be solved, by for example replacing the management team. Otherwise he declines further participation. Stakeholder-specific EngagementEngagement will be about the level of engagement of a BA in a company, on the levels of governance and knowledge ernance (Board/Management Team/Coach)It might be the case that BA 1 participates at the financial level, to translate the numbers to somewhat more storytelling, however they obviously prefer a person in that position who is able to execute that task. Management team is not the goal, adding value is, which is what all three BAs agree on: it’s a part-time participation, driven by passion and experiences originating from their own entrepreneurial career. However, mostly there is something missing in the early phase, which can be temporarily done by the investor. BAs often belong to a network, where knowledge is easily accessible, so it might be the case one of them is able to fulfil a position in the board. Fulfilling a board position when being investor is tricky, which means acting as shareholder and supervisor at the same time. KnowledgeAs mentioned, passion and experience originating form their own past drives BAs to invest and participate. Therefore, BAs vary in actively participating from once a month talking about the numbers to participating for multiple days a week in a specific part of the company. BA 2 mentions research showing that added value of BAs through their knowledge and experience increases the success probability for both the BA and the startup.BA Network AssessmentTo assess whether BAs themselves are able to provide the quality they claim to have, BA 2 assesses BAs as well, before letting BAs in their network are able to meet certain startups. The assessment is based on the BAs’ participation in startup activities and the feedback they receive from entrepreneurs.00InterventionIf a startup turns out to perform really bad or the trust in its management team decreases, BA 1 considers if the issue can be solved, by for example replacing the management team. Otherwise he declines further participation. Stakeholder-specific EngagementEngagement will be about the level of engagement of a BA in a company, on the levels of governance and knowledge ernance (Board/Management Team/Coach)It might be the case that BA 1 participates at the financial level, to translate the numbers to somewhat more storytelling, however they obviously prefer a person in that position who is able to execute that task. Management team is not the goal, adding value is, which is what all three BAs agree on: it’s a part-time participation, driven by passion and experiences originating from their own entrepreneurial career. However, mostly there is something missing in the early phase, which can be temporarily done by the investor. BAs often belong to a network, where knowledge is easily accessible, so it might be the case one of them is able to fulfil a position in the board. Fulfilling a board position when being investor is tricky, which means acting as shareholder and supervisor at the same time. KnowledgeAs mentioned, passion and experience originating form their own past drives BAs to invest and participate. Therefore, BAs vary in actively participating from once a month talking about the numbers to participating for multiple days a week in a specific part of the company. BA 2 mentions research showing that added value of BAs through their knowledge and experience increases the success probability for both the BA and the startup.BA Network AssessmentTo assess whether BAs themselves are able to provide the quality they claim to have, BA 2 assesses BAs as well, before letting BAs in their network are able to meet certain startups. The assessment is based on the BAs’ participation in startup activities and the feedback they receive from entrepreneurs.-114300455930Stakeholder Focus Startup StagesThe stages in which VC participation starts varies per VC from seed to early stage, however definitions on these stages also do vary as data shows. VC 1 invests in Early-stage startups, mentioning the moment market-fit is reached, where a startup has revenue, but does not require being profitable yet, and therefore accept higher risk. In majority of the cases they invest once, however sometimes twice or more times, from a certain investment level only in cooperation with consortium. VC 2 invests earlier, from the moment where a sound business plan, preferably a minimum viable product, can be provided. The two other VCs participate later in the startup lifecycle. VC 3 participates after Seed, mostly before a Series B (thus, series A). They consider Series B when possible together with other VCs. A product and some customers are required. VC 4 does some Seed, calling it pre-revenue, but mostly Series A.Startup SectorsAlso the sectors differ amongst the four VCs, although all of them have experience in SaaS investing. VC 1 does medical technology (calling it med-tech) and SaaS. They prefer SaaS as being a majority proportion of their portfolio in the future. VC 2 invests purely invests in software companies, which is mainly SaaS. VC 3 has a broader portfolio focus: advertising, e-commerce, medium-market technology, mobile, enterprise services, education technology, and financial technology. VC 4 is also mainly active in the Netherlands. They prefer one sector, although they say they need to go broader, even on an international scale. Interviewee recently involved in first SaaS startup, has therefore put a lot of effort into gaining knowledge of SaaS in particular.SPIM beforeAssessment MethodCritical counterweight is core of the way VC 1 assesses business plans they receive, by checking it at other market players or from own experience. In the due diligence process they check everything. VC 2 provides more detailed insights in the process, saying new business plans come in by phone or email, or through candidates from theme events and training sessions they organized. After applying the criteria (as will be described in Assessment Information) they do research through a checklist, as due-diligence, including customers, partners, and employees in that process, to assess if there is knowledge and experience00Stakeholder Focus Startup StagesThe stages in which VC participation starts varies per VC from seed to early stage, however definitions on these stages also do vary as data shows. VC 1 invests in Early-stage startups, mentioning the moment market-fit is reached, where a startup has revenue, but does not require being profitable yet, and therefore accept higher risk. In majority of the cases they invest once, however sometimes twice or more times, from a certain investment level only in cooperation with consortium. VC 2 invests earlier, from the moment where a sound business plan, preferably a minimum viable product, can be provided. The two other VCs participate later in the startup lifecycle. VC 3 participates after Seed, mostly before a Series B (thus, series A). They consider Series B when possible together with other VCs. A product and some customers are required. VC 4 does some Seed, calling it pre-revenue, but mostly Series A.Startup SectorsAlso the sectors differ amongst the four VCs, although all of them have experience in SaaS investing. VC 1 does medical technology (calling it med-tech) and SaaS. They prefer SaaS as being a majority proportion of their portfolio in the future. VC 2 invests purely invests in software companies, which is mainly SaaS. VC 3 has a broader portfolio focus: advertising, e-commerce, medium-market technology, mobile, enterprise services, education technology, and financial technology. VC 4 is also mainly active in the Netherlands. They prefer one sector, although they say they need to go broader, even on an international scale. Interviewee recently involved in first SaaS startup, has therefore put a lot of effort into gaining knowledge of SaaS in particular.SPIM beforeAssessment MethodCritical counterweight is core of the way VC 1 assesses business plans they receive, by checking it at other market players or from own experience. In the due diligence process they check everything. VC 2 provides more detailed insights in the process, saying new business plans come in by phone or email, or through candidates from theme events and training sessions they organized. After applying the criteria (as will be described in Assessment Information) they do research through a checklist, as due-diligence, including customers, partners, and employees in that process, to assess if there is knowledge and experienceStakeholder 3 - Investors [Venture Capitalists]1028700-2541905“(..) any well performing VC wants to talk to customers, and people who dropped out ”00“(..) any well performing VC wants to talk to customers, and people who dropped out ”00available to enable startup growth. If passed the test, the investment committee does the calculations (the committee consists of financial people and representatives of the most important stakeholders of the fund), which thereafter is reported to the ‘Raad van Commissarissen’ (i.e. supervisory board). As VC 3 says, a lot of opportunities for funding seekers to get in contact with the VC do exist. From personal meetings, corporate finance advisors advising startups, congresses, conferences, accelerator-programmes, coincidences, et cetera. The VC searches for potential startups and vice versa. They invest in either sectors they have knowledge about, or new ones, by putting a lot of effort in it to gain new knowledge. After someone in the VC team has seen a potential startup, it will be discussed in the team, to choose whether it will be interesting or not. If that is the case, the financial plan, subsequent questions and portfolio fit will be discussed, where after a term-sheet can be offered to the startup. After the offer is accepted, short due-diligence takes place on finances and technology, after which finally the investment takes place. VC 4 has a comparable process as VC 3, both for the parts as for the period it takes. The whole process is on average approximately three to six months, which is normal for Europe, although VCs in the US has on average shorter assessment periods VC 4 states. The long period is due to the need to review the activities of a startup long before the investment will be made, for example checking whether a startup reaches his milestones in time. The VC need for such a long period of time can increase pressure for startups searching for money, which is why VC 4 states that startups need to be aware of the time it takes, in order to avoid seeking funding under high pressure. 95% does not reach their business plan targets, where maybe 5% does reach it, from which 2% does better than the goals stated.Talking with customers (current and past ones) and other companies, even competitors, is for both VCs another important method to evaluate the startup. Both value personal meetings above assessing quantitative data, however VC 4 mentions they are continuously talking about how they can apply such a quantitative approach. Also an extra component VC 4 mentioned is the use of lawyers and auditors to do the bookkeeping research and making the contracts. VC 4 continuously talks with building programs, although their daily deal-flow does not come from those programs. It is hard to see the startups’ reality through the slick presentations.00available to enable startup growth. If passed the test, the investment committee does the calculations (the committee consists of financial people and representatives of the most important stakeholders of the fund), which thereafter is reported to the ‘Raad van Commissarissen’ (i.e. supervisory board). As VC 3 says, a lot of opportunities for funding seekers to get in contact with the VC do exist. From personal meetings, corporate finance advisors advising startups, congresses, conferences, accelerator-programmes, coincidences, et cetera. The VC searches for potential startups and vice versa. They invest in either sectors they have knowledge about, or new ones, by putting a lot of effort in it to gain new knowledge. After someone in the VC team has seen a potential startup, it will be discussed in the team, to choose whether it will be interesting or not. If that is the case, the financial plan, subsequent questions and portfolio fit will be discussed, where after a term-sheet can be offered to the startup. After the offer is accepted, short due-diligence takes place on finances and technology, after which finally the investment takes place. VC 4 has a comparable process as VC 3, both for the parts as for the period it takes. The whole process is on average approximately three to six months, which is normal for Europe, although VCs in the US has on average shorter assessment periods VC 4 states. The long period is due to the need to review the activities of a startup long before the investment will be made, for example checking whether a startup reaches his milestones in time. The VC need for such a long period of time can increase pressure for startups searching for money, which is why VC 4 states that startups need to be aware of the time it takes, in order to avoid seeking funding under high pressure. 95% does not reach their business plan targets, where maybe 5% does reach it, from which 2% does better than the goals stated.Talking with customers (current and past ones) and other companies, even competitors, is for both VCs another important method to evaluate the startup. Both value personal meetings above assessing quantitative data, however VC 4 mentions they are continuously talking about how they can apply such a quantitative approach. Also an extra component VC 4 mentioned is the use of lawyers and auditors to do the bookkeeping research and making the contracts. VC 4 continuously talks with building programs, although their daily deal-flow does not come from those programs. It is hard to see the startups’ reality through the slick presentations.1371600-4467860“First, is it a good entrepreneur. Second, is it a distinctive product or service. Third, is the documentation structured and correct”00“First, is it a good entrepreneur. Second, is it a distinctive product or service. Third, is the documentation structured and correct”029845Assessment InformationConcerning business plans VC 1 and VC 2 have quite similar opinions: most of the business plans are just sales stories, packages of paper, where market analysis is not right, no customers interaction is done, et cetera. Sometimes clear on target market, sometimes not clear.VC 1 creates an estimation of the risk-profile when considering investing in medical devices, which aligns to the amount of funding (high risk, much testing needed, cost and time consuming process). Well-defined milestones and a roadmap to growth are required. SaaS has the advantage of being able to calculate/prove market potential. Traction in the market is key. They do the market check by themselves (especially concerning healthcare), and when not possessing the appropriate knowledge external partners in their network will be used. Quantification of customer demand is overestimating the present data. Focus more on the question if someone is willing to pay, like the good strategy of launching customers in SaaS. There needs to be a certain validation. An entrepreneur is valued as a good entrepreneur when he is the one being on the streets, talking to people, and making as much deals as possible. VC 1 does not prioritize evaluation criteria (team, product, market) since they are too heavily interrelated to each other. VC 2 is clear on their evaluation criteria. Three are mentioned: first, a good entrepreneur, second a distinctive product or service, and third, is the documentation (for example: business-plan) structured and correct. The entrepreneur needs to overcome three hurdles, being able to: develop a minimum product, make a transition from a technological approach to a more commercial approach, and organizing (attracting and managing external partners). The business plan needs to consist of the proof of product/service necessity in the market, the problem formulated is well and clear and it contains knowledge about the market and other companies, i.e. what are chances for success compared to others. The later executed due diligence is on customers, partners, employees, knowledge and experience (see Assessment Method). Three criteria are mentioned by VC 3 as well, however slightly different. Also here comes the entrepreneurial team first (perseverance, complementarity, and the feeling a team evokes). The second is the product, including the need for some paying customers. The third factor is the geographical location (the Netherlands or Germany). As the assessment method described, the due diligence is on finances and technology, and something on numbers and team. 00Assessment InformationConcerning business plans VC 1 and VC 2 have quite similar opinions: most of the business plans are just sales stories, packages of paper, where market analysis is not right, no customers interaction is done, et cetera. Sometimes clear on target market, sometimes not clear.VC 1 creates an estimation of the risk-profile when considering investing in medical devices, which aligns to the amount of funding (high risk, much testing needed, cost and time consuming process). Well-defined milestones and a roadmap to growth are required. SaaS has the advantage of being able to calculate/prove market potential. Traction in the market is key. They do the market check by themselves (especially concerning healthcare), and when not possessing the appropriate knowledge external partners in their network will be used. Quantification of customer demand is overestimating the present data. Focus more on the question if someone is willing to pay, like the good strategy of launching customers in SaaS. There needs to be a certain validation. An entrepreneur is valued as a good entrepreneur when he is the one being on the streets, talking to people, and making as much deals as possible. VC 1 does not prioritize evaluation criteria (team, product, market) since they are too heavily interrelated to each other. VC 2 is clear on their evaluation criteria. Three are mentioned: first, a good entrepreneur, second a distinctive product or service, and third, is the documentation (for example: business-plan) structured and correct. The entrepreneur needs to overcome three hurdles, being able to: develop a minimum product, make a transition from a technological approach to a more commercial approach, and organizing (attracting and managing external partners). The business plan needs to consist of the proof of product/service necessity in the market, the problem formulated is well and clear and it contains knowledge about the market and other companies, i.e. what are chances for success compared to others. The later executed due diligence is on customers, partners, employees, knowledge and experience (see Assessment Method). Three criteria are mentioned by VC 3 as well, however slightly different. Also here comes the entrepreneurial team first (perseverance, complementarity, and the feeling a team evokes). The second is the product, including the need for some paying customers. The third factor is the geographical location (the Netherlands or Germany). As the assessment method described, the due diligence is on finances and technology, and something on numbers and team. 1371600-4192905“The advantage of SaaS is the necessity to measure on a month-to-month basis”00“The advantage of SaaS is the necessity to measure on a month-to-month basis”00Information problem VC 4 talks about is concerning the large proportion of optimism, ambition, and sometimes a complete lack of reality view. The most important factor for VC 4 is just like the other ones, the entrepreneurs (preferably multiple, forming a team). VC 4 even states that team is the biggest risk factor for all the different startup stages. Frequently something goes wrong in the team, examples are quarrel, less hard working, exhausted, quitting, not having the qualities they though they have, et cetera. They need to be coachable, since participating as a VC means at 5-7 years of cooperation and for entrepreneurs it is an emotional project. Balanced previous experience (specialisations) of the entrepreneurs is important too. The other evaluation factors are on the market, product and investors. For example, the global relevancy and size of the market, where emerging markets are a challenge. Also on the product: distinctive product, quality of the features, and scalability. The fit of the investment and type of investment is assessed, as well as the quality of the currently participating investors.Do not underestimate the qualitative part of the information, although they are continuously thinking and talking about whether it is valuable to use more quantification of information. Books do not say much in early stages, however expense management can be signalling. However, startups are increasingly measuring things, compared to a couple of years ago, thus more data is available. The advantage of SaaS is the necessity to measure on a monthly basis: monthly recurring development, metrics driven MVP testing, Customer Acquisition Cost (CAC). Only leap of faith is on churn in early stage. Therefore they talk to customers, competitors and churned customers. Sales conversion important: what is the number of companies that need to be approached in order to make a deal. VC 4 puts the SaaS metrics in a database and reviews it regularly. For example: growth rate, decreasing after it started with high growth. And the CAC, Customer Lifetime Value (CLTV), and the CTLV:CAC ratio. Are those ratios higher/on average/in the danger zone compared to the market and other SaaS companies? Traction is required to be available too (could be users, blog posts, downloads, etc.). 00Information problem VC 4 talks about is concerning the large proportion of optimism, ambition, and sometimes a complete lack of reality view. The most important factor for VC 4 is just like the other ones, the entrepreneurs (preferably multiple, forming a team). VC 4 even states that team is the biggest risk factor for all the different startup stages. Frequently something goes wrong in the team, examples are quarrel, less hard working, exhausted, quitting, not having the qualities they though they have, et cetera. They need to be coachable, since participating as a VC means at 5-7 years of cooperation and for entrepreneurs it is an emotional project. Balanced previous experience (specialisations) of the entrepreneurs is important too. The other evaluation factors are on the market, product and investors. For example, the global relevancy and size of the market, where emerging markets are a challenge. Also on the product: distinctive product, quality of the features, and scalability. The fit of the investment and type of investment is assessed, as well as the quality of the currently participating investors.Do not underestimate the qualitative part of the information, although they are continuously thinking and talking about whether it is valuable to use more quantification of information. Books do not say much in early stages, however expense management can be signalling. However, startups are increasingly measuring things, compared to a couple of years ago, thus more data is available. The advantage of SaaS is the necessity to measure on a monthly basis: monthly recurring development, metrics driven MVP testing, Customer Acquisition Cost (CAC). Only leap of faith is on churn in early stage. Therefore they talk to customers, competitors and churned customers. Sales conversion important: what is the number of companies that need to be approached in order to make a deal. VC 4 puts the SaaS metrics in a database and reviews it regularly. For example: growth rate, decreasing after it started with high growth. And the CAC, Customer Lifetime Value (CLTV), and the CTLV:CAC ratio. Are those ratios higher/on average/in the danger zone compared to the market and other SaaS companies? Traction is required to be available too (could be users, blog posts, downloads, etc.). 1371600-5236210“larger portfolios require a more high-level information demand (..) financially-driven”00“larger portfolios require a more high-level information demand (..) financially-driven”4229100-5221605“You cannot trust Sales people”00“You cannot trust Sales people”00Reporting Format and FrequencyFormats and frequency are quite similar for all VCs. VCs requires monthly (financial) and quarterly (management) reports. VC 3 mentions reports in every format in the range of simple Excel spreadsheets to data exported from CRM systems. There do exist tools in the market, but no large systems are necessary, although it also does not matter if you want to do it in Excel, like VC 3 does. VC 4 talks about agreeing on a reporting cycle and dashboard beforehand, during establishing the relationship, where it for example happened that the VC received a Tableau log in, to be able to check KPIs on a daily basis. However, normally they agree on getting performance information on a weekly rmationThe information reported frequently after the investment is made is slightly described above, by format and frequency, and assessment information of course also covers some similar information. Still specific performance information after the investment is made needs to be communicated. The reports VC 1 talked about, is the monthly financial data, which consist for example of information on profit and loss statements. VC 3 mentions that larger portfolios require only a higher level of financials, where only something on number of users of a product could be an additional part; it becomes mainly financially driven performance information. The quarterly management information is about the funnel, with a progress report to get more insight on the point a startup is at. A demand for new funding also requires a new performance information demand. Checking progress through milestones is an important component, where to much optimism resulting in not reaching milestones is a good lesson.The other VCs are more specific about the SaaS market and product performance information. Licences are key in those business models, consisting of a maintenance contract, consultancy, and project management for larger projects. Maintenance cannot be the main stream of revenue, and selling products without maintenance means customers do not use the product. Sales is hard to monitor, sales people cannot be trusted. Conversion funnel to order portfolio is important. The other challenge is on the Product monitoring: development, testing and implementing, combined with the ability to deliver. Tailored software is a big risk. On the Finance side it is needed to monitor the expense management and the books, where mainly the debtors says a lot (invoices v.s. revenue). All that information provided on a quarterly basis provides valuable insights in SaaS startup development.00Reporting Format and FrequencyFormats and frequency are quite similar for all VCs. VCs requires monthly (financial) and quarterly (management) reports. VC 3 mentions reports in every format in the range of simple Excel spreadsheets to data exported from CRM systems. There do exist tools in the market, but no large systems are necessary, although it also does not matter if you want to do it in Excel, like VC 3 does. VC 4 talks about agreeing on a reporting cycle and dashboard beforehand, during establishing the relationship, where it for example happened that the VC received a Tableau log in, to be able to check KPIs on a daily basis. However, normally they agree on getting performance information on a weekly rmationThe information reported frequently after the investment is made is slightly described above, by format and frequency, and assessment information of course also covers some similar information. Still specific performance information after the investment is made needs to be communicated. The reports VC 1 talked about, is the monthly financial data, which consist for example of information on profit and loss statements. VC 3 mentions that larger portfolios require only a higher level of financials, where only something on number of users of a product could be an additional part; it becomes mainly financially driven performance information. The quarterly management information is about the funnel, with a progress report to get more insight on the point a startup is at. A demand for new funding also requires a new performance information demand. Checking progress through milestones is an important component, where to much optimism resulting in not reaching milestones is a good lesson.The other VCs are more specific about the SaaS market and product performance information. Licences are key in those business models, consisting of a maintenance contract, consultancy, and project management for larger projects. Maintenance cannot be the main stream of revenue, and selling products without maintenance means customers do not use the product. Sales is hard to monitor, sales people cannot be trusted. Conversion funnel to order portfolio is important. The other challenge is on the Product monitoring: development, testing and implementing, combined with the ability to deliver. Tailored software is a big risk. On the Finance side it is needed to monitor the expense management and the books, where mainly the debtors says a lot (invoices v.s. revenue). All that information provided on a quarterly basis provides valuable insights in SaaS startup development.457200-4235450“CEO knows the most about the company (..) we hope to receive that information (..) in general I think that is the case (..) although it happens (..) you can not get the information tabled you want to have tabled”00“CEO knows the most about the company (..) we hope to receive that information (..) in general I think that is the case (..) although it happens (..) you can not get the information tabled you want to have tabled”00VC 3 thinks more quantification of performance information only plays a role in the bigger and more mature VCs, for example by monitoring departments through activity-based costing. And the more mature a startup gets, the more the hands-on approach of an investor can decrease. Concerning the quantification over the lifecycle, VC 4 says that even the Efficiency stage probably contains a lot of wishful thinking, where just from the Scale stage more data becomes available. VCs focusing on quantifying performance information do exist, using frameworks to rate progress more easily, in order to get the emotional part out of it.Just like VC 4 stating the Team in general is the biggest risk factor in all stages, VC 2 states a stubborn team as a big risk. Information AsymmetryThe asymmetry in performance information management does not seem to be a real issue. VC 3 talks about the same interest for both the entrepreneur as the investor, which is pursuing company growth, resulting in a trust relationship concerning company information. It is an entrepreneurs’ task to manage the right information for the right stakeholders. However, even for a CEO it might be a challenge to get the right information on company processes, for example information behind activity-based costing, therefore an investor always need to avoid assuming everything is all right in the company.VC 4 is quite clear on asymmetry of information, stating they do not want to see the same information the management team sees, due to the fact that amount of information is just too much.InterventionVC 1 mostly includes in their agreements they need to agree with on the yearly budget, therefore once a year able to control. If things change during the year, for example legislation, they come together with the stakeholders and make a new plan. Steering on variables like revenue and costs is possible too. In deliberation with the shareholders for example a director can be fired if not functioning well. Advancing insights can be useful, however VC 2 states that it is important to stick to milestones set before, and try to get to the problems behind it. Sometimes extra funding will do the trick. However this could decrease the founders’ motivation due to dilution. They only pull the plug when it really is not going to work out well, although searching for a acquisition company first, might be more interesting.00VC 3 thinks more quantification of performance information only plays a role in the bigger and more mature VCs, for example by monitoring departments through activity-based costing. And the more mature a startup gets, the more the hands-on approach of an investor can decrease. Concerning the quantification over the lifecycle, VC 4 says that even the Efficiency stage probably contains a lot of wishful thinking, where just from the Scale stage more data becomes available. VCs focusing on quantifying performance information do exist, using frameworks to rate progress more easily, in order to get the emotional part out of it.Just like VC 4 stating the Team in general is the biggest risk factor in all stages, VC 2 states a stubborn team as a big risk. Information AsymmetryThe asymmetry in performance information management does not seem to be a real issue. VC 3 talks about the same interest for both the entrepreneur as the investor, which is pursuing company growth, resulting in a trust relationship concerning company information. It is an entrepreneurs’ task to manage the right information for the right stakeholders. However, even for a CEO it might be a challenge to get the right information on company processes, for example information behind activity-based costing, therefore an investor always need to avoid assuming everything is all right in the company.VC 4 is quite clear on asymmetry of information, stating they do not want to see the same information the management team sees, due to the fact that amount of information is just too much.InterventionVC 1 mostly includes in their agreements they need to agree with on the yearly budget, therefore once a year able to control. If things change during the year, for example legislation, they come together with the stakeholders and make a new plan. Steering on variables like revenue and costs is possible too. In deliberation with the shareholders for example a director can be fired if not functioning well. Advancing insights can be useful, however VC 2 states that it is important to stick to milestones set before, and try to get to the problems behind it. Sometimes extra funding will do the trick. However this could decrease the founders’ motivation due to dilution. They only pull the plug when it really is not going to work out well, although searching for a acquisition company first, might be more interesting.1371600-5693410“basically you capture in your participation contract what position and communication you want of a company. Do you for example want to provide a commissioner, or maybe a chairman of an RVC.”00“basically you capture in your participation contract what position and communication you want of a company. Do you for example want to provide a commissioner, or maybe a chairman of an RVC.”00Pushing the limits is possible; however, enforcing this is not possible. And who are you as an investor to enforce a hard-working entrepreneur to give more, being realistic is key.VC 3 gives the example of the death of a CEO, for them it was the obvious reason to participate actively in the company to work towards a solution together. Although, they are in the position to avoid overreacting to negative information, due to the (relatively) large size of their portfolio; mistakes are calculated beforehand. A shareholder and/or participant in the supervisory board always is responsible to act upon bad startup performance. This can be observed through 3 scenarios VC 4 found out. One, they reach their targets, maybe some extra funding can be helpful, everyone is satisfied. Two, it goes much better than the goals set; therefore, more funding is needed. Or three, the startup performance goes down, and therefore the probability to pull the plug out, to stop the participation, increases.Stakeholder-specific EngagementThe first stakeholder-specific topic will be (like the BA part) on investor engagement, where governance and knowledge sharing describes VC involvement in a ernance (Management Team/Board /Coach)Management team participation is not a feasible activity concerning the workload, therefore not scalable, however VC 4 mentions some VCs fulfil such roles. Board positions are part of a more realistic scenario. Two types of boards do exist. The Anglo-Saxon type consists of a board of directors and supervisors in one board, i.e. a one-tier board. The more European type is the two-tier board, where the board of directors (executive board) is separated from the supervisory board (in Dutch: ‘Raad van Commissarissen)(non-executive board). The one-tier board provides a closer look at the information within a startup, due to their equal rights for both directors as supervisors. However, for all four VCs the (two-tier type) supervisory board is part of the participation, which is due to the lower level of direct reliability when things go wrong internally in a startup, compared to a one-tier board position. The supervisory board both does advice (as a sounding board) and decision-making (about for example employee bonuses), and its positions do not necessarily need to be fulfilled by shareholders. The supervisory board, in case of VC 3, meets once in six weeks. Although such a supervisory board seems to be convenient, startups do not always have such a governance structure in place, for example in case of a few shareholders a board is not necessary, where just a shareholder meeting is sufficient. 00Pushing the limits is possible; however, enforcing this is not possible. And who are you as an investor to enforce a hard-working entrepreneur to give more, being realistic is key.VC 3 gives the example of the death of a CEO, for them it was the obvious reason to participate actively in the company to work towards a solution together. Although, they are in the position to avoid overreacting to negative information, due to the (relatively) large size of their portfolio; mistakes are calculated beforehand. A shareholder and/or participant in the supervisory board always is responsible to act upon bad startup performance. This can be observed through 3 scenarios VC 4 found out. One, they reach their targets, maybe some extra funding can be helpful, everyone is satisfied. Two, it goes much better than the goals set; therefore, more funding is needed. Or three, the startup performance goes down, and therefore the probability to pull the plug out, to stop the participation, increases.Stakeholder-specific EngagementThe first stakeholder-specific topic will be (like the BA part) on investor engagement, where governance and knowledge sharing describes VC involvement in a ernance (Management Team/Board /Coach)Management team participation is not a feasible activity concerning the workload, therefore not scalable, however VC 4 mentions some VCs fulfil such roles. Board positions are part of a more realistic scenario. Two types of boards do exist. The Anglo-Saxon type consists of a board of directors and supervisors in one board, i.e. a one-tier board. The more European type is the two-tier board, where the board of directors (executive board) is separated from the supervisory board (in Dutch: ‘Raad van Commissarissen)(non-executive board). The one-tier board provides a closer look at the information within a startup, due to their equal rights for both directors as supervisors. However, for all four VCs the (two-tier type) supervisory board is part of the participation, which is due to the lower level of direct reliability when things go wrong internally in a startup, compared to a one-tier board position. The supervisory board both does advice (as a sounding board) and decision-making (about for example employee bonuses), and its positions do not necessarily need to be fulfilled by shareholders. The supervisory board, in case of VC 3, meets once in six weeks. Although such a supervisory board seems to be convenient, startups do not always have such a governance structure in place, for example in case of a few shareholders a board is not necessary, where just a shareholder meeting is sufficient. 800100-3293110“in our contracts we basically capture contractual agreements concerning information provision. In our case (..) each month financial reporting, once a quarter management reporting”00“in our contracts we basically capture contractual agreements concerning information provision. In our case (..) each month financial reporting, once a quarter management reporting”00KnowledgeVC 1 mentions knowledge as mainly useful in the startup (market) assessment phase, where they see mostly as a VC having more specific knowledge of the field compared to the funding seeking startup (for example on healthcare). Establishing RelationshipsThe relationships established when a startup applies for funding until a company exit is made will be described here, both by discussing the formal agreements and the exit strategy.Formal AgreementsContracts are first mainly on the terms of investing (for example positions) and topics like the reporting cycles as described in reporting Format and Frequency (communication). On terms of investing, in a term-sheet, which could be agreements on positions, by providing a person for the supervisory board, or even a chairman of the supervisory board in case of a large percentage of shares. Agreements on such a position include also on the communication, which insights are necessary in order to be able to assess the board of directors, being able to fire a board in case of dysfunction. VC 1 for example mentions the blocking vote, on topics as the director and what that director needs to earn. Especially when they are the only investor, a lot of adhesion is wanted, and possible. Even when together with other shareholders, selling a company could be done if wanted. Those things are all on positioning and power a VC has. However, as VC 4 mentions, the ideal goal is having a term-sheet that is not needed until the exit where the terms concerning distribution of shares needs to be clear. Also VC 3 mentions a 100-day plan, which describes the first steps of improvement in the startup when the investment is done, for example hiring professional people like a new director of marketing. Besides such a short-term plan, the strategy and execution for the long-term is discussed. Multiple milestones is something VC 4 wants to avoid: they prefer somewhat less funding and aiming at one clear point where they have the possibility to measure, than too much money aiming at a longer period of milestones. However, the type of milestones are important, because some targets, like Revenue, can function as perverse incentives by just doing more Sales. Therefore transparent and clearly measurable milestones are more useful. This also has to do with the field of tension investors and entrepreneurs are in, where too much entrepreneurial optimism interplays with the more realistic view of an investor. 00KnowledgeVC 1 mentions knowledge as mainly useful in the startup (market) assessment phase, where they see mostly as a VC having more specific knowledge of the field compared to the funding seeking startup (for example on healthcare). Establishing RelationshipsThe relationships established when a startup applies for funding until a company exit is made will be described here, both by discussing the formal agreements and the exit strategy.Formal AgreementsContracts are first mainly on the terms of investing (for example positions) and topics like the reporting cycles as described in reporting Format and Frequency (communication). On terms of investing, in a term-sheet, which could be agreements on positions, by providing a person for the supervisory board, or even a chairman of the supervisory board in case of a large percentage of shares. Agreements on such a position include also on the communication, which insights are necessary in order to be able to assess the board of directors, being able to fire a board in case of dysfunction. VC 1 for example mentions the blocking vote, on topics as the director and what that director needs to earn. Especially when they are the only investor, a lot of adhesion is wanted, and possible. Even when together with other shareholders, selling a company could be done if wanted. Those things are all on positioning and power a VC has. However, as VC 4 mentions, the ideal goal is having a term-sheet that is not needed until the exit where the terms concerning distribution of shares needs to be clear. Also VC 3 mentions a 100-day plan, which describes the first steps of improvement in the startup when the investment is done, for example hiring professional people like a new director of marketing. Besides such a short-term plan, the strategy and execution for the long-term is discussed. Multiple milestones is something VC 4 wants to avoid: they prefer somewhat less funding and aiming at one clear point where they have the possibility to measure, than too much money aiming at a longer period of milestones. However, the type of milestones are important, because some targets, like Revenue, can function as perverse incentives by just doing more Sales. Therefore transparent and clearly measurable milestones are more useful. This also has to do with the field of tension investors and entrepreneurs are in, where too much entrepreneurial optimism interplays with the more realistic view of an investor. 00As VC 4 says, careful milestone setting and discussing these with entrepreneurs is key in this process.Exit StrategyVC 2 came up with the exit strategy as a required part of the assessment of a company. The entrepreneurs always need to know, from the beginning, how the exit should look like. This contradicts with the opinion of VC 3, stating that they always are convinced a startup growing well, will encounter a possibility of a sale automatically (i.e. exit). Which is not needed to discuss beforehand together with the startup founders, however they need to be aware of the type of company that could approach them for a sale, in order to have a certain feeling where they need to focus on. Discussing an exit together is odd VC 3 says, especially seen the long period of cooperation they are facing (on average five or six years). A lot unexpected events can and will happen along the way. However it might be obvious the VC internally discusses calculations of profit and loss on an exit, before participating through funding. 00As VC 4 says, careful milestone setting and discussing these with entrepreneurs is key in this process.Exit StrategyVC 2 came up with the exit strategy as a required part of the assessment of a company. The entrepreneurs always need to know, from the beginning, how the exit should look like. This contradicts with the opinion of VC 3, stating that they always are convinced a startup growing well, will encounter a possibility of a sale automatically (i.e. exit). Which is not needed to discuss beforehand together with the startup founders, however they need to be aware of the type of company that could approach them for a sale, in order to have a certain feeling where they need to focus on. Discussing an exit together is odd VC 3 says, especially seen the long period of cooperation they are facing (on average five or six years). A lot unexpected events can and will happen along the way. However it might be obvious the VC internally discusses calculations of profit and loss on an exit, before participating through funding. 1028700-4068445“(..) in this kind of environment, investors are not just financial investors (..) the non-financial investors also needs some kind of information”00“(..) in this kind of environment, investors are not just financial investors (..) the non-financial investors also needs some kind of information”00ExpertsThe expert results provide a short overview of the input they provided, in order to improve this particular research (in terms of components like research focus (scoping), goals, and content on success factors).Research Focus The research focus part will describe both the focus of the experts as well as the directions they advise to choose in this research, in terms of scope.StakeholdersRisk and decision making base upon certain kinds of information in certain stages, needs specific types of stakeholders. A multi-stakeholder environment is necessary, although it would be helpful to classify all of them as investors. Expert 1 classifies investors as stakeholders in two types: financial investors and non-financial investors. The financial do funding, the non-financial provide information (resources, knowledge, expertise, facilities). Expert 2 mentions mainly their own stakeholders, where their research insights are interesting for startups, investors, corporates, and public organizations like the department of Economic Affairs concerning innovation budgets. Startup PopulationIn opposite to this particular research, for both experts only longitudinal studies are relevant. On a more high-level approach they want to derive conclusions on startup behaviour and success. For example Expert 2 did research on a population of 106 startups, over multiple years, in order to have a data set as large as possible, from which conclusions are derived.Research Goals Both experts want to gain insights in startup behaviour and success. Expert 2 for example uses the research for their own understanding of startups as well as in consulting corporates how they can cooperate with startups (i.e. Corporate Innovation). Although results are high-level, several results are that convincing they are confident enough to use it to make their conclusion and statements.00ExpertsThe expert results provide a short overview of the input they provided, in order to improve this particular research (in terms of components like research focus (scoping), goals, and content on success factors).Research Focus The research focus part will describe both the focus of the experts as well as the directions they advise to choose in this research, in terms of scope.StakeholdersRisk and decision making base upon certain kinds of information in certain stages, needs specific types of stakeholders. A multi-stakeholder environment is necessary, although it would be helpful to classify all of them as investors. Expert 1 classifies investors as stakeholders in two types: financial investors and non-financial investors. The financial do funding, the non-financial provide information (resources, knowledge, expertise, facilities). Expert 2 mentions mainly their own stakeholders, where their research insights are interesting for startups, investors, corporates, and public organizations like the department of Economic Affairs concerning innovation budgets. Startup PopulationIn opposite to this particular research, for both experts only longitudinal studies are relevant. On a more high-level approach they want to derive conclusions on startup behaviour and success. For example Expert 2 did research on a population of 106 startups, over multiple years, in order to have a data set as large as possible, from which conclusions are derived.Research Goals Both experts want to gain insights in startup behaviour and success. Expert 2 for example uses the research for their own understanding of startups as well as in consulting corporates how they can cooperate with startups (i.e. Corporate Innovation). Although results are high-level, several results are that convincing they are confident enough to use it to make their conclusion and statements.685800-3705134“(..) part of it is also the whole process of, as they say, picking winners. So how do you evaluate businesses that seem to have the right kind of MT’s, characteristics, service or product offering.”00“(..) part of it is also the whole process of, as they say, picking winners. So how do you evaluate businesses that seem to have the right kind of MT’s, characteristics, service or product offering.”00Building Methods A topic of interest for Expert 1 is the introduction of new business models related to the use of the Lean Startup techniques and their benefits for small business, for example the move away from traditional methods of business planning to the newer methods like the Business Model Canvas. Also how entrepreneurs search for the Engine of Growth in later stages.Coaching Important part of startup growth within a building program or venture builder clearly is coaching: using particular kinds of advice, for example in terms of tools, like startup methods (Expert 1). Building programs take these businesses on board, and when they are worth pursuing, providing them with expertise, coaching, funding, facilities, to manage them through the lifecycle as quickly as they can, and eventually let them go, to develop on their own afterwards. Evaluation CriteriaIn order to be able to assess whether these startups are worth pursuing, organizations like an incubator or venture builder should be able to identify the ideas that are worth pursuing, which is a process of which Expert 1 calls ‘picking winners’: evaluate a business on management team, characteristics, service or product offering, et cetera. The selection is based on criteria as well as on gut feeling. Characteristics Expert 2 mentions are on the following factors: experienced leadership (corporate or entrepreneurial experience), academic experience (finished a bachelor, master, and/or PhD), team of at least two (complementary) founders, and timing (avoiding pre-mature scaling). Quantification of these factors can be done on for example a complementary team, by the elements of experience, like Finance/Marketing/Engineering/Product/etc.Expert 2 says some large accelerators in the Netherlands focus primarily on the team, where they keep in mind a startup can pivot for 180 degrees, where a team still needs to have the capability to continue on that particular startup.00Building Methods A topic of interest for Expert 1 is the introduction of new business models related to the use of the Lean Startup techniques and their benefits for small business, for example the move away from traditional methods of business planning to the newer methods like the Business Model Canvas. Also how entrepreneurs search for the Engine of Growth in later stages.Coaching Important part of startup growth within a building program or venture builder clearly is coaching: using particular kinds of advice, for example in terms of tools, like startup methods (Expert 1). Building programs take these businesses on board, and when they are worth pursuing, providing them with expertise, coaching, funding, facilities, to manage them through the lifecycle as quickly as they can, and eventually let them go, to develop on their own afterwards. Evaluation CriteriaIn order to be able to assess whether these startups are worth pursuing, organizations like an incubator or venture builder should be able to identify the ideas that are worth pursuing, which is a process of which Expert 1 calls ‘picking winners’: evaluate a business on management team, characteristics, service or product offering, et cetera. The selection is based on criteria as well as on gut feeling. Characteristics Expert 2 mentions are on the following factors: experienced leadership (corporate or entrepreneurial experience), academic experience (finished a bachelor, master, and/or PhD), team of at least two (complementary) founders, and timing (avoiding pre-mature scaling). Quantification of these factors can be done on for example a complementary team, by the elements of experience, like Finance/Marketing/Engineering/Product/etc.Expert 2 says some large accelerators in the Netherlands focus primarily on the team, where they keep in mind a startup can pivot for 180 degrees, where a team still needs to have the capability to continue on that particular startup.800100-6150610“(..) academically we want to separate out (..) also in the perfect world (..) we love to make very clear definitions between these stages. But in practice, they are much more fluid.”00“(..) academically we want to separate out (..) also in the perfect world (..) we love to make very clear definitions between these stages. But in practice, they are much more fluid.”00Framework This part will shortly describe the results of all interview comments concerning the framework.GeneralAll interviewees see the advantage, described by Expert 2 as a tool to adjust its information services to. Expert 1 suggests tying the model to factors uncertainty and risk. Stages emerge challenge concerning academically desire to separate out, clear definitions, but in practice much more fluid. Not a unified direction process. Might find some companies where story more complicated than simple linear model. INC 2 thinks it only will be an effective model if it is based and evaluated on a homogeneous niche group (e.g. sector) first, than tested on other groups. Hardly any (or even no) company really is actively searching how startup progress can be measured. Maturity models, like the US Defense tech-model can be helpful. In terms of applicability, MVP is an IT (or SaaS) term, where prototype is the similar term for tech-companies, VC 1 thinks. Solving a pain instead of being a nice-to-have is crucial concerning that MVP, VC 2 says. And, VC 2 argues the stages need to be designed keeping the following stage in mind, to be able to handle growth, whereas startups not able to grow, fail. He also says the validation phase can be considered as the toughest phase, where a startup needs to proceed without the necessary funding. Choosing StakeholdersExpert 2 thinks incubator programs and investors might be the well-positioned stakeholders in the market to gather data from. Where public incubator programs might be more willing to share their findings, on for example success characteristics for startup selection, than the private ones will be. Corporates might be stakeholders to exclude in order to avoid a wide research scope.Formal and informal investors are different concerning participation stage and predictability of their actions. Informals are unpredictable, and willing to handle higher risk since they participate earlier in the startup lifecycle, where startups mostly are funded based on vision instead of data (like user engagement). 00Framework This part will shortly describe the results of all interview comments concerning the framework.GeneralAll interviewees see the advantage, described by Expert 2 as a tool to adjust its information services to. Expert 1 suggests tying the model to factors uncertainty and risk. Stages emerge challenge concerning academically desire to separate out, clear definitions, but in practice much more fluid. Not a unified direction process. Might find some companies where story more complicated than simple linear model. INC 2 thinks it only will be an effective model if it is based and evaluated on a homogeneous niche group (e.g. sector) first, than tested on other groups. Hardly any (or even no) company really is actively searching how startup progress can be measured. Maturity models, like the US Defense tech-model can be helpful. In terms of applicability, MVP is an IT (or SaaS) term, where prototype is the similar term for tech-companies, VC 1 thinks. Solving a pain instead of being a nice-to-have is crucial concerning that MVP, VC 2 says. And, VC 2 argues the stages need to be designed keeping the following stage in mind, to be able to handle growth, whereas startups not able to grow, fail. He also says the validation phase can be considered as the toughest phase, where a startup needs to proceed without the necessary funding. Choosing StakeholdersExpert 2 thinks incubator programs and investors might be the well-positioned stakeholders in the market to gather data from. Where public incubator programs might be more willing to share their findings, on for example success characteristics for startup selection, than the private ones will be. Corporates might be stakeholders to exclude in order to avoid a wide research scope.Formal and informal investors are different concerning participation stage and predictability of their actions. Informals are unpredictable, and willing to handle higher risk since they participate earlier in the startup lifecycle, where startups mostly are funded based on vision instead of data (like user engagement). 1524000According to VC 3 and BA 2 they can be divided into family, friends, which are both the most important source of Dutch SME financing, and BAs. Most formals (for example VCs) act similar, which BA 3 describes as it is demonstrated in the way they pick startups, organize their term-sheets concerning like demands for shares, Return-on-Investment, management fees, evaluation criteria. Which can all be related to a less-emotional decision making process. The stages VCs start their participation in, can be different, for example before or after a startup is cash flow positive, VC 1 and VC 4 state. Or, according to VC 3 and VC 4 describing VCs as Seed, Venture Capital (early/late stage), Private Equity, and Late-stage/Growth.Startup typeINC 4 distinguishes funding for some factors like B2B (focus on sales force) and B2C (focus on marketing) and number of competitors. Principles in those markets are the same, although the timing used and targeted innovation types (technology v.s. business-model) differ. VC 1 argues most IT funding deals are business-to-business related. 00According to VC 3 and BA 2 they can be divided into family, friends, which are both the most important source of Dutch SME financing, and BAs. Most formals (for example VCs) act similar, which BA 3 describes as it is demonstrated in the way they pick startups, organize their term-sheets concerning like demands for shares, Return-on-Investment, management fees, evaluation criteria. Which can all be related to a less-emotional decision making process. The stages VCs start their participation in, can be different, for example before or after a startup is cash flow positive, VC 1 and VC 4 state. Or, according to VC 3 and VC 4 describing VCs as Seed, Venture Capital (early/late stage), Private Equity, and Late-stage/Growth.Startup typeINC 4 distinguishes funding for some factors like B2B (focus on sales force) and B2C (focus on marketing) and number of competitors. Principles in those markets are the same, although the timing used and targeted innovation types (technology v.s. business-model) differ. VC 1 argues most IT funding deals are business-to-business related. 800100-1692910“I think if you really want to look at SaaS, I would recommend you to speak to funds internationally (..) who do it (SaaS) a lot (..) and probably more data driven .”00“I think if you really want to look at SaaS, I would recommend you to speak to funds internationally (..) who do it (SaaS) a lot (..) and probably more data driven .”800100-2721610“(..) not many funds do exist in the Netherlands, if your really look at SaaS (..) [top VC A] wants to do more (..) [top VC B] wants to do more (..) they have not done it yet”00“(..) not many funds do exist in the Netherlands, if your really look at SaaS (..) [top VC A] wants to do more (..) [top VC B] wants to do more (..) they have not done it yet”00Tips/Hints/References Expert 2: US accelerators push statistics about founding team. Two large Dutch accelerators focus on team. Look into crowdfunding-platforms, since they always possess a list of criteria. Dutch platform [X] also does have online reports on that.INC 2: Try to contact Tool Startup [X]. Look into maturity models, like US defense tech-model. BA 1: When talking about tech-companies, try to include how investors cope with technology-component. How to test if it really works and is disruptive as it is claimed.BA 2: Website public organisation SINK provides insights into funding supply to SMEs. Finnish BA Association article publication on SINK website relevant as introduction on angel market. Publications on EBAN and BAE websites.VC 1: Measuring market fit corresponds to Contingency Theory. Informal investor network in the Netherlands more appropriate to do research on than individual BAs, because they closely look and know how deals are made (mentioning examples and contact details).VC 3: Try to get in contact with company [D] for example, to assess how which information flows do exist within the company and towards external parties.VC 4: Little VC funds in the Netherlands on SaaS. You have to approach international funds: VC [E, F, G] and American funds, more knowledge and probably more data-driven. Blogs Chris Dickson, Brad Feld, Christoph Janz. Janz founded VC [E], doing nearly only SaaS, authority on metrics, using those to pick for example in one quarter, from 9000 applicants, 2 or 4 relevant ones. 00Tips/Hints/References Expert 2: US accelerators push statistics about founding team. Two large Dutch accelerators focus on team. Look into crowdfunding-platforms, since they always possess a list of criteria. Dutch platform [X] also does have online reports on that.INC 2: Try to contact Tool Startup [X]. Look into maturity models, like US defense tech-model. BA 1: When talking about tech-companies, try to include how investors cope with technology-component. How to test if it really works and is disruptive as it is claimed.BA 2: Website public organisation SINK provides insights into funding supply to SMEs. Finnish BA Association article publication on SINK website relevant as introduction on angel market. Publications on EBAN and BAE websites.VC 1: Measuring market fit corresponds to Contingency Theory. Informal investor network in the Netherlands more appropriate to do research on than individual BAs, because they closely look and know how deals are made (mentioning examples and contact details).VC 3: Try to get in contact with company [D] for example, to assess how which information flows do exist within the company and towards external parties.VC 4: Little VC funds in the Netherlands on SaaS. You have to approach international funds: VC [E, F, G] and American funds, more knowledge and probably more data-driven. Blogs Chris Dickson, Brad Feld, Christoph Janz. Janz founded VC [E], doing nearly only SaaS, authority on metrics, using those to pick for example in one quarter, from 9000 applicants, 2 or 4 relevant ones. SummaryThis section will consist of a summary of the data presented in the previous section, in order to provide quicker insights in the data.Stakeholder FocusStagesIncubators: early early-stage / early-stage.BAs: seed/early stages. Define scope as: from vague idea to detailed business plans. VCs: seed/early stages/late stage. Define scope as: from detailed business plan to at least market-fit.Stakeholders’ definitions on stages differ, hard to tie them to exact phases.Sectors Incubators unknown.BAs: B2B seems most common. Mostly rely on expertise; however still 40% in unknown sectors. Then syndicate with expert investors is important.VCs: Prefer one sector, however change is needed. Larger VCs broader portfolio. SaaS specialisation seems new for Dutch VCs.SPIM beforeAssessment Method Incubators: unknown.BAs: Tend to focus on the entrepreneur and his business planVCs: Already are monitoring the complete startup for multiple months. BAs: Mainly focusing on meetingsVCs: Execute additional formal steps, like due diligence, checklists, talking to customers and competitors. The focus on assessment parts is different. The way of getting in contact is quite similar for both types of investors. Assessment Information INC 2: applicant screening on Fit & Viability, less focus on Team. Expert 2: Team for large Dutch accelerators most important. BAs: Assess on (prioritized) factors. First feeling on Team, second the Product & Market estimation, and finally on appropriateness of Funding size, which can be objectively assessed. In the end, emotions are key in BA matching. Most VCs: Team is the most important risk/success factor. Can be its perseverance and VCs feeling on it (subjective) or completeness (objective). Product and Market focuses on traction, growth rate, and product metrics, depending on startup stage. BA + VC: both agree on optimistic character of business plans, i.e. sales stories, and state that proof of assumptions is something entrepreneurs need to use to receive funding. Example: VC 4 states that 95% of business plans or not realistic in terms of targets.VC 2 considers open invoices as an important characteristic of a startup. Corresponds to ‘Billings’ in stage-dependent-metrics. In general: assessment factors align with Expert 1, stating both criteria as well as gut feeling are involved. However, Expert 2 emphasises on using criteria through quantitatively assessing team (experience in leadership and academics, team size, team completeness, and timing). SPIM afterFormat & FrequencyIncubators: Consider performance measurement as important and necessary. Lean startup methods are used to communicate information. Formal reports are considered as not suitable, therefore mostly it is done through conversations, in bi-weekly incubator meetings and meetings with coaches. Since progress is key, INC 2 wants to get more insights in the startup process, where quantification is considered as useful. BAs: Different approaches, however in general a bi-weekly, monthly and/or quarterly overview of management issues, financials, etc. are required. The information they need to see is proof on the claims they make and just how the startups are doing.VCs: Require monthly financial reports and quarterly management reports. Could be every format, no standardization is used. Dashboards including KPIs are defined in the official agreements, where larger portfolios may require higher-levels of detail. Milestones are an important part. Reporting InformationBAs: Less data and somewhat abstract on factors and metrics to measure.VCs: Have more clear descriptions on KPIs (i.e. metrics), some which are included in the SPIM framework too. VC 4 believes these KPIs only apply to later stages, where even Efficiency sometimes can be still qualitative. According to what is stated in the assessment information part, the quantitative measurement of the Product & Market might be important, but VC 4 (and partly VC 2) claims Team as being the biggest risk factor for all rmation AsymmetryBAs + VCs: Not considered as a problem, merely a characteristic of the relationship, where startups have detailed process or specific technological knowledge an investor does necessarily benefit by knowing it. VCs: VCs characterized by investing in more mature startups: (1) simply can be too much information to handle as a VC and (2) recognize that even for CEOs it might be a challenge to get the right information. VCs therefore need to have a critical view on information provided. InterventionIncubators: Focuses mainly on the personal level, where meetings are used to monitor progress, and 1-on-1 coaching can be a tool for intervention.BAs: Focuses primarily on the performance of the management team, which can be replaced. VCs: Mention budgets, revenue and costs as variable to obtain startup control. And, since VCs mostly participate in a supervisory board, mostly they are partly responsible for startup performance as well, and therefore are required to take action when that performance gets worse. BAs + VCs: Participate until the moment when it turns out too bad and intervention does not help, then they pull the plug out and further participation stops.InterventionIncubators: unknown.BAs: Primarily want to add value, whereas their experience might be needed to participate (temporarily) in a startup. The group varies in BAs participating multiple days a week in a startup to BAs sharing their experiences and thoughts concerning the startup once a month. VCs: Require more formal positions, like most of them fulfil a supervisory board position (depending on startup maturity), in order to act as a sounding board as well as a decision maker, together with other commissioners (not necessarily shareholders). VCs’ added value concerning knowledge is mainly in the assessment phase, where specific market knowledge is required. Engagement is different for BAs and VCs mainly in terms of informal versus formal. Establishing RelationshipsFormal AgreementsIncubators: unknown.BAs: unknown.VCs: Agreements consist of for example board positions and 100-day plans. Careful milestone setting is key in the process: a revenue number as milestone, for example, is a perverse incentive since revenue can be easily increased through hiring sales people. Exit StrategyIncubators: unknown.BAs: unknown.VCs: Exit strategy is a part VCs differ in opinions. VC 2 believes exit strategy is a required part of the company assessment and agreements, whereas VC 3 believes exit strategy is something to only discuss as a venture capitalist team internally. VC 3 thinks it might be strange to discuss the strategy with the startup while knowing they just started their cooperation for (on average) five or six years, not foreseeing what will happen within these years. Only VC interviews contain data on this topic. This is probably due to two reasons: (1) the formal character of this topic, and (2) incubators and BAs are not participating anymore at the moment a company has its exit. Tips/Hints/ReferencesMost important in this part is the data retrieved from interviewing VC 4, who according to data on SPIM can be considered as most mature in evaluating and monitoring non-traditional startups. VC 4 states little is known in the Dutch ecosystem on SaaS startup investing in particular, compared to foreign investors. SPIM FrameworkAfter describing the theoretical background on SPIM and the interview data focused on SPIM, this chapter will provide the resulting framework on SPIM. The framework, originating from a conceptual model, consists of a two-parts SPIM Framework (stakeholders overview and metric-base) and a practical SPIM Framework Application Model. As is described in the research method description in chapter 2, the framework is build upon two sources: the theoretical background and interview data. Conceptual Model Before the first framework is developed, a conceptual model open to theoretical findings is designed, called the Startup Ecosystem Information Demand Framework (SEIDF). This particular conceptual model is depicted in figure 22. Stakeholder (X)Startup Stage (Y) X1X2…Xn-298450-105800Y1?Y2…YnFig. SEQ Fig. \* ARABIC 22 – Conceptual Model for SEIDFIn order to enable the conceptual model as being a starting point for the search for the final framework, a couple of questions related to the research questions are used: Which Stakeholders are represented by columns {X1, X2, …, Xn }?Which Startup Stages are represented by rows {Y1, Y2, …, Yn }?Which information is demanded by different stakeholders {X} in the different startup stages {Y}, represented by the cells {[X1Y1], [X2Y2], …, [XnYn]},?Optional (related to research time left) are the following questions:What information system (IS) (or IS design) enables optimal use of the SEIDF?Which RISK/ROI-ratios are related to the different startup stages?The FrameworkOriginationThe first theoretical findings led to the first framework, therefore based purely on concepts derived from theory, which is the SEIDF (v. 0.1) (attached to this research in Appendix D). After conducting the interviews, the SEIDF evolved to v. 0.2, v. 0.3, and v. 0.4 (attached to this research in Appendices E, F, and G), to an SPIM framework, consisting of two parts: the first framework part focusing on stakeholders, and the second (main) framework part focusing on startup performance information. Both frameworks are depicted in respectively figure 21 and figure 22 (due to space both added after this chapter).Framework DescriptionFirst remark to make is that the final result differs from the preceding conceptual model and SEIDF frameworks. The main difference is the stakeholders and their specific information demand, in one framework, caused by the changes over time due to interview results. It turned out stakeholders are not specific enough in metrics they are focused on, only the stages they are involved in. Therefore the SEIDF with metrics tied to stakeholders changed to separate stages-stakeholder and stages-metrics framework parts. Still all parts are based on both the theoretical background as well as the interview results,Part 1: SPIM Stakeholder FrameworkThe first framework part is the SPIM Stakeholder Framework, representing which different startup stakeholders are involved in which particular startup stages (table 9). The upper part represents the four Marmer stages representing the main startup-building processes (Discovery, Validation, Efficiency, and Scale), and the corresponding three main milestones a startup wants to reach (the search for Problem/Solution Fit, Product Market Fit and Growth). The factor Time (in months) is based upon findings concerning average time per stage, from the research among startups by Marmer et al. (2011) as 6.2 described. Obviously that number of months mostly can be seen as an impression how long the stages can take instead of being a rigid guide, since those numbers are average numbers. Also part of it is the Startup focus activities part (where reaching milestones also does belong to). The bottom part represents the main part of the framework: which Stakeholders belong to which Startup stages, tied to investment risk percentage per stage, as being discussed in 3.5.2. All components are based on both the theoretical background as well as the interview results.Startup stagesDiscoveryValidationEfficiencyScaleStartup focus actitvities (information)Problem/Solution Fit searchProduct/Market Fit searchGrowthProblem clearFirst channelsSolutionHiringCustomer Segment clearMVP building Revenue stream in placeNegative churn in place?MVP testing Cost structure in placeMarket expanse?Solution definitionImproving Channels???Engine of Growth???Negative Churn roadmap?StakeholdersBuilding OrganizationsIncubatorAcceleratorVenture BuilderInvestorsBusiness Angel(s)Venture Capitalist(s)Investment Risk66,2 %53.0 %33.7 %20.1%Table SEQ Table \* ARABIC 10 – Framework on Startup Stages – Startup Stakeholders 297180010661650011322050 Time7 months11 months17 months25 months Time7 months11 months17 months25 monthsOne extra remark is needed concerning the iterative character of the processes. As is discussed before in this research, pivots for example are common in building a well-performing startup. Therefore, processes are not interpretable that linear as they are visualized. The arrows at the Validation phase visualize the same aspect: it marks the iterative character of MVP building and testing. Part 2: SPIM Metrics Framework (i.e. SPIM Metrics Base)The upper part of the second part, consisting of the startup stages, milestones and focus activities are similar as in the previous Stakeholder Framework. However, since this framework focuses in particular on performance measurement within SPIM, the rows represent the Stage-dependent Metrics and General Metrics, to in the end serve as a SPIM metrics base.The framework can be used first to check where a startup is when checking the activities. Concerning those activities, a startup, startup-building organisation, and external stakeholders are able to do a first evaluation of a startup using the related metrics (i.e. KPIs) to check both how a startup performed in previous periods, both in the short-term (stage-dependent metrics) as well as the long-term (general metrics). Also, the stage-dependent and general metrics can be used to monitor the startup performance for respectively on a short-term basis as well as on a long-term basis, both enabling intervention on the short-term as well as enabling more accurate prediction for the future, in order to be able aligning the building and investing strategy to those results. Startup stagesDiscoveryValidationEfficiencyScaleStartup focus actitvities (information)Problem/Solution Fit searchProduct/Market Fit searchGrowth Problem clear First channels Solution Hiring Customer Segment clear MVP building Revenue stream in place Negative churn in place? MVP testing Cost structure in place Market expanse? Solution definition Improving Channels??? Engine of Growth??? Negative Churn roadmap??MetricsStage-dependent (data)?Customer Survey Statistics (%)Attention (# visitors)Customer Interview Score (0-35)Enrolment (%)Validation Production + Conversion rates (approaches/week -> interviews/week)Customer Lifetime Value (CLV) (€)Revenue (per customer, or MRR, or ARR)Interview Production + Conversion rates (problem interview -> solution interview -> sale)# customers Billings (no)?Stickiness (# users)?User Acquisition Cost (€)Customer Acquisition Cost (CAC) (€)?MVP acceptance score (%)CLV: CAC (ratio)?Churn (users/month)Churn (customers/month)Feature Utilization (%)Uptime & Reliability (%)?Engine of Growth (ratio)Negative churn (ratio)Up-selling (frequency)Cross-selling (frequency)API traffic (%)Ecosystem Relationships (no.)Ecosystem Effectiveness (%)Competitors (no.)Support Costs (€)Compliance (%)New Markets (no.)Sales Force (FTE)102806560325 Time7 months11 months17 months25 months Time7 months11 months17 months25 monthsThe next page will continue on the Framework, where the General Metrics will be discussed.Startup stagesDiscoveryValidationEfficiencyScaleMetrics - general (data)Mgmt. Team Size (no.)Mgmt. Team Experience (corporate/entrepreneurial/none)Mgmt. Team Background (academic degree)Existing Alternatives (no.)Burn Rate (cash/week,-/month)Runway (months)Short-term hiring plans (yes/no)Time-to-break-even (months)Pivots (no.)Learning (metrics quality)Learning (mentor help)Learning (Lean method(s) usage)Funding Raised (€)FTE's (no.)SPIM Framework continued:Table SEQ Table \* ARABIC 11 – Startup Performance Information Management (SPIM) FrameworkFramework ApplicationBefore being able to provide advice on a particular information system aiming at enabling the implementation of all these metrics within a startup ecosystem, or even developing such a system, one necessary phenomenon will be described first: a method to be able to choose out of all these metrics the useful ones, at distinct times and situations, i.e. picking the right metrics. First the goals and reasons of picking those appropriate metrics will be described, followed by an application model to support that particular process.Background Picking the Right MetricsAll those metrics in the previous sections seems to be useful. However, after describing all those metrics for the four different stages, this research will also include more on focus: the main goal is to raise awareness among researchers, entrepreneurs and investors on the importance of picking the right metrics at the right time, instead of using as much metrics (i.e. data) as possible, resulting in the end in the risk of drowning in all that data. Therefore, as Maurya (2012) and other industry experts describe, it is important of knowing which metrics can be considered as actionable metrics and which ones as vanity metrics. Difference is where the actionable metrics’ observed results are tied to specifically and repeatable actions. Vanity stands for the opposite, a metric also defined to observe results, but which is not usable to base actions on.An example of how the lean startup methods can lead to failure will be described first. The lean startup methods have space left for pivots, since is a highly iterative approach (3.2.2.). The risk of such an approach and the characteristics of entrepreneurs may lead to try new things, instead of using a methodical way to eliminate risk (Croll & Yoskovitz, 2013). For example, trying each of the engines of growth to obtain growth, instead of focussing by choosing just one engine of growth and stick to that one (Ries, 2011). Focus is considered by Croll and Yoskovitz (2013) as the key to startup success, therefore they initiated a discipline they call the One Metric That Matters (OMTM), applicable within the lean startup methods. They define it as “the one number you’re completely focused on above everything else for your current stage” (Croll & Yoskovitz, 2013, p.56). It is like choosing out of the most important metrics (Key Performance Indicators) one a startup will focus on. That approach provides guidance in the web of all different metrics for all different business models at different stages.Picking the right OMTM, changing over time, is effective for four different reasons (Croll & Yoskovitz, 2013, p.58):It answers the most important question you have. The entrepreneur needs to identify the riskiest part of the business, and that’s where the most important question lies. When the entrepreneur knows what the right question is, he will know what metric to track in order to answer that question.It forces you to draw a line in the sandAfter the entrepreneur identified the key problem on which he wants to focus, he needs to set goals.It focuses the entire company. Display your OMTM prominently through web dashboards, on TV screens or in regular emails. It inspires a culture of experimentationExperimentation is what all of the lean startup methods encourage. When everyone rallies around the OMTM and is given the opportunity to experiment independently to improve it, it is a powerful force.Four characteristics (i.e. quality criteria) of a good metric are defined by (Croll & Yoskovitz, 2013, p.9-11). A metric must be:Comparative: Being able to compare a metric to other time periods, groups of users, or competitors, helps you understand which way things are moving.Understandable: If people can’t remember it and discuss it, it’s much harder to turn a change in the data into a change in the culture.A ratio or a rate: Ratios or rates tend to be easier to act on, they are inherently?comparative?(see the first characteristic above) and they are good for comparing opposing factors.Changes the way you behave: What will you differently based on changes in the metric?If a startup has chosen its OMTM, what is next? To gain insights in making such a OMTM actionable, Graham (2012) will be used. Graham (2012), founder of Y Combinator, the example accelerator described in 3.5., wrote an essay on startups and growth. He also advocates the importance of startup focus, and therefore describes growth rate as the number every founder always should know. It is the measure of a startup to see if you are doing well or badly. In the Y Combinator accelerator program, growth rate is measured each week. Partly because of the limited time period of the building program, partly because feedback every week can keep startups on the right path in the early-stage. He argues that the primary metric you need to focus on is Revenue, and the secondary best metric is the number of active users when a startup is not charging money initially (Y Combinator guides startups which already found P/M fit and therefore making revenue) (Graham, 2012).A startup needs to pick the growth rate they think they can hit for that week, and fully focus on that rate. Bottom line for the weekly growth rate is 5-7%, exceptionally well is a growth rate of 10% per week. Lower than 5% tells the founders they have not figured out the riskiest parts of the business model. Correspondence on that growth rate takes place each week, to be able to change directions in time, or continue growing on that particular growth rate (Graham, 2012)Although a weekly growth rate focuses obviously on weekly growth, it still affects the long-term decisions. Graham (2012) uses the example of hiring a programmer to implement a new feature, to perhaps reach the growth rate in a month when the startup did not reach it that particular week. Such a decision is only allowed when the startup (a) does not miss its’ growth rate number in the short term, and (b) the startup is worried enough of not keeping to hit the growth rates without a new hire. This decision reflects the positive influence of forcing a startup to discover new ideas as part of an evolutionary process, to in the end staying on track concerning reaching the identified growth rate (Graham, 2012). SPIM Framework Application ModelAs the previous section discussed, the appropriate weekly picked metrics (OMTMs) bring focus to startup founders (and other stakeholders), which is considered as key in startup success. Therefore this chapter will close with an application model, based on Croll and Yoskovitz (2013), describing a method supporting stakeholders in order to bring the ‘picking the right metrics’ approach into practice. An important note on this SPIM Framework Application Model is that it primarily aims at application of the stage-dependent metrics and less at general metrics, since the latter always remain the same for every startup stage and therefore less relevant in the weekly iterative process of picking the right metrics.40005002315210* Moment of Communicating results (sharing performance information) remains flexible, since interview data shows stakeholder agreements deal with reporting cycles and their content00* Moment of Communicating results (sharing performance information) remains flexible, since interview data shows stakeholder agreements deal with reporting cycles and their contentFig. SEQ Fig. \* ARABIC 23 – Method supporting picking the right metricsThe method depicted in figure 23 shows an iterative, Lean Startup corresponding approach, to enable picking a (weekly) metric: the OMTM. Which supports the testing of hypothesis through measuring results on the OMTM tied to that particular hypothesis. Bottom-lines are useful in determining whether a hypothesis can be validated or invalidated. The cycle time preferably is a weekly period. Both the prescribed growth rate and cycle time-period are corresponding to best practices from Y Combinator as described in the previous section. This part will elaborate on the steps in the model. (1) The process starts with formulating the hypothesis, as the core of the iterative Lean Startup process. (2) Then a related OMTM needs to be picked from the SPIM Metrics base, based on two startup characteristics: the Business Model, in this particular research SaaS, however further research can extend to other business models, and the Stage a startup is in. (3) This metric needs to be checked on the quality criteria as described 5.3.1.. (4) Thereafter a bottom-line will be used in order to avoid unbound data measurement. As a bottom-line, two possible ways exist: the weekly growth rate of 5-7% for a particular metric as described in the previous section, or keeping track of the Lean Analytics bottom-lines related to the metrics as described in 3.6.3.3 (however the latter merely are characterised by long term measurements). However, the iterative character of the model does also suggest space for improvements, where an improved bottom-line might be more appropriate in some situations than theory provides. (5) Measuring the results enables the startup stakeholders to prove whether the formulated hypothesis from the first step can be considered as (6a) validated or (6b) invalidated. (6a) Validation leads to (7) communicating the results to the stakeholders involved, where after the cycle can be repeated with a newly formulated hypothesis. However, when a hypothesis is considered as invalidated (6b), two options are available to the stakeholder: The stakeholder (8) gives up and (7) communicates this event to the stakeholders involved, where after a new and maybe more realistic hypothesis will be formulated.0701040Summary Started with a conceptual model, a SPIM framework is developed along the way during the research period, through findings in literature and interviews. The SPIM framework consists of multiple parts. First the two parts on Stakeholders and Metrics (both Stage-dependent and General), all modelled on the four Marmer stages, the corresponding three main milestones and its related startup activities to focus on.However, only an overview of startup stages, activities, stakeholders and a set of metrics is not considered as useful on its own. Startups and stakeholders need to know which metrics they need to consider as relevant to track. This in order to use these to support growth in an efficient way, keeping the entrepreneurs focused. Both the OMTM (Only Metric That Matters) technique, originating from Lean Analytics, and the weekly growth rate from Y Combinator are described as useful techniques to pick the right metrics. To support this particular process in the Lean way, a Framework Application Model is provided, where in a weekly cycle, the right metrics can be chosen by the startup stakeholders. This in order to validate hypotheses stated about, for example, parts of the Business Model. Or just to keep track of bottom-lines and weekly growth rates in order to grow the startup according to those bottom-lines provided through adopted best practices from Lean Analytics and Y Combinator. 00Summary Started with a conceptual model, a SPIM framework is developed along the way during the research period, through findings in literature and interviews. The SPIM framework consists of multiple parts. First the two parts on Stakeholders and Metrics (both Stage-dependent and General), all modelled on the four Marmer stages, the corresponding three main milestones and its related startup activities to focus on.However, only an overview of startup stages, activities, stakeholders and a set of metrics is not considered as useful on its own. Startups and stakeholders need to know which metrics they need to consider as relevant to track. This in order to use these to support growth in an efficient way, keeping the entrepreneurs focused. Both the OMTM (Only Metric That Matters) technique, originating from Lean Analytics, and the weekly growth rate from Y Combinator are described as useful techniques to pick the right metrics. To support this particular process in the Lean way, a Framework Application Model is provided, where in a weekly cycle, the right metrics can be chosen by the startup stakeholders. This in order to validate hypotheses stated about, for example, parts of the Business Model. Or just to keep track of bottom-lines and weekly growth rates in order to grow the startup according to those bottom-lines provided through adopted best practices from Lean Analytics and Y Combinator. The stakeholder returns back in the process to (5) measuring for another time-period (preferably week) until the formulated hypothesis can be considered as validated.Conclusions342900632460RQ How can Startup Performance Information Management (SPIM) support Startup Building in a Venture Builder Ecosystem?00RQ How can Startup Performance Information Management (SPIM) support Startup Building in a Venture Builder Ecosystem?This chapter will provide conclusions on the research. The different research questions will be answered in order to provide an answer to the central question in this research, which is: The first part of the research is the startup building part, consisting of three research questions, to gain insights in the characteristics of startups, their building process and the ecosystem they operate in. The first question to answer is what startup building methods do exist. The second question deals with the structure of the startup lifecycle (phases and stages). Both will be answered simultaneously, since they are that much interrelated, however there might be a slight difference between stages serving as building method components and phases referring to the startup lifecycle. Where after an answer will be provided to the third question concerning building organizations.Startups were built through traditional methods (like waterfall) before, where currently non-traditional methods (like the Lean Startup) have taken over. From the different (non-traditional) building methods (i.e. frameworks), the six most common known ones are included, conceptualized through different stages. Most method stages are named differently, however the content of the stages target mostly similar parts, since they are mostly based on the Lean Startup method (Ries, 2011). The ones selected for further use in this research are the Lean Analytics method, developed by Croll and Yoskovitz (2013) and the Marmer stages, developed by Marmer et al. (2011). Important to keep in mind is the iterative character of the different frameworks, since pivots, i.e. major changes in the business, are normal. Marmer et al. (2012) even found that startups pivoting once or twice raise more money, have better user growth and are less likely to scale prematurely than startups pivoting more than 2 times or not at all. The three main milestones Problem/Solution Fit, Problem/Market Fit and Growth (Maurya, 2012) align seamlessly to the four Marmer stages. Therefore both frameworks are used in the target SPIM framework. Reaching the P/S Fit milestone means you have significantly identified your customer segment and a vision on a possible solution. Reaching P/M Fit means the solution, in this stage represented by an MVP, is sufficiently validated in the market. What follows is the Growth phase, where its first important part is preparation for the growth, i.e. Scale phase, through the Effiency phase. This is highly important considering on of the major findings of Marmer et al. (2011), and Croll & Yoskovitz (2013) stating that premature scaling, assuming there is Product/Market Fit and leaving the Validation/Stickiness phase too early, by going to the Scale/Virality phase, emerged as the most common reason for startups to fail. Interview results show the focus of venture-building organizations towards using those (non-traditional) methods and lifecycle descriptions, whereas other stakeholders, investors for example, communicate using their own methodologies. They are less used to the Lean Startup terms and more convenient using terms like for example Seed, Early-Stage, and Late-Stage. Theory shows the methodologies to describe such a perspective on startup lifecycles is used for a couple of decades already, Ruhnka and Young for example (1987), and therefore can be determined as being a more traditional perspective. The third question is to search for a detailed descriptive background on the startup ecosystem, e.g. the building organizations and the related stakeholders. As the introduction described, Cohen and Hochberg (2014) claim little research is done in the field of startup building programs, both descriptive and result oriented. Therefore the research has separated and described three types of startup building organizations, the Incubator, Accelerator, and Venture Builder, whereas for the last one a ecosystem diagram and a first definition is provided. The ecosystem consists of different types of stakeholders, where the research has focused on the Investors. Findings on the positive association between receiving funding and startup growth are described. The investor types this research focuses on are: BAs, the independent wealthy individuals, and VCs, the professional investment funds. BAs tend to focus on the Seed and Early Stage phases of a startup, where VCs tend to invest later, in Early Stage and Later Stages. Important finding is the investment risk factors similarity to startup success factors. The research overview of risk factors provided a prioritized categorization for those success factors, which are: (1) Team, (2) Product & Market, and (3) Startup. Findings from interviews show similar distinctions in success factors categories. Those risk (or success) factors needs monitoring, however early-stage companies do not have historical information to provide to investors for most of the different factors, which also is stated by stakeholders through the interviews. Therefore Gompers (1995) argues that investors need to invest in monitoring, where Davila and Foster (2005) found that involvement of VCs brings formal monitoring (information systems) for the first time to startups. In line with these findings, this particular research has tried to figure out a way of bringing that formal monitoring to startups earlier, when, for example, still in the Discovery or Validation phase. Therefore, the term ‘SPIM’, Startup Performance Information Management emerged.The second part of the research elaborated on that type of information management, SPIM, which is the performance measurement and information management of startups. This part elaborates on SPIM, the search for supporting information systems, and a final framework as a result of both the first and the second part of the research. The fourth research question deals with the definition, purpose and content of SPIM. SPIM is defined by bringing several definitions together. SPIM is the collection and communication of performance information produced through the execution of Business Performance Management, in order to make quicker and better decisions. To implement information systems in order to digitalize this process, first an understanding of the underlying problems, technical elements and the organizational processes is needed; therefore this research started with describing the startup and related building organizations background. The main goal of the research is to improve startup performance, where indeed Taticchi et al. (2010) argue performance measurement is a crucial element. Eight advantages of performance measurement are described in the same chapter, explaining how metrics contribute to both clear communication between employees and company success. The focus in performance measurement has shifted from a mainly measurement of financials towards a more measurement of innovation. This can be seen as a shift corresponding to the (apparently still existing) difference between the (traditional) investor perspective on startups and the (non-traditional) venture-building organizations perspective on startups.The metrics derived from research are divided into general metrics and stage-dependent metrics. General are the ones involved at all stages of a startup, divided in line with the success factor categorization from previous literature: Team, Product & Market, and Startup. Whereas stage-dependent are the ones especially designed to be used for one or more stages, divided in line with the four Marmer stages (Discovery, Validation, Efficiency and Scale). Croll and Yoskovitz (2013) consider focus as key to startup success; therefore picking the right metric (OMTM) and focusing on growth for that metric is a necessary part of the process of using SPIM in startups. The fifth question tries to search for an answer concerning SPIM supporting information systems (i.e. tools). Davila and Foster (2005) found a positive association between the adoption of management control systems and (at least) two startup characteristics: startup growth and CEO tenure length. Therefore the section on existing SPIM tools is included, consisting of descriptions on the Lean Canvas, Validation Board and Lean Dashboard, chosen based on several requirements. All of them support a part of the Lean Startup methods in a certain way, however therefore not being solutions for all the processes, in particular SPIM concerning metrics. After the interview results are included, the last research question can be answered. The sixth research question deals with searching for a way of modelling the SPIM information in a SPIM framework. That process started with a conceptual model, which has evolved over the time of research towards the final SPIM framework, consisting of two parts, one on the stakeholders and one on the SPIM itself. The first part consists of the four Marmer startup-building stages, three Lean lifecycle phases (or milestones), corresponding startup focus activities and stakeholders tied to these stages and phases. The second part focuses on SPIM, consisting of the four Marmer startup-building stages, three Lean lifecycle phases (or milestones), corresponding startup focus activities too. But in this framework the stage-dependent and general metrics tied to these stages and phases are included, in order to enable SPIM, which supports performance information management and growth of startups within venture builder ecosystems.DiscussionThis chapter will discuss the limitations and provide recommendations for further research.LimitationsStartups built through Lean methods (non-traditional), as well as related building organizations, are not common subjects in scientific research yet, as claimed by Blank (2013) and Cohen and Hochberg (2014). Therefore this research can be considered mainly as exploratory research, exploring non-traditional concepts, combining it with traditional perspectives on these concepts. The largest limitation therefore was concerning formulating the right and feasible research questions taking the (then partly unknown) scope in consideration. One of the main limitations related to this aspect, is finding the right stakeholders for relevant data collection. Finding individual Business Angels is hard and perhaps might be not sufficient in order to represent the heterogeneous BA market. Therefore BA networks are used as representatives for population. However, these network founders know less about the topic of how BAs monitor the performance of startups after the investment is done. Some field of tension on formulating conclusions on BAs emerged there. Also concerning the stakeholders, a limitation is the fact that besides the (relative young) host company, venture builders are not common in the Dutch startup ecosystem, let alone experienced ones. Therefore, only building programs could be the subjects of interview, whereas incubators were easier to approach as accelerators were: none of the (multiple) approached accelerators had the ability to cooperate in this research. The main research question therefore is answered for supportive startup ecosystems instead of venture builders in particular.A related ecosystem limitation is considering the external validity, whereas only data on Dutch stakeholders is gathered, and none of the conclusions therefore are directly applicable on non-Dutch stakeholders. Which corresponds to the findings in data on VC 4, who mentions that this research, partly consisting of SaaS investing, needs to involve foreign investors, concerning knowledge and experience aspects on SaaS. For example, only data on VC 4 shows they are using the currently recommended metrics, which also are the ones described by the modern blogs nowadays, since VC 4 mentions he dived into recent theory. Also on the general metrics not much non-traditional approaches, for example quantification, are used. For example, only Expert 2 talked about quantification of Team aspects. Feedback concerning those kinds of issues is not gathered through a second round after the first round of interviews. The only verification done afterwards through email is on the tools VC 3 uses. Another main limitation, related to the exploratory character of the research, is concerning the way the framework is formed. After doing interviews, the framework seems to be not that much focused on stakeholders anymore, like the conceptual model was, since not all of them are familiar with the non-traditional ways startups are being build with currently, and the corresponding metrics. Therefore, tying the stakeholders and their exact information demand to the different stages for those stakeholders is hard, where the latter even more, is impossible when taking significance of conclusions into consideration. The research tried to come up with two parts of a complete framework, one on stakeholders and one on performance information. Perhaps, tying different abstraction levels for different stakeholders to information would be more convenient. Due to the limited research timeframe, unfortunately research on which Information System would enable digitalizing the use of SPIM, and therefore contribute to startup growth, could not be executed.Further ResearchThis section will provide recommendations for further research. The first important aspect to elaborate on in future research is the non-traditional startup movement, the Lean Startup, related to both new ways of SaaS startup building as well as new perspectives investors are going to need when investing in these specific startups. Another recommendation is on including other streams of theory, which could be for example on the use of Knowledge Management theory: the theory of Nonanka might be useful in describing how to transform implicit to explicit information, especially regarding startup team aspects.The third recommendation is concerning the stakeholders, whereas the perspective of entrepreneurs themselves on the framework might be interesting, in order to improve this first SPIM framework. Also a feedback session on the SPIM framework with Building Organizations and Investors would provide a more accurate framework.Another recommendation is further research into the framework metrics: the level of detail, data quality/privacy, metrics focus, and further implications. Concerning this level of metrics/data detail requested by stakeholders, some of them mentioned a difference in detail level of information: VCs with large portfolios might focus more on high-level financials compared to VCs with small portfolios, due to simply a difference in level of involvement and available monitoring time. Rules concerning quality/privacy rules will be interesting in further research as well, when further evaluating and implementing the framework. The aspect concerning, focus: BAs with less technological knowledge might focus only on business model metrics, and less on product metrics, as interview tips suggest. Another aspect to elaborate on in further research is the usage of metrics tied to the prediction of startup success. Some bottom-lines representing a healthy startup already are provided in this research, although further research might lead to more and proven bottom-lines on the long-term in order to be useful for predictions. 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Is the interviewee actively trying to solve the problems, or has he done so in the past?YesHe's trying to solve the problem with Excel and fax machines. You may have struck gold10Sort of He spends a bit of time fixing the problem, but just considers it the price of doing his job. He's not trying to fix it.5NoHe doesn't really spend time tackling the problem and is OK with the status quo. It's not a big problem03. Was the interviewee engaged and focused throughout the interview?YesHe was hanging on you every word, finishing your sentences, and ignoring his smartphone.8Sort ofHe was interested, but shows distraction or didn't contribute comments unless you actively solicited him.4NoHe tuned out, looked at his phone, cut the meeting short, or generally seemed entirely detached--like he was doing you a favour by meeting with you04. Did the interviewee agree got a follow-up meeting/interview (where you'll present your solution)?Yes, without being asked toHe's demanding the solution "yesterday"8Yes, when you asked him toHe's OK with scheduling another meeting, but suddenly his calendar is booked for the next month or so.4NoYou both realize there's no point showing him anything in terms of a solution05. Did the interviewee offer to refer others to you for interviews?Yes, without being asked toHe actively suggested people you should talk to without being asked.4Yes, when you asked him toHe suggested others at the end, in response to your question.2NoHe couldn't recommend people you should speak with.06. Did the interviewee offer to pay you immediately for the solution?Yes, without being asked toHe offered to pay you for the product without being asked, and named a price.3Yes, when you asked him toHe offered to pay you for the product.1NoHe didn't offer to buy and use it. 0Appendix B – Interview Protocol (Startup Building Organizations)IntroductionGraduation Research Business Informatics master, Utrecht University.Research GoalsStartup and Stakeholders insightsStartup lifecycleStakeholdersStartup Ecosystem Information Management insightsProviding stakeholders better and possibly new insights into startup de building & investingShow Target Framework Reason to interview that particular intervieweeStakeholdersWhich stakeholders are the most important ones in the startup building process?Startup lifecycle- GeneralIn which stage of their lifecycle is a startup when applying to your program? Which type of startups do you build? / For which sectors?- MethodWhich startup building method do you use for venture building?What makes this particular method suitable for you?To which extent are you, as an incubator/accelerator, planning your milestones?Stakeholder [building organization] InformationWhat information/data are you asking for in the different stages of your startups?To which extent Quantitative / Qualitative?Which consequences are the result of that data?For example: Go’s/No-go’s, etc.?How is the team formed / assessed, before/shortly after applying for the programme?How do you monitor team performance during their stay at your startup-building program/organization? Stakeholder [Investor] InformationAre there any investors involved in the process, and if so, from which point in the startup lifecycle are they involved? Are these investors Business Angels or Venture Capitalists?What information/data do these investors ask for?To which extent is that information/data different from what you are asking for?Which role is assigned to investors within a startup?Appendix C – Interview Protocol (Investors)IntroductionGraduation Research Business Informatics master, Utrecht University.Research GoalsStartup and Stakeholders insightsStartup lifecycleStakeholdersStartup Ecosystem Information Management insightsProviding stakeholders better and possibly new insights into startup de building & investingShow Target Framework Reason to interview that particular intervieweeStakeholder(s) RoleAre the (framework) included stakeholders the most important ones in the startup building process?In which stage of their lifecycle is a startup when applying to your program? Which startup sectors do you invest in?Startup Performance- Before InvestmentWhat information (or factors) do you need to evaluate an unknown startup on?(Check mentioning Startup & Team)How do you do that evaluation research? (Check Informal meeting(s), Due diligence, etc.)- After InvestmentWhat information/data are you asking for in the different stages of your startups?(CheckBasic: Example. No. of customers, Revenue, Profit & Loss (snapshot)Advanced: Data driven, customer data (real-time KPIs) (period) )To which extent is that information/data different or less from what a startup has?Which consequences do that data result in?For example: Investment follow-up/stopEngagementDo you participate in the Board/Management Team to closely monitor the performance?Do you coach the startups/teams?ClosingDo you have any remarks/tips?Appendix D - First SDEIF (version 0.1)-1770671148301700Appendix E – Second SDEIF (version 0.2)-1682554133139900Appendix F – Third SDEIF (version 0.3)-168275021336000Appendix G – Fourth SDEIF (version 0.4)-1035050190500 ................
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