Notes on Web 2.0



White Paper: Creating the World of Enterprise 2.0

Serus Corporation

Created 01/03/07

Updated 01/12/07, Updated 01/22/07

Updated 02/11/07, Updated 02/22/07

Updated 03/09/07, Updated 04/15/07

Updated 05/05/07

Executive Summary

In the last 18 months, the Internet world has been greatly changed by the development of “Web 2.0”. A range of different meanings have been given to this term, but all of the meanings revolve around an Internet that is “socially linked,” as well as technically linked. The interactivity of the applications has reached a higher level than that of e-commerce applications of the 1999-2000 era, and the boundaries between the producers of content and the users have become blurred.

The “social linkage” stems from the use of the Internet as means of interacting on an “always on” basis, in which a community is formed by users voluntarily sharing their calendars, contact information, preferences, critiques, and other content via information utilities. Today’s users take advantage of low-cost high-bandwidth connectivity to share stories and videos. Any user can upload new content, and any user can provide comments on the content. Users can tailor and combine information in new ways, such overlaying map or geographic data with information on favorite stores or coffee shops.

Serus Corporation believes that the “Enterprise-level” use of similar technologies will create a new category (called “Enterprise 2.0”) of value-added information services for corporations. In this white paper, we review the most relevant aspects of Web 2.0, and extrapolate those trends into the world of the enterprise. We include a discussion of Enterprise 2.0 trends from the early paper by Andrew McAfee.

Serus Corporation focuses on “out-sourced operations management”, typically in high-tech manufacturing. We believe that there are eight key aspects of Enterprise 2.0 for corporate planners, schedulers and operations, and each are defined and discussed in this paper:

• Collaborative – everyone participates as a reader and author of content

• Options – generate options to resolve an exception

• Notifications – generate alerts for exception conditions

• Tags & Comments – content can be marked and prioritized

• Real-time – content is fetched up to the minute

• Open – uses open systems content, such as XML

• Links – hyperlinks between concurrent analysis processes

• Scenarios – create what-ifs and forecast results

These items are already present or under development in the Serus Intelligent Operations Management platform, which we will use as basis for driving the definition and deployment of Enterprise 2.0.

Review of Relevant Aspects of Web 2.0

In the fall of 2006, the O’Reilly 2.0 conference included a “Principles and Best Practices” survey paper. That paper provided much useful information regarding current trends in industry. One of the key comments was as follows:

Web 2.0 is much more than just pasting a new user interface onto an old application. It’s a way of thinking, a new perspective on the entire business of software— from concept through delivery, from marketing through support. Web 2.0 thrives on network effects: databases that get richer the more people interact with them, applications that are smarter the more people use them, marketing that is driven by user stories and experiences, and applications that interact with each other to form a broader computing platform.

In many respects the same awareness of the network effects was already in the culture of collaborative operations managers in today’s businesses. At Serus Corporation, we have provided software systems for the operations managers who handle planning, scheduling, and day-to-day exception management for manufacturing operations in out-sourced locations.

A casual visit to the “war rooms” of operations managers clearly showed that they have understood the network effect of information early on – but their technology was largely filing cabinets, fax machines, telephones, and calendars on the wall. The physical desktops of many such users are buried in documents. The efficiency of the operations was compromised by different types of information, disjoint sources of information, incompatible data formats, etc. Many of the first-generation operations management software solutions provided little more than visibility into the activities at the out-sourced locations.

But today, we find that many of the information integration challenges are being addressed, partially due to the same standards that have enabled Web 2.0, such as XML, RSS, distributed databases, broadband transmission of information, real-time messaging, etc. So we see the enterprise world starting a new phase Enterprise 2.0, which focuses more on how information is shared across the network of business partners and how to improve its value, using the various instruments of Web 2.0.

The Web 2.0 applications and companies that have since emerged understood that information gains value as more of it is collected, and that communities can self-organize and manage this information. For instance, the retailer collects feedback on each book that is offered, and feedback on each transaction, as well as stores and builds on the buying patterns of every customer. Likewise, eBay maintains feedback ratings on each transaction and each buyer and seller. Sites like de.lico.us maintain user preference “tags” that show what a user is interested in, so that the application can carry out an on-going search for other items of interest. Wiki-based sites like Wikipedia allow any user to edit the information being shown on the pages, so that any user becomes a publisher. The user can make new pages, and create links, all without knowing anything about HTML or application software. Finally, the mode of delivery is changing to subscription-based ASP (application service provider), rather than installing traditional enterprise applications.

Technological and Cultural Shifts

The O’Reilly report identified eight core patterns of Web 2.0, and the most relevant of those from our perspective are the ones focused on data:

• Harnessing Collective Intelligence

• Data Is the Next “Intel Inside”

• Rich User Experience

For gathering and managing the collective intelligence of the manufacturing ecosystem, Serus is developing a Master Data Management facility combined with an SOA-based approach to collecting data from multiple sources. The system can cleanse and correlate information.

The rich user experience is enabled by AJAX-based tools and libraries. We are using the “dojo” toolkit, and have augmented our applications for AJAX.

The largest shift in the user experience is the requirements for increased personalization of content display and interaction. Our application allows for personalized control over display layouts, alerts, and reports.

Evolution beyond Today’s Web 2.0

Web 2.0 emerged because the users were overloaded with disjoint information sources. For instance, people had Internet news, Yahoo directories, product listings on Amazon, event listings on services such as Fandango, movies at Blockbuster, maps from MapQuest, etc. There was little integration between them.

One part of the first Web 2.0 applications sought to integrate some of this content; for instance, Google added maps and news, Amazon added movies, etc.

The other aspect of the first Web 2.0 application was, they leveled the playing field for content, from a source-driven to a peer-to-peer basis. Think of the change from having just one movie review organization (for instance, Siskel and Ebert) to having an entire community of movie reviewers, in which you are a viewer and reviewer.

Enterprise users today, particularly those in distributed manufacturing operations, are faced with exactly the same challenges. They have too many disjoint information sources: WIP reports, cost reports, logistics analysis, product lifecycle changes, demand reports, regulatory changes (e.g., restrictions that stem from Removal of Hazardous Substances regulations).

Some companies have already begun the shift to Enterprise products. For example, the Google Maps product started in early 2005 as a consumer-oriented service with no support, guarantees, or SLAs. But in spring 2006, the company unveiled Google Maps Enterprise—a licensed, fully supported, more enterprise-friendly offering.

The recent article “Enterprise 2.0” by Andrew McAffe in MIT Sloan Management Review article describes the organizational impact of Web 2.0 technology at a financial services firm DrKW. He identifies six key factors in the change, which have the acronym “SLATES”.

Search

For any information to be valuable, the users must be able to find it. Hence, effective search tools are critical.

Links

Place hyperlinks everywhere, allow for jumps from article to article.

Authoring

Anyone can be an author of content. Rather than having a fixed structure of people who create content, and people who review it, new material can be generated by any users.

Tagging

A tag is a Web 2.0 term for placing a user-specific mark onto a document that indicates its relevance or importance.

Extensions

By use of a collaborative filtering algorithm, the extension facility can suggest related documents, using the premise: “if you like this, then by extension you will like that”. This same approach is used at Amazon to suggest related books using buying history and preferences.

Signals

The enterprise application must generate signals to users that new content has appeared. The conditions for generating the signals should be user-specifiable.

A Day in the Life of the Operations Management User

Serus’ research and analysis has suggested a number of additional key factors which are important for operations management Enterprise 2.0 applications. We go a few steps beyond what is described above. In general, while the six items above help categorize the factors that are useful for a document-based system such as one that is sharing notes and wiki-pages between members of the organization, the operational users are more interested in sharing quantitative analysis of a plan or a situation. Here is a typical situation:

It is the 10th week of the operational quarter. The operations manager at NetworkDevices-Are-Us doesn’t have a factory floor that he can visit to track the activities, since all of their chip production is carried out by TSMC or Amkor across the ocean. After their chips are completed in Taiwan, they are tested and assembled at another facility, which is located in Japan. Then the chips go into router manufacturing at Jabil in Florida, and then get shipped to a customer. Each of these stages takes about 3 days of production time, plus about 3 days of transit time from one place to another.

The activities are scheduled according to a sales forecast for each week of the quarter, which was collaboratively created and reviewed back on week 5. There was an update on forecasts, but that hasn’t been made into a new production plan.

This week, ND-A-U receives a new order for 5,000 routers from East Coast University, with a shipment date of the 13th week of the quarter (the corporate calendar organizes the weeks in 4 equal 13-week chunks).

To meet the order, he must reschedule several activities. While trying to generate a few revised plans and alternatives, he gets a phone call that reports that there is a hurricane approaching Florida, and Jabil’s operations will be out for at least 4 days.

He then needs to carry out several scenarios, each of which represent different assumptions and approaches.

• Redirect the standard production from Florida to another location

• Also add in an extra amount for the ECU order, on the premise that it is a “blue-bird” order

• Assume that ECU order is actually part of next week’s forecast, and simply shift those units one week earlier in time.

• Create a baseline that shows the impact of the hurricane if nothing else is done, to get cost basis for amount of extra effort that must be accounted for in expedited shipments.

Once these plans are made, the best 2 or 3 will then be sent to the VP of Operations, for final review. It would be preferable for the system to maintain links between the resulting plans and the scenarios that created them, and the relative marketing forecasts and the new order, but actually all of these are in different emails or spreadsheets, so the operations manager has to attach all of them together into an email for the VP of operations, and then write a email that explains which attachment is part of what option.

All of these efforts by the operations manager work on live documents that are quantitative plans based on the forecast numbers, the production numbers, and use the corporate calendar.

Here are the factors that we see as important, which can be summarized by the acronym “CONTROLS”

Collaborative

This is a restatement of the idea that anyone can be an author and reader of content. However, it adds the idea that the resulting document may be a quantitative report or table, in which some numbers come from one participant in the collaboration, and some from others.

Options-based

The system should generate the set of options that the manager has to deal with, include adding in the branches to the initial set of choices when the new information about the hurricane is received.

Notifications

The system should generate alerts for the exception conditions. In this case, the placement of the order which exceeds the forecast would start a rescheduling activity right at the time that the order is place.

Tags & Comments

This is restatement of the idea of tagging that was present in the McAfee article, with the additional capability that the tagging is now on dynamic content rather than static documents. For instance, tagging and commenting is critical in cross-organizational approval of a plan or document, e.g., Jim will add a comment like “I will approve if Jack approves”, then Jack will add a comment that says “ I will approve if the date is shifted from 3/12 to 3/16”, etc. This kind of paper trail must also be non-revocable, because in the enterprise, it will also be used for tracking Sarbanes-Oxley compliance. An example commenting threads might look like:

[pic]

Real-time

Content is fetched up to the minute, as is shown in the example regarding weather. The same is true for the factory status reports, which come in from TSMC on a real-time basis. Actually, in many cases each individual factory is only generating a report every 4 to 6 hours but the factories are in 3 or 4 different time times, so that there is a time reconciliation issue to deal with as well.

Open

Uses open systems content, such as XML. This enables effective transmission of content between the different sites.

Links

This is a modification of the “Links everywhere” criteria of the McAfee article, with the idea that the links are also joining the different raw data sources the analysis results, the working documents, and the completed scenarios. It means that when an analysis is sent out, it is not in a set of distinct spreadsheets, but is automatically linked together.

Scenarios

The generation of the what-ifs and expected results is critical in the above situation. To carry out the what-if’s the operation manager is trying out different routing plans, different time delays, and different schedules.

Tools for Enterprises

The Serus product is a highly flexible, real-time application that augments existing systems to enable operational planners and executives to manage Financial Exposure across supply and demand chains. Its platform interfaces with existing ERP and other systems to collect information, allows the user(s) to generate, review, and track plans and handle exceptions within the dashboard-based screens of the application, and take actions that are sent back down into the ERP and operational systems. This flow is shown in the diagram below:

[pic]

For the past five years, Serus has been building a platform that enables Enterprise 2.0, even though it wasn’t called as such. The platform offers the following capabilities, which support the modules:

• Management of collaborative, transactional, business content

o Raw data stores/caches/catalogs of products, orders, locations, costs, flows, etc.

o Meta-data (information about the fields and structure of the data stores)

o Collaborative posting of changes to managed content

o Change tracking

o What-If’s (scenarios that consist of provisional changes)

o Dynamic Custom Formulas and Analytics against content

• Loosely coupled eco-system

o Service Oriented Architecture using Web Services or other protocols

The platform also supports personalization, which refers to the tailoring of the presentation or action of the system, typically on a per-user basis. There are several examples:

• Presentation: defines what columns are present and in what order

• Calculation: defines new columns

• Shortcuts: as shown above to personalize the quick access shortcuts.

• Behavior: to define actions such as alert actions.

• Templates: to define pre-filled-in template for orders and other complex business objects. Commonly used for repeated replenishment orders.

• Reports: to define specific reports or views

The calculation facilities allow a user to create a new value to be used in an alert or column using a spreadsheet-like formula expression. The formula can use any of the fields located in the output reports, and can derive new values using math, logic, and financial functions.

The subscription based service allows for:

• Ease of deployment – self deployment tools available for customers

• Builds ecosystem as viral effect

• Allows for easy integrations with internal systems and external data sources such as XML, web services, demonstrates the advantages of SOA architecture

• Standardized the data exchange information and formats with potential to become the data hub

Content in the Enterprise 2.0 Environment

Three sets of content are managed and generated

• Private Data – Virtual enterprise information private to a customer

• Ecosystem Data – Ecosystem information generated by monitoring the performance of the enterprises in the ecosystem

• Public Data – Information available accessible on the internet; free space.

[pic]

The future services that can be offered over the ecosystem would be

• Mash up of public data and private data – integrate public and company Information

• Mash up of public, private and ecosystem data – for instance to a content provider of compliance (SOX, RoHS) information

• Integrating the ecosystem Data - Master data of product catalogs

• Integrating private and ecosystem Data - Vendor performance services

Monetizing the Enterprise 2.0 Service

Subscriptions and advertising have driven the monetization of Web 2.0 applications and services. In the corporate environment, these models may not apply as well.

However, there are several distinct advantages to operating in the corporate environment:

• Clearer cost-benefit perception

• Numerical values of benefit gains from exception resolution

• Quantitative metrics calculated from ecosystem information

• Quantities measures of the value of the information obtained from the ecosystem

Hence, besides the typical subscription fees and transaction fees, we expect to charge based on the economic value of the information provided to the user, both as direct information and as used in the scenarios.

Users will be incentivized to contribute their input to the system by offering discounts and charge-backs for provided information.

Thru these approaches, we hope to avoid having screens cluttered with advertising.

Decision Support

We feel that the largest difference between consumer use of these technologies and enterprise use is that while consumers largely have a goal of being informed (“what is the new hot movie?” or “where is the shopping center?”), enterprises have an additional goal of making decisions (“what is the best plan for scheduling production?” or “how do we respond to an unexpected change in demand or transportation?”).

Decision support is more than just reporting. It refers to the ability to perform what-if analysis within the application without affecting the other parts of the application and without saving the results to be transacted into other parts of the application until the user has arrived at a solution or result they like. This involves changing numbers, rules, and parameters, then running an analysis, and then saving a scenario for future reference, and then running a new scenario. A user may save three or more scenarios, then review with a group of people, once a final scenario has been selected, that scenario is then used to update or recalculate results or used to perform analyses in other modules.

Scenarios may be called up using a scenario access screen for a module, which aids by sorting the scenarios according to user-selectable criteria such as lowest cost:

[pic]

Conclusion

We believe that there are eight key aspects of Enterprise 2.0 for corporate planners, schedulers and operations managers, and have defined each:

• Collaborative – anyone can be an author of content

• Options – generate options to resolve an exception

• Notifications – generate alerts for exception conditions

• Tags & Comments – content can be marked and prioritized

• Real-time – content is fetched up to the minute

• Open – uses open systems content, such as XML

• Links – hyperlinks between concurrent analysis processes

• Scenarios – create what-ifs and forecast results

These items are already present or under development in the Serus Intelligent Operations Management platform, which we will use as basis for driving the definition and deployment of Enterprise 2.0.

The solution will then become an ecosystem, in which the information is worth more than the sum of the parts.

References

O’Reilly “Web 2.0 Principles and Best Practices” conference presentation, Fall 2006. By John Musser, with Tim O’Reilly and the O’Reilly Radar team. Published by O’Reilly Media, copyright 2007, 100 pages.

“Enterprise 2.0: the Dawn of Emergent Collaboration” by Andrew McAffee, MIT Sloan Management Review article, Spring 2006, vol. 47, no. 3.

Business Week article on Amazon’s web services, November 2006

“Ajax in Action” by David Crane and Eric Pascarello, Manning Publications, 2006.

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Private Data

(Owner = Customer)

Public Data

(Owner = third party)

Ecosystem

Data

(Owner = Serus)

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