CHAPTER Chapter 10: Managerial Support Systems



CHAPTER 12: Managerial Support Systems

|Chapter Outline |

12.1 Managers and Decision Making

12.2 What Is Business Intelligence?

12.3 Business Intelligence Applications for Data Analysis

12.4 Business Intelligence Applications for Presenting Results

12.5 Business Intelligence in Action: Corporate Performance Management

|Learning Objectives |

1. Identify the phases in the decision-making process, and use a decision-support framework to demonstrate how technology supports managerial decision-making.

2. Describe and provide examples of the three different ways that organizations use BI.

3. Specify the BI applications available to users for data analysis, and provide examples of how each one might be used to solve a business problem at your university.

4. Describe three BI applications that present the results of data analyses to users, and offer examples of how businesses and government agencies can use each of these technologies.

5. Describe corporate performance management, and provide an example of how your university could use CPM.

|Teaching Tips and Strategies |

The goal of this chapter is to convey the importance of information systems in helping individuals make informed decisions. Often students approach this chapter with indecision and insecurity. They see acronyms such as DSS, GDSS, ESS, and ES, and they are a bit intimidated or overwhelmed. Explaining how IT provides vital information to decision makers helps to relax students and get them interested.

Information overload is a problem that confronts managers in various types of companies all over the world. Managers may receive hundreds of e-mails but have difficulty deciding which ones should take precedence. Brand managers can accumulate reams of data analyzing consumers’ buying habits or brand preferences. How do they determine which data are important to their brand? This is the paradox of the information revolution. There is so much data, but turning that data into useable information is a challenge.

There is hope. Information technology has advanced to make the data more meaningful. According to a Gartner report (), most Fortune 1000 companies currently use data mining. In fact, data mining is now widespread in all areas of business – marketing, finance, management, operations, etc. . Even several consumer-facing Web sites in e-commerce allow users to search and drill down based on multiple criteria. Users performing a search can narrow the search down to the meet their needs – an example of data-driven decision -making. By discussing these examples, students really get a feel for how important this chapter is and how they can leverage all the data out there to conduct their businesses more productively.

Emphasize that managers now rely on IT systems such as DSS to make more informed decisions. It is essential, however, that the right data are collected and analyzed. An example is and the amount of information that they are able to collect on a single individual. What data does collect from users? At minimum, the following information:

• credit card information

• name, address, phone number, e-mail address

• type of books ordered, hence horror, business, etc.

• previous order history, including type of book bought

• total amount of money spent at

With the use of a DSS and data mining techniques, Amazon managers can input descriptors such as customers who have not purchased anything in the last six months. They can send an e-mail to those customers soliciting new business or give them a discount if they act within the next couple of days. Significantly, Amazon can do all of this with a couple of keystrokes. The manager could even see how well the campaign worked by comparing the number of coupons sent out with the number of coupons validated. If managers wanted to target their advertising even more directly, they could send coupons that are good only for the type of books that the recipients have bought in the past.

Students start to understand the importance of data and information and analysis after this lecture. Many of them will be using similar support systems to Amazon to determine how to run their business more effectively.

Demonstrate to students that AI is not only machine based. Give them the example of using Word for writing applications. When we spell a word incorrectly in Word, most of the time the program “knows” it. Ask, “How does Word know when you have spelled a word incorrectly? Is it magic?” Hardly. Rather, the programmers have input a database of commonly misspelled words with the different incorrect variations people tend to use. Once Word sees that the word is spelled incorrectly, it will put a red line under the word and offer alternatives. The only reason why Word knows the different spellings is that someone has programmed them in there. Many smart phone text applications also do this.

What type of system is Word utilizing? The answer is an expert system. An expert system is a technology that replaces an expert. In this case Word is replacing the English teacher/dictionary. What happens when Word doesn’t recognize a word we commonly use a lot? Word will keep mistaking the spelling as an error. One way around this is to click on the “Add to dictionary” function (this is available when using spell-check). That way Word lthe word is added to Word’s database. Illustrate this point to the class to let them know that an expert system is great, but it is not really functional unless you can add to the database to keep meeting your needs. It is important to update databases to keep them functional for their intended tasks.

Students tend to understand the importance of AI and different expert systems. They realize that these systems are not only used in science fiction pictures such as Star Trek and Minority Report.

A good example of an AI technology that is not catching on due to poor quality and difficulty of use is voice recognition. There are several types of voice recognition software on the market. Unfortunately, they have some serious problems that need to be corrected before they can go mainstream. Some people had predicted that in the new millennium keyboards would be useless (along with the mouse). Instead, we were going to use computers by talking to them. No longer would we have to type notes.. Instead, a user would sit down in front of the computer and start talking away. This scenario has not come close to fruition.

Two reasons why voice recognition software did not take off in the 1990’s were (1) the processors in computers were not fast enough to perform natural language processing (2) and memory was prohibitively expensive. You need both of these elements to make voice recognition work well. As the 2000’s approached, the prices of memory and CPUs became very reasonable.

Manufacturers of voice recognition software started adding features at a rapid clip. Consumers flocked to buy the latest and greatest voice recognition software. Then, about a week after purchasing the software, the consumer would usually give up in disgust. What went wrong?

In the case of voice recognition technology we now have the capability (resources) to make the software work. The problem is our voices. All individuals speak differently, at different rates, and in different dialects. It is impossible for programmers to program the thousands of different ways we speak. Users of voice recognition software are forced to “train” the software by speaking into a microphone and repeating words over and over. Although this is an improvement, many of the training sessions confused the computer as well as the user. Even when the computer had been trained the software continued to misinterpret different words. Users became frustrated and finally gave up.

Hopefully, using the above example will help students understand that computers, although an asset, are not always easy to program or use. It may be decades before we are using voice recognition software that is capable of overcoming these problems.

A classic example of support for all phases of the decision-making process is making a decision about purchasing a new automobile. If you were going to buy a new car, you might go through the following steps:

• Intelligence—Review automobile maintenance records to see if the prior owner had experienced chronic problems or needed multiple repairs. Seek information from dealers, consumer reports and friends about new automobiles.

• Design—Establish objectives and criteria for evaluating automobiles. Assign weights to the various criteria to reflect their relative importance.

• Choice—Generate summary statistics on the evaluation of each automobile.

Chronic problems with an existing automobile might create a situation in which you need to make a decision about purchasing a new car. During the design phase, you may select safety, price, and performance as three key criteria. You can then create a weighted features matrix to establish the importance of each of these factors, such as safety (25 points), price (25 points), and performance (50 points). You could obtain information from dealers, owners, and magazines to help you make comparisons among alternatives. Finally, you could use summary statistics to provide overall scores for each alternative. These scores should provide a concrete basis for a reasonable choice on your part.

This example illustrates the systemic process of decision making long promoted by management scientists. Our challenge is to educate students about current high-level approaches to solving unstructured managerial problems. The fields of DSS, EIS, and AI — plus its spin-off discipline, intelligent systems — created this new realm of possibility.

|Review Questions |

Section 12.1 … Before you go on…

1. Describe the decision-making process proposed by Simon.

Simon proposed a three-stage process consisting of:

• Intelligence – in which managers examine a situation and identify and define the problem

• Design – in which decision makers construct a model that simplifies the problem

• Choice – in which a solution is selected.

2. You are registering for classes next semester. Apply the decision-making process to your decision about how many and which courses to take. Is your decision structured, semi-structured, or unstructured?

Hopefully, students will respond, after some thought, that their process is either structured or semi-structured.

3. Consider your decision-making process when registering for classes next semester. Explain how information technology supports (or does not support) each phase of this process.

Possible responses include checking class offerings online, possibly using the course catalog to check course descriptions. They also might access a Web site like “” if they do not know anything about the course’s instructor. They may also go online to determine which courses they need to graduate.

They may also talk to their friends about a class or instructor. They would probably not need technology to do this, unless they use Twitter or Facebook.

Section 12.2 … Before You Go On…

1. Define BI.

Business intelligence (BI) is a broad category of applications, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make better decisions. BI applications enable decision makers to quickly ascertain the status of a business enterprise by examining key information.

2. Discuss the breadth of support provided by BI applications to organizational employees.

BI is used to fundamentally transform the ways in which a company competes in the marketplace. BI supports a new business model, and it enables the business strategy. Because of the scope and importance of these changes, critical elements such as sponsorship, approval, and funding originate at the highest organizational levels. The impact on personnel and processes can be significant, and the benefits are organizationwide.

3. Identify and discuss the three basic targets of BI.

• The development of a single or a few related BI applications,

• The development of infrastructure to support enterprisewide BI, and

• Support for organizational transformation.

Section 12.3 … Before You Go On…..

1. Describe multidimensional analysis, and construct a data cube with information from IT’s About Business 12.2. (Hint: You must decide which three business dimensions you would like to analyze in your data cube.)

Online analytical processing (OLAP) (or multidimensional data analysis) is a set of capabilities for “slicing and dicing” data using dimensions and measures associated with the data.

Have students refer back to the example of a data cube presented in Chapter 5. Students will have to decide on the cube’s dimensions.

2. What are the two basic operations of data mining?

Data mining can perform two basic operations: (1) predicting trends and behaviors and (2) identifying previously unknown patterns.

3. What is the purpose of decision support systems?

Decision support systems (DSS) combine models and data in an attempt to analyze semistructured and some unstructured problems with extensive user involvement. Models are simplified representations, or abstractions, of reality. DSS enable business managers and analysts to access data interactively, to manipulate these data, and to conduct appropriate analyses.

Section 12.4 … Before You Go On…..

1. What is a dashboard? Why are dashboards so valuable to employees?

Dashboards evolved from executive information systems, which were information systems designed specifically for the information needs of top executives. Today, however, all employees, business partners, and customers can use digital dashboards.

2. Explain the difference between geographic information systems and reality mining, and provide examples of how each of these technologies can be used by businesses and government agencies.

A geographic information system (GIS) is a computer-based system for capturing, integrating, manipulating, and displaying data using digitized maps. Its most distinguishing characteristic is that every record or digital object has an identified geographical location.

Reality mining allows analysts to extract information from the usage patterns of mobile phones and other wireless devices. Reality mining needs GIS and GPS data to work.

Students should provide examples. An example of a GIS is the online maps some cities provide citizens. These maps include information related to property ownership, flood plains, utility easements, etc. For reality mining, an example is providing real-time information on traffic congestion based on information collected via GPS from driver phones.

3. What is real-time BI, and why is this technology valuable to an organization’s managers and executives?

Real-time BI is designed to capture, store, and use real-time data. Real-time BI enables users to employ multidimensional analysis, data mining, and decision support systems to analyze data in real time. In addition, it helps organizations to make decisions and to interact with customers in new ways. It also influences how workers can be monitored and rewarded based on their performance.

Section 12.5 … Before you go on…

1. What is corporate performance management?

Corporate performance management (CPM) is involved with monitoring and managing an organization’s performance according to key performance indicators (KPIs) such as revenue, return on investment (ROI), overhead, and operational costs. For online businesses, CPM includes additional factors such as the number of page views, server load, network traffic, and transactions per second.

2. How do BI applications contribute to corporate performance management?

BI applications allow managers and analysts to analyze data to obtain valuable information and insights concerning the organization’s KPIs.

|“IT’s About Business” Questions |

IT’s About Business 12.1

Adelaide Brighton Cement

1. Provide specific examples of the advantages of the myDIALS package to Adelaide.

The company provided a hosted solution, which was low cost and reduced risk. It could also be implemented without overhauling Adelaide’s existing systems.

2. What were the reasons why Vince Aurora decided not to implement an ERP system? Was this an appropriate decision? Why or why not?

Aurora specifically needed a system to monitor safety throughout the plant he was responsible for. He determined an ERP system would be too costly and complicated to meet the needs of the company.

IT’s About Business 12.2

Data Analytics Helps Kelley Blue Book Remain Competitive

1. Provide specific examples of other revenue-generating applications that Kelley could develop from its data-mining application.

Students will suggest various ideas. One possibility is the best tire make/model for a particular car model. Projected repair costs based on model and area of car damaged are another option.

2. Analyze this case in terms of the three phases of the decision-making model (intelligence, design, and choice).

In the intelligence phase managers examine a situation and identify and define the problem or opportunity. In this case, the managers determined they needed a new strategy due to a decline in sales. They also determined that they were an information company. They decided to use data analytics to utilize those data more effectively. The first step was to update the company’s data management infrastructure.

In the design phase, decision makers construct a model for the situation. In this case, Kelley determined they could utilize data analytics to improve their existing services.

The choice phase involves selecting a solution or course of action that seems best suited to resolve the problem. Among other things, they discovered that by using the software to integrate third-party data, they could refine the estimates of car values estimates located on their Web site more quickly and accurately than previously.

IT’s About Business 12.3

North Carolina State University Uses Business Analytics to Monetize Intellectual Property

1. What advantages does the analytics software provide for the Office of Technology Transfer?

It was able to analyze large amounts of data in days that previously took months to go through. It also found unknown relationships that it might have been missed using the previous manual method.

2. Should the analytics software in the Office of Technology Transfer be used in other departments in the university? Why or why not? Support your answer.

Students may suggest various options, including:

Finding new directions for ongoing or previous research that had been set aside or discontinued

Finding new or previously unknown or exploited partnerships between researchers and industry.

The downside is the possible loss of central management of licensing opportunities.

IT’s About Business 12.4

1-800 CONTACTS

1. Interpret the phrase “that which gets watched, gets done.” Give an example from your personal life.

In the case of 1-800 CONTACTS, each operator and manager was able to view and track their and other’s performance based on a number of factors. They could also see what their rewards would be based on their or others’ efforts.

Students will have different personal examples.

2. Would you like to work in a job where your compensation is based on your performance relative to your coworkers? Discuss.

Students will have different opinions on this topic.

|Discussion Questions |

1. Your company is considering opening a new factory in China. List several typical activities involved in each phase of the decision (intelligence, design, and choice).

Each of the phases can be used to explain the approach of decision support systems (DSS).

• Intelligence Phase—the starting point where reality is examined and the problem is defined.

o Determine if opening a factory in China is consistent with organizational objectives.

o Conduct a search for relevant information about doing business in China.

o Collect and classify data according to the problem definition

o Develop a business problem statement

• Design Phase—design and construct a model

o Select a model according to the degree of abstraction required.

o Validate the model by way of experiments and analysis.

o Establish criteria for evaluating alternative solutions that are identified. (Attempt to forecast how a factory in China will resolve the business problem identified in the previous phase.)

o Generate alternative solutions to the problem (how best to conduct business with a factory in China).

• Choice Phase—selecting a solution to test “on paper.”

o Perform testing by experimenting with different “China business” scenarios.

o Select the best solution and generate criteria to test it. (Is doing business in China economically feasible?)

• Implementation Phase—implement the solution that is most economically feasible.

2. Recall that data mining found that young men tend to buy beer and diapers at the same time when they shop at a convenience store. Now that you know this relationship exists, can you provide a rationale for it?

Students will have their own opinions. One possible explanation is that their wife sent them out to get diapers and while they were there they opted to also buy something to drink.

3. American Can Company announced that it was interested in acquiring a company in the health maintenance organization (HMO) field. Two decisions were involved in this act: (1) the decision to acquire an HMO, and (2) the decision of which HMO to acquire. How can the company use BI to assist it in this endeavor?

Dashboards, expert systems and BI applications support upper management in company acquisition decisions by providing analyses based on the decision maker’s initial definition of the situation including managerial intuition and judgment. The DSS can utilize financial modeling and sensitivity analysis to evaluate multiple interdependent variables.

ES applications can be used to provide consistent expert analyses relevant to the acquisition and selection process. BI systems can help analyze the data and build models to understand the relationships among the variables so to be able to build a more comprehensive picture of the problem and the solution chosen.

Dashboards could be used to provide “drill down” capabilities to locate key information about HMOs under consideration. Drill down is important because it eliminates the need for intermediaries for consultation and analysis of the data. The Dashboard can also connect to online information services to seek additional intelligence from external sources.

4. Discuss the strategic benefits of BI systems.

These applications consolidate, analyze, and provide access to vast amounts of data to help users make better business decisions.

5. Will BI replace business analysts? (Hint: See W. McKnight, “Business Business Intelligence: Will Business Intelligence Replace the Business Analyst?” DMReview, February, 2005).

BI systems will never replace business analysts altogether. Rather, they will help analysts do a better job of analyzing all sorts of business data.

|Problem-Solving Activities |

Students will research and submit reports per instructions.

1. The city of London (U.K.) has an entrance fee for automobiles and trucks in the central city district. About 1,000 digital cameras photograph the license plate of every vehicle passing by. Computers read the plate numbers and match them against records in a database of cars for which the fee has been paid for that day. If a match is not found, the car owner receives a citation by mail. Examine the issues pertaining to how this process is accomplished, the mistakes that can be made, and the consequences of those mistakes. Also examine how well the system is working by checking press reports. Finally, relate the process to business intelligence.

The system tracks cars that enter the city. It can be used for many planning functions, parking, events, public transportation, etc.

2. Enter and visit the demos on the right side of the page. Prepare a report on the various features shown in each demo.

Encourage students to use the demos to illustrate how BI tools such as Cognos are integrated into the business processes of these companies.

3. Enter and find products for fraud detection and risk analysis. Prepare a report.

Students will prepare a list and report on these products.

4. Enter (TSN) (you will need a password), and find the paper titled “Data Warehousing Supports Corporate Strategy at First American Corporation” (by Watson, Wixom, and Goodhue). Read the paper and answer the following questions:

a. What were the drivers for the data warehouse/business intelligence project in the company?

b. What strategic advantages were realized?

c. What were the critical success factors for the project?

Advise students that they will need to create a login to access the paper.

5. Access index.php/talks/view/id/92 to find the video of Hans Rosling’s presentation. Comment on his data visualization techniques.

Rosling does a series of interesting presentations comparing population data in a visual format.

6. Enter . Explore the relationship between visualization and business intelligence. See how business intelligence is related to dashboards.

Visualization refers to data graphs and displaying data in a visual form, whereas BI refers to understanding the relationships and rules found in the data.

7. Access . Identify all types of business intelligence software. Join a discussion group about topics discussed in this chapter. Prepare a report.

Students can find BI tools that are suited to their academic major or their career interests.

8. Visit the sites of some GIS vendors (such as , , or ). Download a demo. What are some of the most important capabilities and applications?

Students can find tools that relate to their area of interest.

9. Analyze Microsoft Virtual Earth (virtualearth) as a business intelligence tool. (Hint: Access ). What are the business intelligence features of this product?

Visualization of data and mapping to specific geographic areas on the screen.

|Team Assignments |

Make team assignments and have student groups complete them per instructions.

1. Using data mining, it is possible not only to capture information that has been buried in distant courthouses but also to manipulate and index it. This process can benefit law enforcement but invade privacy. In 1996, Lexis-Nexis, the online information service, was accused of permitting access to sensitive information on individuals. The company argued that it was unfairly targeted because it provided only basic residential data for lawyers and law enforcement personnel. Should Lexis-Nexis be prohibited from allowing access to such information? Debate the issue.

Students should research and present their arguments.

2. Use Google to find combined GIS/GPS applications. Also, look at various vendor sites to find success stories. For GPS vendors, look at (directory) and Google. Each group will make a presentation of five applications and their benefits.

Each group will access a leading business intelligence vendor’s Web site (e.g., MicroStrategy, Oracle, Hyperion, Microsoft, SAS, SPSS, Cognos, Applix, Business Objects). Each group will present a report on the vendor they have selected, noting its BI capabilities.

|Closing Case |

Operational Business Intelligence Means Better Pizza at Papa Gino’s

The Business Problem

Papa Gino’s (), the Dedham, Massachusetts, restaurant operator, generates massive amounts of data in its daily operations. The data include everything from statistics on how long it takes customers to receive pizza deliveries to how well restaurants stack up against local competition. Until May 2007, business managers gathered data via e-mail each day from a variety of sources. The process was difficult and time-consuming as district managers, who are typically responsible for 8 to 12 restaurants, accumulated data and passed it on to regional vice presidents for further analysis.

In mid-2007, Papa Gino’s was in the middle of a strategic five-year project to optimize its information technology systems and applications throughout the organization. The goal was to improve the performance of its restaurants. The company wanted to more effectively leverage the large amounts of data being gathered in a variety of systems, including the J.D. Edwards enterprise resource-planning applications; internally developed, in-store point-of-sale systems; and Excel spreadsheets.

The overall business and many of the individual restaurants were performing satisfactorily when Papa Gino’s used the old process of data analysis. However, executives wanted to improve the process, save time, and tap into the wealth of information more effectively in order to generate additional improvements.

The IT Solution

To accomplish these goals, Papa Gino’s deployed operational business intelligence (BI) software. Operational business intelligence is the process of using business intelligence to drive and optimize business operations and decision making on a daily basis or sometimes several times per day. The operational BI software at Papa Gino’s placed reporting and analytics applications in the hands of business users who could analyze information to identify strategies for working more efficiently and improving results. In all, some 100 managers at Papa Gino’s use the BI application.

Papa Gino’s deployed the operational BI software in three phases. In the first phase, business users acquired the reporting tools and the information they wanted. In the second phase, this information was reduced to 10 to 20 metrics deemed vital to the business. (Users had the option to look at other metrics as needed.) Finally, in the third phase, managers used the technology to report and manage by exception. In other words, they examined key metrics for conditions that fell outside pre-established ranges.

The Results

Papa Gino’s managers now receive data much more quickly. It is generally available to all key decision makers in the organization by 6:30 every morning.

With the software, Papa Gino’s managers use dashboards to quickly analyze financial data, such as revenue, at individual restaurants by week, month, or year. They then compare the revenue data with similar data from the same restaurant in previous periods, with revenue goals set by management, and with revenue at other restaurants in the same region or state. The system also reports and analyzes operational data—such as how many customers visit a restaurant during various times, what types of menu items customers are ordering, and how many hours employees are logging—so managers can see how each restaurant is performing.

With the manage-by-exception strategy, decision makers look only at data that are outside certain thresholds or percentages—both in a positive and negative direction. For example, if a restaurant’s average total of daily guests falls below a certain threshold, managers are alerted to the anomaly. In the same way, managers are made aware of restaurants that have a higher-than- expected number of guests.

Food delivery accounts for about one-third of Papa Gino’s business, so a key statistic is percentages of on-time deliveries. Managers look at the delivery times promised to customers and analyze how well the restaurants are meeting that promise.

Another major contributor to the business is phone-ahead orders, so other key statistics include how quickly order takers at restaurants answer the phone, how many calls are abandoned by customers, and how many callers receive busy signals when they dial the restaurants. Papa Gino’s claims that the industry standard is to have 85 percent of calls answered within 12 seconds. By analyzing calling data, managers can determine whether there are enough people answering the phones.

One of the tangible benefits of the BI system is that operations and finance managers now spend more time analyzing data trends and less time collecting data. Another benefit is that managers can use the forecasting capabilities of the BI application to get a better idea of how much product they should order and how many workers they should schedule, which improves the overall efficiency of operations.

As for performance improvements, Papa Gino’s has seen gains such as a higher percentage of on-time deliveries since it deployed the operational BI system. The company is using the system as a tool to refine and improve the restaurant experience and increase customer satisfaction.

Questions

1. Describe the various benefits that Papa Gino’s is seeing from its operational business intelligence system.

Using the BI system, Papa Gino’s is able to run several processes more efficiently. They collect data from their stores much faster and use the data in their daily decision making. They use manage-by-exception strategy to look at data that falls outside of the norm, which makes their data analysis much easier. They also make better decisions on their food delivery decisions that account for one third of their costs. They also look at phone order wait times and see if they need to be adjusted when calls are being abandoned due to longer waits. The BI has made a great impact on Papa Gino’s business.

2. Discuss additional analyses that Papa Gino’s managers and analysts could run that would benefit the company and its restaurants and provide competitive advantage.

One of the advantages of the BI system is that operations and finance managers now spend more time analyzing data trends and less time collecting data. Another benefit is that managers can use the forecasting capabilities of the BI application to get a better idea of how much product they should order and how many workers they should schedule, which improves the overall efficiency of operations. Likewise, they can use the data to understand which products are more popular and what the profiles of their customers are. This will help in business planning and operations.

|CHAPTER GLOSSARY |

business intelligence: A broad category of applications, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make better decisions.

corporate performance management: The area of business intelligence involved with monitoring and managing an organization’s performance, according to key performance indicators (KPIs) such as revenue, return on investment (ROI), overhead, and operational costs.

Dashboard: A BI application that provides rapid access to timely information and direct access to management reports.

data mining: The process of searching for valuable business information in a large database, data warehouse, or data mart.

decision: A choice among two or more alternatives that individuals and groups make.

decision support systems (DSS): Business intelligence systems that combine models and data. in an attempt to solve semistructured and some unstructured problems with extensive user involvement.

geographic information system: A computer-based system for capturing, integrating, manipulating, and displaying data using digitized maps.

independent data mart: A data mart that is independent of other data marts and warehouses.

management: A process by which organizational goals are achieved through the use of resources.

model (in decision making): A simplified representation, or abstraction, of reality.

online analytical processing (OLAP) (or multidimensional data analysis): A set of capabilities for “slicing and dicing” data using dimensions and measures associated with the data.

productivity: The ratio between the inputs to a process and the outputs from that process.

reality mining: Allows analysts to extract information from the usage patterns of mobile phones and other wireless devices

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