CHAPTER 12: Managerial Support Systems
Chapter Outline
12.1
12.2
12.3
12.4
12.5
Managers and Decision Making
What Is Business Intelligence?
Business Intelligence Applications for Data Analysis
Business Intelligence Applications for Presenting Results
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 (www.gartner.com), 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 ecommerce 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.
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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
Amazon.com and the amount of information that they are able to collect on a single individual.
What data does Amazon.com collect from users? At minimum, the following information:
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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 Amazon.com
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.
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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:
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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
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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, semistructured, 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
“Ratemyprofessor.com” 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
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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.
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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?
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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.
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“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?
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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
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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.
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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 www.cognos.com 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 www.fairisaac.com and find products for fraud detection and risk analysis. Prepare a
report.
Students will prepare a list and report on these products.
4. Enter www.teradatastudentnetwork.com (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.
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5. Access www.ted.com/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 www.visualmining.com. 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 http://businessintelligence.ittoolbox.com. 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 www.mapinfo.com, www.esri.com, or
www.autodesk.com). 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 (www.microsoft.com/virtualearth) as a business
intelligence tool. (Hint: Access
http://www.microsoft.com/Industry/government/solutions/virtual_earth/demo/ps_gbi.html).
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.
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2. Use Google to find combined GIS/GPS applications. Also, look at various vendor sites to
find success stories. For GPS vendors, look at http://biz.yahoo.com (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 (www.papaginos.com), 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
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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-thanexpected 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.
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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.
Chapter 12: Managerial Support Systems (4th edition)
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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