America's cup the tension between technology and human decision makers

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Chapter 12 Enhancing Decision Making

“Companies have been able to use technology to do some very cool stuff to reach

customers in new ways, to automate operations. But one thing many businesses haven’t

been able to do easily is use the data they’ve collected to find and stamp out waste across

operations. Sifting through corporate data was supposed to make executives more

efficient. Much of the time, though, it’s just made them more confused.” (Fortune, March

3, 2002)

Even though this quote is ten years old, it’s still pertinent in many companies. We’re

getting better though about turning raw data into useful information that helps improve

decision making.

12.1 What are the different types of decisions and how does the

decision-making process work? How do information systems

support the activities of managers and management decision

making?

Each of us makes hundreds of decisions every day. If just a fraction of those

decisions could be improved through better and more information and better

processes, we’d all be delighted. Businesses feel the same way. Customers would

be happier, employees would be more motivated, and managers would have an

easier job. Most of all, businesses could improve their profitability to the benefit

of all.

Business Value of Improved Decision Making

Table 12.1 provides a few examples of the dollar value that enhanced decision making

would give to firms.

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Don’t be misled into thinking that the dollar value of improving decision-making

processes is limited to managers. As more business flatten their organizational structures

and push decision making to lower levels, better decisions at all levels can lead to

increased business value.

Types of Decisions

There are generally three classifications of decisions:

 Unstructured: Requires judgment, evaluation, and insight into nonroutine

situations. Usually made at senior levels of management.

 Structured: Repetitive, routine, with definite procedures for making the decision.

Usually made at the lowest organizational levels.

 Semistructured: A combination of the two. Usually made by middle managers.

Figure 12.1 couples these three types of decisions with the appropriate management level.

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Figure 12.1 Information Requirements of Key Decision-Making Groups in a Firm

 Senior management: Makes decisions based on internal business information but

also external industry and society changes; decisions affect long-term, strategic goals

and the firm’s objectives.

 Middle management and project teams: Decisions affect resource allocation, short-

range plans, and performance of specific departments, task forces, teams, and special

project groups.

 Operational management and project teams: Decisions affect subunits and

individual employees regarding the resources, schedules, and personnel decisions for

specific projects.

 Individual employees: Decisions affect specific vendors, other employees, and most

importantly, the customer.

The Decision-Making Process

Making decisions requires four steps:

 Intelligence: Discovering, identifying, and understanding problems.

 Design: Identifying and exploring solutions to problems.

 Choice: Choosing among solution alternatives.

 Implementation: Making the chosen alternative work and monitoring how well

the solution is working.

These four steps are not always consecutive and may well be concurrent or repetitive.

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Managers and Decision Making in the Real World

Although information systems have gone a long way toward improving the decision-

making process, they are not the Holy Grail. They should be viewed as a way to assist

managers in making decisions, but not as the final answer.

Managerial Roles

Let’s compare the classical model of management with the behavioral model. The

former describes the five classical functions of managers as:

 Planning

 Organizing

 Coordinating

 Deciding

 Controlling

Behavioral models of managers dissect the many activities involved in the five functions

of management. That is, managers:

 Perform a great deal of work at an unrelenting pace.

 Activities are fragmented.

 Prefer current, specific, and ad hoc information.

 Prefer oral communications rather than written documentation.

 Maintain a diverse and complex web of contacts.

Now, let’s take all of these activities and categorize them into three managerial roles:

 Interpersonal: Act as figureheads, leaders, and liaisons.

 Informational: Act as nerve centers, disseminators, and spokespersons.

 Decisional: Act as entrepreneurs, handle disturbances, allocate resources,

negotiate and mediate conflicts.

Table 12.2 shows that supporting information systems exist for only some of the

managerial behaviors but not all of them.

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Table 12.2 Managerial Roles and Supporting Information Systems

Real World Decision Making

Because you have no doubt had to make decisions in the real world, you know for a fact

that the process is not as cut-and-dried as what we’ve reviewed so far. Three reasons why

the whole process can blow up without a moment’s notice:

 Information Quality: Was the information used to make the decision accurate,

consistent, complete, valid, timely, accessible, and of high integrity? What if you

were making a decision about purchasing a house and found out that there were errors

in your credit record that prevented you from obtaining the necessary financing?

Perhaps the data was out of date or contained mistakes.

 Management Filters: Everyone processes information through personal filters and

biases. Managers are no different. For instance, you may suggest to your manager that

the department purchase a piece of equipment from a certain manufacturer. Your

manager disapproves the suggestion because he had a bad experience with that

company ten years ago. The manager’s bias negates the fact that the company has

since improved and is the best and cheapest choice.

 Organizational Inertia and Politics: People hate change and will sometimes do

whatever they can to keep the status quo. Decision makers are no different especially

if they stand to lose. What if your department will benefit from improving its business

processes to the benefit of all concerned except that the manager will lose her job? It’s

likely the manager will not make decisions that will cause her to lose her job.

Therefore, nothing gets done regarding improving processes.

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High-Velocity Automated Decision Making

What if your friend asked you to find a copy of the lyrics to the Beatles hit song “Hey

Jude?” How long do you think it would take you if Internet-based search processes were

not available? Days? Weeks? A Google search for the information takes less than five

seconds. That’s the power of high-velocity automated decision making in today’s world.

Humans simply can’t match a computer’s speed and accuracy for making some decisions.

Computer programmers use the same four step decision-making process we’ve discussed

before when they create algorithms that help make these kinds of lightning-fast decisions:

identify the problem, design a method for finding a solution, define a range of acceptable

solutions, and implement the solution. They just have to be careful that the algorithms are

written correctly to ensure proper decisions are made by computers or you may end up

getting a profile of Jude Law, the actor.

Earlier we mentioned a class of decisions that are routine, very structured, and have

definite procedures for determining the solution. In these situations, why not automate the

process and have a computer make the decision much faster than a human can?

Computers have these positive characteristics that make them ideal for high-velocity

automated decision making:

 Computer algorithms that precisely define the steps to be followed

 Very large databases

 Very high-speed processors

 Software optimized to the task

The algorithms are structured to follow the intelligence, design, choice, and

implementation steps we discussed as part of the decision-making process. But, just in

case, the information systems used to process these kinds of decisions should be

monitored and regulated by humans.

Bottom Line: Everyone makes decisions at all levels of an organization. The goal is

to match the four decision-making organizational levels along with the three types of

decisions to the appropriate kind of decision support system. It’s important to

understand the roles and activities associated with management decision making

and that information systems can only assist in the process.

12.2 How do business intelligence and business analytics

support decision making?

Business intelligence and business analytics provide managers with a systematic way of

making sense of the vast amounts of data collected on customers, suppliers, employees,

business partners, and the external business environment.

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What Is Business Intelligence?

All of us collect information from our surroundings, try to understand it, and then act on

it in an intelligent way. Businesses are no different other than the fact that they have much

more data to collect, process, store, and disseminate.

A whole new industry has sprung up that helps businesses create an infrastructure to

warehouse, integrate, report, and analyze data. This is where the databases, data

warehouses, data marts, analytic platforms, and Hadoop that we discussed in previous

chapters come back into the picture. Business intelligence describes how businesses

collect, store, clean, and disseminate useful information to executives, managers, and

employees.

Business analytics, on the other hand, are the tools and techniques businesses use to

analyze and understand the data in a meaningful way. It’s one thing to read a report that

says sales are 10 percent ahead of last year. Business analytic tools, such as data mining,

statistics, online analytical processing, and models help managers understand that part of

the cause is an increased focus on marketing to middle-aged women with two children.

Business Intelligence Vendors

The top five vendors of BI and BA hardware and software include well-known

technology companies: Oracle, SAP, IBM, Microsoft, and SAS. These vendors are

primarily the same ones that we’ve discussed before when we reviewed enterprise

systems. Perhaps the most interesting aspect of BI and BA hardware and software suites

is that it’s the fastest-growing and largest segments in the U.S. software market. That

demonstrates just how hungry businesses are to make sense of all the data they have

available to them.

The Business Intelligence Environment

Let’s review six hardware, software, and management capabilities that are included in the

business intelligence environment:

 Data from the business environment: Integrating and organizing structured and

unstructured data from different sources that people can analyze and use.

 Business intelligence infrastructure: Database systems that process relevant

data stored in transactional databases, data warehouses, or data marts.

 Business analytics toolset: Software tools that managers use to analyze data,

produce reports, respond to questions, and track their progress using key

performance indicators (KPI).

 Managerial users and methods: Business performance management and

balanced scorecard methods that help managers focus on key performance

indicators and industry strategic analyses. Requires strong executive oversight to

ensure managers are focusing on the right issues and not just producing reports

and dashboard screens because they can.

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 Delivery platform—MIS, DSS, and ESS: All the information from MIS, DSS,

and ESS are integrated and delivered to the appropriate level of management.

 User interface: BI and BA systems make it easy to visually display data, thereby

making it easy to quickly understand information on a variety of computing

devices.

Figure 12.3 helps you understand how these six elements work together in business

intelligence and business analytics systems.

Figure 12.3 Business Intelligence and Analytics for Decision Support

Business Intelligence and Analytics Capabilities

The days of receiving static reports that are out of date—meaning more than 30 days or

even 30 minutes old—containing data that are meaningless are over. Business

intelligence systems help correct that situation in five different ways:

 Production reports: Predefined reports based on industry specific requirements.

 Parameterized reports: Pivot tables help users filter data and isolate impacts of

parameters chosen by users.

 Dashboards/scorecards: Visual reports that present performance data chosen by

users.

 Ad hoc query/search/report creation: Users create their own reports based on

data they choose.

 Drill down: Users initially receive high-level data summaries and then drill down

to more specific data.

 Forecasts, scenarios, models: User can perform linear forecasting, what-if

scenario analysis, and analyze data using standard statistical tools.

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Who Uses Business Intelligence and Business Analytics?

The audience for business intelligence and business analytic tools and techniques has

unique characteristics depending on their management level and how they use the

systems:

 Casual users: Rely largely on production reports.

 Senior executives: Monitor organization activities using dashboards and

scorecards.

 Middle managers and analysts: Enter queries; slice and dice data along different

dimensions.

 Operational employees, customers, suppliers: Mostly use prepackaged reports.

Figure 12.4 tells you how each division of the business intelligence audience uses the

capabilities of these systems.

Figure 12.4 Business Intelligence Users

Production Reports

Because 80 percent of the people who access business intelligence systems are casual

users, most vendors create a mass of predefined production reports based on industry

standards and best practices. Table 12.4 gives you an idea of the types of reports produced

for each business functional area.

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Table 12.4 Examples of Business Intelligence Predefined Production Reports

Predictive Analytics

Most times, customer behavior is very predictable if you’re looking at and understanding

the right data. Companies use business analytic software to figure out ahead of time how

reliable certain customers are regarding credit extensions, how customers will respond to

changes in prices or services, or how successful new sales locations will be. Those are the

kinds of questions predictive analytics can answer more quickly and more easily than

humans. Predictive analytics helps managers ask and answer the right questions to make

their company more successful.

Over the last few years, many retailers have drastically reduced the number of catalogs

they send in snail mail to potential customers. With rising postal fees and many people

using the Internet to make purchases, fewer and fewer of them are waiting for the catalog

in the mail. By using predictive analytics, companies can weed out people who are

unlikely to make catalog purchases and concentrate on those who will. That decreases

marketing costs while increasing the ratio of catalogs to purchasing customers.

Big Data Analytics

You’re shopping on a major retailer’s Web site when, all of a sudden, you see a sweater

that you simply can’t live without. Alongside the sweater’s display are pictures of a pair

of pants or skirt that, combined, will make the perfect outfit. The pants and skirt are

labeled, “You might also like…” or “What other customers purchased when they

purchased this sweater….”

Those extra items weren’t put there by chance but more as a result of big data analytics

that we discussed in earlier chapters. Rather than requiring you to thumb through pages

and pages of skirts and pants, the retailer will do it for you and, in the meantime, increase

the chances of making an extra sale. Those recommendations likely are a result of what

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other customers purchased. The retailer captures all of its sales data, analyzes it, and

includes data from social media streams to create the customized recommendations.

Interactive Session: Technology: Big Data Make Cities Smarter (see page 480 of the

text) describes how two major cities are using vast amounts of data to improve

services for citizens and make city agencies more efficient.

Operational Intelligence and Analytics

Businesses are collecting millions of pieces of data on a constant basis from sensors,

gauges, monitoring devices, and other technologies. The trick is to make good use of the

data and turn it into information that employees and managers can use to make better

decisions at the operational level of an organization.

Operational intelligence and analytics software gives organizations the ability to analyze

all of the big data as they are generated in real time. The data can feed dashboards for

employees or managers and give them a heads-up about ongoing, real time operations.

Interactive Session: Management: America’s Cup: The Tension Between

Technology and Human Decision Makers (see page 483 of the text) describes how

Team USA used big data in real-time operation intelligence mode to win the 2013

America’s Cup sailboat race. Ultimately, it was a balancing act between technology-

driven decisions and human decision makers.

Location Analytics and Geographic Information Systems (GIS)

Many executive decisions depend on the availability of information, internal and external.

For instance, a company that ships most of its products on trucks needs data about

interstate highway access and traffic patterns to help control shipping costs and make it

easier for drivers to access its warehouses. Some company policies limit business

locations to high-traffic areas such as malls and similar densely populated areas. Other

executive decisions revolve around data about current and potential customers and their

geographic location.

Location analytics enable companies to gain insight from the location component of

data, including data from mobile phones, wireless sensors, scanning devices, location-

based cameras, and maps. The data may help businesses solve problems, attract more

customers, or improve services.

Geographic information systems (GIS) rely heavily on demographic data from the U.S.

Census Bureau. This type of decision-support system helps managers visualize

geographic information more easily and make better decisions based on digitized maps.

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GIS data can be coupled with an organization’s internal data to better allocate resources,

money, people, time, and material.

Management Strategies for Developing BI and BA Capabilities

Is it better to select a one-stop integrated solution for your organization’s business

intelligence and business analytics systems or should you adopt a multiple best-of-breed

vendor solution? Be aware that your decision carries risks and rewards either way.

Single vendor: The risk is that your company becomes dependent on the vendor’s pricing

power. The reward is that a single vendor promises hardware and software that will work

together “out of the box.”

Multiple vendors: The reward is that you’ll have greater flexibility and independence in

selecting your hardware and software. The risk is that you’ll suffer compatibility issues,

not just between the BI hardware and software but with your other systems as well.

You are locked into your decision and the switching costs are extremely high regardless

of which way you decide to go.

As a manager you must:

 Critically evaluate vendor claims

 Understand exactly how the systems will improve your business

 Determine if the expenditures are worth the benefits.

Bottom Line: Business intelligence and business analytics hardware and software

systems help businesses warehouse, integrate, report, and analyze data from the

firm’s internal and external environment. BI and BA systems provide employees,

managers, and executives with a wide variety of tools and techniques that help them

make sense of all the data and ultimately make better decisions. Each business must

decide whether a single vendor or multiple vendors will provide the better system.

12.3 How do difference decision-making constituencies in an

organization use business intelligence? What is the role of

information systems in helping people working in a group make

decisions more efficiently?

At the beginning of this chapter we outlined the types of decisions made at each

managerial level—structured, semistructured, and unstructured. We also mentioned that

each management level has different information needs that match the type of decisions

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made at that level. Let’s look at the types of information systems that match the

information needs.

Decision Support for Operational and Middle Management

For the most part, operational managers get their information from transaction processing

systems. But, more and more, they are accessing management information systems (MIS)

for a broader look at their company’s performance. Middle management also relies on

MIS systems for the bulk of their information.

Here are the characteristics of a typical MIS system:

 Used for structured and semistructured decisions

 Reports based on routine flows of data

 Provide general control of the organization

 Routine production reports are the primary output

 Exception reports are available

Support for Semistructured Decisions

Decision support systems help executives make better decisions by using historical and

current data from internal information systems and external sources of data. By

combining massive amounts of data with sophisticated analytical models and tools, and

by making the system easy-to-use, they provide a much better source of information to

use in the decision-making process.

Because of the limitations of hardware and software, early DSS systems provided

executives only limited help. With the increased power of computer hardware, and the

sophisticated software available today, DSS can crunch lots more data, in less time, in

greater detail, with easy-to-use interfaces. The more detailed data and information

executives have to work with, the better their decisions can be.

The “what-if” decisions most commonly made by executives use sensitivity analysis

models to help them predict what effect the decisions will have on the organization.

Executives don’t make decisions based solely on intuition. The more information they

have, the more they experiment with different outcomes in a safe mode, the better their

decisions. That’s the benefit of the models used in the software tools.

Common spreadsheet software such as Microsoft’s Excel helps managers review data in

two dimensions rather than just one by using pivot tables. They can decipher patterns in

information and help them allocate resources better. Managers using pivot tables can

develop better strategies because they’ll gain a better sense of correlating data points.

Figure 12.6 shows you a typical screen used in a Microsoft Excel pivot table.

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Figure 12.6 A Pivot Table That Examines Customer Regional Distribution and

Advertising Source

Decision Support for Senior Management: Balanced Scorecard and Enterprise Performance Management Methods

Executive support systems (ESS) are used primarily by senior management whose

decisions are usually never structured and could be described as “educated guesses.”

Executives rely as much, if not more, on external data than they do on data internal to

their organization. Decisions must be made in the context of the world outside the

organization. The problems and situations senior executives face are very fluid, so the

system must be flexible and easy to manipulate.

Executive support systems don’t provide executives with ready-made decisions. They

provide the information that helps them make their decisions. Executives use that

information, along with their experience, knowledge, education, and understanding of the

corporation and the business environment as a whole, to make their decisions.

Using a balanced scorecard method, executives combine their company’s internal

financial information with additional perspectives such as customers, internal business

processes, and learning and growth. By focusing on key performance indicators (KPIs)

in each of these areas, executives gain a better understanding of how the organization is

performing overall. After senior management establishes KPIs for each area, then and

only then can the flow of information be established. Figure 12.7 depicts the framework

for a balanced scorecard.

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Figure 12.7 The Balanced Scorecard Framework

Business performance management (BPM) is yet another tool for executives to

systematically translate the strategy they’ve developed for their company into operational

targets. BPM methods use KPIs to help users measure the organization’s progress toward

the targets. BPM is similar to the balanced scorecard approach but with a stronger

strategic viewpoint than an operational viewpoint.

Executives often face information overload and must be able to separate the chaff from

the wheat in order to make the right decision. On the other hand, if the information they

have is not detailed enough, they may not be able to make the best decision. An ESS can

supply the summarized information executives need and yet provide the opportunity to

drill down to more detail if necessary.

As technology advances, ESS are able to link data from various sources, both internal and

external, to provide the amount and kind of information executives find useful. As

common software programs include more options and executives gain experience using

these programs, they’re turning to them as an easy way to manipulate information.

Because of the trend toward flatter organizations with fewer layers of management,

companies are employing ESS at lower levels of the organization. Flatter organizations

also require managers to access more information about a wider range of activities than in

the past. This requirement can be accomplished with the aid of a good ESS. Executives

can also monitor the performance of their own areas and of the company as a whole.

Group Decision-Support Systems (GDSS)

More and more, companies are turning to groups and teams to get work done. Hours upon

hours are spent in meetings, in group collaboration, in communicating with many people.

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To help groups make decisions, a new category of systems was developed: the group

decision-support system (GDSS).

You’ve been there—a meeting where nothing seems to get done, where some people

dominate the agenda and others never say a word, and it dragged on for hours. When it

was all over no one was sure what was accomplished, if anything. But the doughnuts and

coffee were good! Organizations have been struggling with this problem for years. They

are now using GDSS as a way to increase the efficiency and effectiveness of meetings.

In GDSS, the hardware includes more than just computers and peripheral equipment. It

also includes the conference facilities, audiovisual equipment, and networking equipment

that connect everyone. More sophisticated GDSS require meeting facilitators and other

staff that keep the hardware operating correctly. Many companies are bypassing specially

equipped rooms in favor of having group participants “attend” the meeting through their

individual desktop computers.

Now instead of wasting time in meetings, people will know ahead of time what is on the

agenda. All of the information generated during the meeting is maintained for future use

and reference. Because input is anonymous, ideas are evaluated on their own merit. And

for geographically separated attendees, travel time and dollars are saved.

GDSS are best used for tasks involving:

 Idea generation

 Complex problems

 Large groups

Bottom Line: Executive support systems meet the needs of corporate executives by

providing them with vast amounts of information quickly and in graphic form to

help them make effective decisions. ESS must be flexible, easy-to-use, and contain

both internal and external sources of information. The balanced scorecard method

expands the view of the organization to include four dimensions: financial, business

process, customer, and learning and growth. Group decision-support systems,

comprised of hardware, software, and people, help streamline group meetings and

communications by removing obstacles and using technology to increase the

effectiveness of decisions.