CHAPTER 12 "Enhancing Decision Making"
12.1 Decision Making and Information Systems
Decision making in businesses used to be limited to management. Today,
lower-level employees are responsible for some of these decisions, as
information systems make information available to lower levels of the business.
Business Value of Improved Decision Making
The firm has identified a number of key decisions where new system
investments might improve the quality of decision making. Although the value of
improving any single decision may be small, improving hundreds of thousands of
“small” decisions adds up to a large annual value for the business.
Types of Decisions
Decisions are classified as structured, semistructured, and
unstructured. Unstructured decisions are those in which the decision maker must provide judgment,
evaluation, and insight to solve the problem. Structured decisions,
by contrast, are repetitive and routine, and they involve a definite procedure
for handling them so that they do not have to be treated each time as if they
were new. Many decisions have elements of both types of decisions and are semistructured, where
only part of the problem has a clear-cut answer provided by an accepted
procedure.
Senior executives face many unstructured decision situations. Middle
management faces more structured decision scenarios but their decisions may
include unstructured components. Operational management and rank-and-file
employees tend to make more structured decisions.
The Decision-Making Process
Making a decision is a multistep process. Simon (1960) described
four different stages in decision making:
- Intelligence consists of discovering, identifying, and understanding the problems occurring in the organization.
- Design involves identifying and exploring various solutions to the problem.
- Choice consists of choosing among solution alternatives.
- Implementation involves making the chosen alternative work and continuing to monitor how well the solution is working.
Managers and Decision Making in The Real World
Managerial Roles
The classical model of
management, which describes what managers
do, was largely unquestioned for the more than 70 years since the 1920s. Behavioral models
state that the actual behavior of managers appears to be less systematic, more informal,
less reflective, more reactive, and less well organized than the classical
model would have us believe. Managerial
roles are expectations of the activities
that managers should perform in an organization. Mintzberg found that these
managerial roles fell into three categories: interpersonal, informational, and
decisional.
Real-World Decision Making
In those managerial roles where information systems might improve decisions,
investments in information technology do not always produce positive results.
There are three main reasons: information quality, management filters, and
organizational culture
High-Velocity Automated Decision Making
Today, many decisions made by organizations are not made by managers,
or any humans. The class of decisions that are highly structured and automated
is growing rapidly. What makes this kind of automated high-speed decision
making possible are computer algorithms that precisely define the steps to be
followed to produce a decision, very large databases, very high-speed
processors, and software optimized to the task. In these situations, humans
(including managers) are eliminated from the decision chain because they are
too slow.
12.2 Business Intelligence in The Enterprise
At the foundation of all of these decision support systems are
business intelligence and business analytics infrastructure that supplies the
data and the analytic tools for supporting decision making.
What Is Business Intelligence?
“Business intelligence” is a term used by hardware and software
vendors and information technology consultants to describe the infrastructure
for warehousing, integrating, reporting, and analyzing data that comes from the
business environment. “Business analytics” is also a vendor-defined term that
focuses more on tools and techniques for analyzing and understanding data.
Think online analytical processing (OLAP), statistics, models, and data mining.
So, stripped to its essentials, business intelligence and
analytics are about integrating all the information streams produced by a firm
into a single, coherent enterprise-wide set of data, and then, using modeling,
statistical analysis tools, and data mining tools, to make sense out of all
these data so managers can make better decisions and better plans, or at least
know quickly when their firms are failing to meet planned targets.
The Business Intelligence Environment
There are six elements in this business intelligence environment:
- Data from the business environment
- Business intelligence infrastructure
- Business analytics toolset
- Managerial users and methods
- Delivery platform—MIS, DSS, ESS
- User interface
Business Intelligence and Analytics Capabilities
There are 5 analytic functionalities that BI systems deliver to
achieve these ends:
- Production reports
- Parameterized reports
- Dashboards/scorecards
- Ad hoc query/search/report creation
- Drill down
- Forecasts, scenarios, models
Who Uses Business Intelligence and Business Analytics?
Over 80 percent of the audience for BI consists of casual users who
rely largely on production reports. Senior executives tend use BI to monitor
firm activities using visual interfaces like dashboards and scorecards. Middle
managers and analysts are much more likely to be immersed in the data and
software, entering queries and slicing and dicing the data along different dimensions.
Operational employees will, along with customers and suppliers, be looking
mostly at prepackaged reports.
Predictive Analytics
Predictive analytics are being built into mainstream applications
for everyday decision making by all types of employees, especially in finance
and marketing. Predictive analytics have also worked especially well in the
credit card industry to identify customers who are at risk for leaving.
Data Visualization and Geographic Information Systems
Data
visualization tools help users see patterns
and relationships in large amounts of data that would be difficult to discern
if the data were presented as traditional lists of text.
Geographic information systems (GIS) help decision makers visualize problems requiring knowledge about
the geographic distribution of people or other resources.
Management Strategies for Developing BI and BA Capabilities
There are two different strategies for adopting BI and BA
capabilities for the organization: one-stop integrated solutions versus
multiple best-of-breed vendor solutions.
Regardless of which strategy your firm adopts, all BI and BA
systems lock the firm into a set of vendors and switching is very costly. Once
you train thousands of employees across the world on using a particular set of
tools, it is extremely difficult to switch. When you adopt these systems, you
are in essence taking in a new partner. As a manager, you will have to critically
evaluate such claims, understand exactly how these systems could improve your
business, and determine whether the expenditures are worth the benefits.
12.3 Business Intelligence Constituencies
There are many different constituencies that make up a modern
business firm.
Decision Support for Operational and Middle Management
Operational and middle management are generally charged with
monitoring the performance of key aspects of the business.
Support for Semistructured Decisions
Some managers are “super users” and keen business analysts who
want to create their own reports, and use more sophisticated analytics and
models to find patterns in data, to model alternative business scenarios, or to
test specific hypotheses. Decision support systems (DSS) are the BI delivery
platform for this category of users, with the ability to support semi-structured
decision making. Sensitivity analysis models ask what-if questions repeatedly to predict a range of
outcomes when one or more variables are changed multiple times
Decision Support for Senior Management: The Balanced Scorecard and Enterprise Performance Management Methods
The purpose of executive support systems (ESS) is to help C-level
executive managers focus on the really important performance information that affect
the overall profitability and success of the firm. There are two parts to
developing ESS. First, you will need a methodology for understanding exactly
what is “the really important performance information” for a specific firm that
executives need, and second, you will need to develop systems capable of
delivering this information to the right people in a timely fashion. Currently,
the leading methodology for understanding the really important information
needed by a firm’s executives is called the balanced scorecard
method
Performance on each dimension is measured using key performance indicators (KPIs), which are the measures proposed by senior management for understanding how well the
firm is performing along any given dimension. Another closely related popular
management methodology is business performance
management (BPM). Originally defined by an
industry group in 2004, BPM attempts to systematically translate a firm’s strategies into operational targets.
Group Decision-Support Systems (GDSS)
The DSS we have just described focus primarily on individual
decision making. However, so much work is accomplished in groups within firms
that a special category of systems called group decision-support systems (GDSS) has been developed to support group and organizational decision
making. A GDSS is an interactive computer-based system for facilitating the
solution of unstructured problems by a set of decision makers working together
as a group in the same location or in different locations.
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source: "Management Information System" e-book, 12th edition, written by Kenneth C. Laudon and Jane P. Laudon.