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Q7 What Is the Role of Knowledge Management Systems? 367

employees to solve problems more quickly and to otherwise accomplish work with less time
and other resources, hence improving process efficiency. 16
Additionally, recall from Chapter 2 that successful teams not only accomplish their as-
signed tasks, they also grow in capability, both as a team and as individuals. By sharing knowl-
edge, team members learn from one another, avoid making repetitive mistakes, and grow as
business professionals.
For example, consider the help desk at any organization, say, one that provides support
for electronic components like iPhones. When a user has a problem with an iPhone, he or she
might contact Apple support for help. The customer service department has, collectively, seen
just about any problem that can ever occur with an iPhone. The organization, as a whole, knows
how to solve the user’s problem. However, that is no guarantee that a particular support repre-
sentative knows how to solve that problem. The goal of KM is to enable employees to be able to
use knowledge possessed collectively by people in the organization. By doing so, both process
quality and team capability improve.
What Are Expert Systems?

The earliest KM systems, called expert systems, attempted to directly capture employee exper-
tise. They existed long before social media and in fact were in use long before the Internet.
Expert systems are rule-based systems that encode human knowledge in the form of If/
Then rules. Such rules are statements that specify if a particular condition exists, then to take
some action. Figure 9-25 shows an example of a few rules that could be part of a medical expert
system for diagnosing heart disease. In this set of rules, the system examines various factors for
heart disease and computes a CardiacRiskFactor. Depending on the value of that risk factor,
other variables are given values.
The set of rules shown here may need to be processed many times because it is possible
that CardiacRiskFactor is used on the If side of a rule occurring before these rules. Unlike this
example, an operational expert system may consist of hundreds, if not thousands, of rules.
The programs that process a set of rules are called expert systems shells. Typically, the
shell processes rules until no value changes. At that point, the values of all the variables are re-
ported as results.
To create the system of rules, the expert system development team interviews human ex-
perts in the domain of interest. The rules in Figure 9-25 would have been obtained by interview-
ing cardiologists who are known to be particularly adept at diagnosing cardiac disease. Such
a system encodes the knowledge of those highly skilled experts and makes it available to less-
skilled or less-knowledgeable professionals.

Other rules here...

IF CardiacRiskFactor = ‘Null’ THEN Set CardiacRiskFactor = 0
IF PatientSex = ‘Male’ THEN Add 3 to CardiacRiskFactor
IF PatientAge >55 THEN Add 2 to CardiacRiskFactor
IF FamilyHeartHistory = ‘True’ THEN Add 5 to CardiacRiskFactor
IF CholesterolScore = ‘Problematic’ THEN Add 4 to CardiacRiskFactor
IF BloodPressure = ‘Problematic’ THEN Add 3 to CardiacRiskFactor
IF CardiacRiskFactor >15 THEN Set EchoCardiagramTest = ‘Schedule’
...
Other rules here...
Figure 9-25
Example of If/Then Rules

16
Meridith Levinson, “Knowledge Management Definition and Solutions,” CIO Magazine, accessed May 2012,
www.cio.com/article/40343/Knowledge_Management_Definition_and_Solutions?page=2.