Business intelligence and knowledge management

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Use with
Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Management Information
Systems

By

Effy Oz & Andy Jones





www.cengage.co.uk/oz

Chapter 10: Business Intelligence
and Knowledge Management


Use with
Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Objectives


Explain the concepts of data mining and online
analytical processing


Explain the notion of business intelligence and its
benefits to organizations


Identify needs for knowledge storage and
management in organizations


Explain the challenges in knowledge management
and its benefits to organizations



Use with
Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Data Mining and Online Analysis


Data warehouses are useless without software
tools


Process data into information


Business intelligence (BI)
: information gleaned
with information tools


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Data Mining


Data mining
: selecting, exploring, and modeling
data


Supports decision making


Finds relationships and ratios within data


Finds unknown relationships


Queries are more complex than traditional


Combination of data
-
warehouse and data
-
mining
facilitates predictions



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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Data Mining (continued)


Data mining has four objectives


Sequence or path analysis


Classification


Clustering


Forecasting


Techniques applied to various fields


Marketing


Fraud detection


Marketing to individual


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Data Mining (continued)


Data mining can predict customer behaviour


Banking


Find profitable customers


Find patterns of fraud


Mobile phones


Customers tend to switch companies often


Customer loyalty programs ensure steady flow
of customer data


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Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Data Mining (continued)


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Data Mining (continued)


Utilizing loyalty programs


Frequent flier


Consumer clubs


Amass huge amount of data about customer


Harrah’s Entertainment Inc.


Uses data mining to discern big spenders


Allows sales agents to charge big spenders less
money



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Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Data Mining (continued)


Inferring demographics


Predict what customers likely to purchase in future


Amazon.com


Age ranges estimated from purchase history


Advertises for appropriate age group


Anticipates holidays


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Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Online Analytical Processing


Online analytical processing (OLAP)
:
application to exploit data warehouses


Extremely fast response


View combinations of two dimensions


Drilling down
: start with broad info and get
more specific


Can receive info in numbers or percentages


Uses specifically tailored data or relational
database



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Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Online Analytical Processing
(continued)


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
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© 2008 Cengage Learning


Online Analytical Processing
(continued)


OLAP application composes tables immediately


Dimensional database
: data organized into tables


Tables show information in summaries


Companies sell multidimensional database
packages


OLAP applications are powerful tools for
executives



Use with
Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Online Analytical Processing
(continued)


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Online Analytical Processing
(continued)


Ruby Tuesday restaurant chain case


One location was performing below average


Customers were waiting longer than normal


Appropriate changes were made


OLAP applications installed on special server




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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Online Analytical Processing
(continued)


OLAP faster than relational applications


OLAP increasingly used by corporations


Office Depot used OLAP on data warehouse


CVS let 2,000 employees run analyses


Ben & Jerry’s track ice cream popularity


BI software becoming easier to use


Intelligent interfaces



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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
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© 2008 Cengage Learning


More Customer Intelligence


Major effort of business is BI collection


Data
-
mining and OLAP software integrated into
CRM


Web becoming popular for transactions


Targeted marketing better than mass marketing


Data from customer not complete


Third party companies hired to study consumer


Doubleclick


Engage


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
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© 2008 Cengage Learning


More Customer Intelligence (continued)


Third party consumer data collection companies


Compile billions of clickstreams to create
behavioural models


Keep track of various fields


Time of surfing


Frequency of visits


Which sites


Number of times ads are clicked


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
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© 2008 Cengage Learning


Executive Dashboards


Dashboard
: interface between BI tool and user


Resembles a car dashboard


Contains visual images


Designed to quickly represent specific data



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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Executive Dashboards (continued)


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y Effy Oz & Andy Jones ISBN
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© 2008 Cengage Learning


Knowledge Management


Companies should record experience with
clients


Financial transactions information not enough


Ease of interaction


Strengths


Weaknesses


Types of problems encountered


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Knowledge Management (continued)


Knowledge management (KM)


Purpose is to know where to find information
about subject


Transfer individual knowledge into databases


Filter relevant knowledge


Organize knowledge for easy access






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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Capturing and Sorting Organizational
Knowledge


Knowledge workers
: research, prepare, and
provide information


Much overlap in work they do


Money saved by collecting and organizing
knowledge gained by workers


Require workers to create reports of findings


Require reports about sessions with clients


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Capturing and Sorting Organizational
Knowledge (continued)


Challenge is how to find answers to specific
questions


Software tools exist to help


Electronic Data Systems Corp


Replaced questionnaires with automated
system


Motorola uses application that pulls
information from KM program





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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Employee Knowledge Networks


Some tools direct employees to other employees


Expert can provide non
-
recorded expertise


No need to waste money hiring experts in every
department


Learning from past mistakes saves money


Employee knowledge network
: facilitate
knowledge sharing through intranets


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Employee Knowledge Networks
(continued)


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
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© 2008 Cengage Learning


Employee Knowledge Networks
(continued)


Tacit Systems


Used tool to process business communications


Discovered work focus of employees


Expertise


Business relationships


Mines unstructured data to build profiles


Profile accessible by other employees but not private
info


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Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Employee Knowledge Networks
(continued)


AskMe


Used software to detect keywords from e
-
mail and
documents created


Created knowledge base


Allowed for search query on Web


Search returns names of employees



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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Knowledge from the Web


Consumers post opinions of products on Web


On vendor’s site


Product evaluation sites


Epinions.com


Blogs


Opinions expressed on large number of Web
pages


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Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Knowledge from the Web (continued)


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Management Information Systems 1e

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y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Knowledge from the Web (continued)


Consumer opinions highly unstructured


Garnering this knowledge could aid market
research


Learn about competitors and own products


Companies have developed software to get this
information


Accenture Technology Labs


Uses Online Audience Analysis software


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Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Knowledge from the Web (continued)


Companies use tools that search Web sites for
information about products


Data mining used to help locate what
consumers are saying about company products


Factiva is software tool that gathers such info


Collects from newspapers, journals, market
data, and newswires


Screens all new information for info relevant to
specific organization


Use with
Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Summary


Business intelligence (BI) is any information
about organization, customers, or suppliers


Data mining is selecting, exploring, and
modeling data


Data mining useful for predicting customer
behavior and detecting fraud


Online analytical processing (OLAP) puts data
into two
-
dimensional tables


Use with
Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Summary (continued)


OLAP uses dimensional databases or
calculates tables on the fly


Drilling down means moving from a broad to
specific view of information


Executive dashboards interface with BI
software


Knowledge management involves gathering,
organizing, and sharing knowledge


Main challenge of knowledge management is
identifying and classifying useful information


Use with
Management Information Systems 1e

B
y Effy Oz & Andy Jones ISBN
9781844807581


© 2008 Cengage Learning


Summary (continued)


Most unstructured knowledge is textual


Employee knowledge networks are software
tools to help employees find other employees