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Management Information Systems By Effy Oz & Andy Jones Chapter 10: Business Intelligence and Management Information Systems By Effy Oz & Andy Jones Chapter 10: Business Intelligence and Knowledge Management www. cengage. co. uk/oz Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Objectives • Explain the concepts of data mining and online analytical processing • Explain 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 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Data Mining and Online Analysis • Data warehouses are useless without software tools • Data Mining and Online Analysis • Data warehouses are useless without software tools • Process data into information • Business intelligence (BI): information gleaned with information tools Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Data Mining • Data mining: selecting, exploring, and modeling data – Supports decision making 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Data Mining (continued) • Data mining has four objectives – Sequence or path analysis 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Data Mining (continued) • Data mining can predict customer behaviour – Banking • Find 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Data Mining (continued) Use with Management Information Systems 1 e By Effy Oz & Data Mining (continued) Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Data Mining (continued) • Utilizing loyalty programs – Frequent flier – Consumer clubs – 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Data Mining (continued) • Inferring demographics – Predict what customers likely to purchase in 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Online Analytical Processing • Online analytical processing (OLAP): application to exploit data warehouses – 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Online Analytical Processing (continued) Use with Management Information Systems 1 e By Effy Oz Online Analytical Processing (continued) Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Online Analytical Processing (continued) • OLAP application composes tables immediately • Dimensional database: data 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 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Online Analytical Processing (continued) Use with Management Information Systems 1 e By Effy Oz Online Analytical Processing (continued) Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Online Analytical Processing (continued) • Ruby Tuesday restaurant chain case – One location was 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Online Analytical Processing (continued) • OLAP faster than relational applications • OLAP increasingly used 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

More Customer Intelligence • Major effort of business is BI collection • Data-mining and 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

More Customer Intelligence (continued) • Third party consumer data collection companies – Compile billions 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Executive Dashboards • Dashboard: interface between BI tool and user – Resembles a car Executive Dashboards • Dashboard: interface between BI tool and user – Resembles a car dashboard – Contains visual images – Designed to quickly represent specific data Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Executive Dashboards (continued) Use with Management Information Systems 1 e By Effy Oz & Executive Dashboards (continued) Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Knowledge Management • Companies should record experience with clients • Financial transactions information not Knowledge Management • Companies should record experience with clients • Financial transactions information not enough – Ease of interaction – Strengths – Weaknesses – Types of problems encountered Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Knowledge Management (continued) • Knowledge management (KM) – Purpose is to know where to 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Capturing and Sorting Organizational Knowledge • Knowledge workers: research, prepare, and provide information – 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Capturing and Sorting Organizational Knowledge (continued) • Challenge is how to find answers to 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Employee Knowledge Networks • Some tools direct employees to other employees • Expert can 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Employee Knowledge Networks (continued) Use with Management Information Systems 1 e By Effy Oz Employee Knowledge Networks (continued) Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Employee Knowledge Networks (continued) • Tacit Systems – Used tool to process business communications 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Employee Knowledge Networks (continued) • Ask. Me – Used software to detect keywords from Employee Knowledge Networks (continued) • Ask. Me – 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Knowledge from the Web • Consumers post opinions of products on Web – On 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Knowledge from the Web (continued) Use with Management Information Systems 1 e By Effy Knowledge from the Web (continued) Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Knowledge from the Web (continued) • Consumer opinions highly unstructured – Garnering this knowledge 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 Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Knowledge from the Web (continued) • Companies use tools that search Web sites for 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 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Summary • Business intelligence (BI) is any information about organization, customers, or suppliers • 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 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Summary (continued) • OLAP uses dimensional databases or calculates tables on the fly • 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 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning

Summary (continued) • Most unstructured knowledge is textual • Employee knowledge networks are software Summary (continued) • Most unstructured knowledge is textual • Employee knowledge networks are software tools to help employees find other employees Use with Management Information Systems 1 e By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning