Chapter 11: Data, Knowledge, and Decision Support Introduction to Information Technology 2nd Edition Turban, Rainer & Potter © 2003 John Wiley & Sons, Inc. Chapter 11: Data, Knowledge, and Decision Support Prepared by: Roberta M. Roth, Ph.D. University of Northern Iowa

Chapter Preview In this chapter, we will study: The decision making process and how IT can support it Various types of decision support, including DSS, EIS, and GDSS Methods of analyzing and mining stored data Ways of presenting information through data visualization techniques Knowledge management and how it can benefit an organization

Why Do Managers Need IT Support? Volume of available information is staggering Manually processing information quickly is increasingly difficult Computerized modeling helps manage complexity examine numerous alternatives very quickly provide a systematic risk analysis

Where do we get the data we need? Data Sources Internal Data Personal Data External Data Data Collection Methods Manually By instruments and sensors Scanning or electronic transfer Internal data – generated by business transactions Personal data – individual, subjective estimates, projections, opinions, judgements External data – generated outside organization, but relevant to organization. Economic data, competitive intelligence

What is ‘good’ data? Data Quality quality determines the data’s usefulness as well as the quality of the decisions based on these data an extremely important issue characteristics of high quality data: accurate, secure, relevant, timely, complete, and consistent

Data Storage and Management Databases or in data warehouse and data marts Data Management difficulties Data volume exponentially increases with time Many methods and devices used to collect data Raw data stored many places and ways only small portions of data are relevant for specific situations More and more external data Different legal requirements relating to data Difficulty selecting data management tools Data security, quality, and integrity are essential Need to store and manage data so that it can be transformed into information and knowledge.

Document Management Systems Much data is contained in documents DMS manage electronic documents Provide control over and access to documents within organization Imaging systems, workflow software, and databases are utilized to efficiently capture and control documents Global systems – systems connecting two or more companies in two or more countries Electronic data interchange (EDI) – electronic movement of business documents between business partners Electronic funds transfer (EFT) – transfer of money using telecommunications Extranets – extended Intranets that link business partners Shared databases – databases that business partners both have access to Integrated messaging – delivery of email and fax messages through a single communication system.

Business Intelligence Ultimate goal of collecting data is to provide a foundation for business intelligence All data needed for sound decisions Data is drawn from data warehouses or data marts Data analysis tools are applied Decision makers’ judgment is augmented with facts, analysis, and forecasts Global systems – systems connecting two or more companies in two or more countries Electronic data interchange (EDI) – electronic movement of business documents between business partners Electronic funds transfer (EFT) – transfer of money using telecommunications Extranets – extended Intranets that link business partners Shared databases – databases that business partners both have access to Integrated messaging – delivery of email and fax messages through a single communication system.

Decision Making Process  Intelligence Phase Design Phase Choice Phase REALITY Implementation of Solution  SUCCESS FAILURE Verification, Testing of Proposed Solution Validation of the Model Examination Intelligence: organizational objectives Search and scanning procedures data collection problem identification problem classification problem statement Design formulate a model (assumptions) set criteria for choice search for alternatives predict and measure outcomes Choice solution to the model sensitivity analysis selection of best alternative plan for implementation design of control system

Decision Making Process (continued) Decision Support Systems supply computerized support for the decision making process End-users actively work with the data warehouse End-users apply models to represent, understand, and simplify the decision situation

What do we mean by ‘model’? Model - simplified representation of reality Iconic (scale) models physical replica of a system Analog models Behaves like real system; does not look like it Mathematical (quantitative) model models complex relationships and conducts experimentations with them Mental models how a person thinks about a situation Iconic model – prototype of building or new airplane Analog model – topographic map; house blueprint Mathematical model – weather forecasting and storm prediction Mental model – beliefs, assumptions, relationships, and work flows. These models determine the information we use the the manner in which people interpret or ignore information.

Thinking about decisions… A Framework for Computerized Decision Support Problem Structure decision making processes fall along a continuum that ranges from highly structured to highly unstructured decisions Nature of Decisions strategic planning - the long-range goals and policies for resource allocation management control - the acquisition and efficient utilization of resources in the accomplishment of organizational goals operational control - the efficient and effective execution of specific tasks

Thinking about decisions… Structured decisions have long been supported by computers Classes of structured decisions have been addressed mathematically with Management Science models Define the problem Classify the problem into a standard category Construct a standard mathematical model Find potential solutions Choose and recommend a specific solution

Decision Support Systems Needed when decision is not structured Characteristics and Capabilities Support decision makers at all managerial levels Support several interdependent and/or sequential decisions Support all phases of decision making and a variety of decision-making processes and styles Can be adapted over time to deal with changing conditions Easy to construct Utilizes models and links to data- and knowledge bases Execute sensitivity analysis

DSS (continued) Sensitivity Analysis What-if Analysis the study of the effect that changes in one or more parts of a model have on other parts of the model What-if Analysis checks the impact of a change in the assumptions or other input data on the proposed solution Goal-seeking Analysis find the value of the inputs necessary to achieve a desired level of output

DSS (continued) Components and Structure of DSS Data Management Includes the database(s) containing relevant data for the decision situation User Interface Enables the users to communicate with and command the DSS Model Management Includes software with financial, statistical, management science, or other quantitative models Knowledge Management Provides knowledge for solution of the problem; supports any of the other subsystems or act as an independent component

Enterprise Decision Support Executive Information Systems Meet information needs of executives Need to monitor and identify problematic trends Need external as well as internal information Rapid access to data needed by executives Very easy user interface Highly graphical Often connected with online information services (e.g., Dow Jones News Retrieval)

Enterprise Decision Support Executive Information Systems (continued) Capabilities of EIS Drill down Critical success factors and key performance indicators Status access Trend analysis Ad hoc analysis Exception reporting Intelligent EIS Integration with DSS; web accessibility

Enterprise Decision Support Group Decision Support Systems Facilitate solution of semistructured and unstructured decisions by a group of decision makers Help the group be productive by mitigating some negative group behaviors Support the group’s process by encouraging idea generation, improving communication, and applying analytical tools as needed to the problem

Enterprise Decision Support GDSS Implementations Face-to-face meetings – special ‘decision room’ created with linked computers and GDSS software; use is facilitated by trained leader Corporate ‘war room’ – information displayed graphically and analyses conducted for all to see Support for virtual teams – collaborative team tools for geographically dispersed teams; support discussion, calendars, polling, etc.

What can we do with the stored data? Analytical Processing - the activity of analyzing accumulated data Online analytical processing (OLAP) An end-user activity Involve large data sets with complex relationships Use Decision Support Systems models Is retrospective

Online Analytical Processing (OLAP) Analysis by end users from their desktop, online, using tools like spreadsheets Analyze the relationships between many types of business elements Involve aggregated data Compare aggregated data over hierarchical time periods (monthly, quarterly, annually) Present data in different perspectives Involve complex calculations between data elements Respond quickly to users requests

Data Visualization Analyzed data can be even more useful if presented using Data Visualization techniques Visual Interactive Modeling – graphic display of decision consequences Visual Interactive Simulation – simulation model is animated and can be viewed and modified by decision maker Geographic Information Systems – display data related to geographic location using digitized maps

Chapter Summary High quality data can be analysed to improve decision making DSSs help decision makers with semi- or unstructured decisions Executives can use EISs tailored to their information needs GDSSs support group decision activities Data analysis and data mining help in understanding and discovery of new insight Knowledge is also an organizational resource that can be stored and managed Global systems – systems connecting two or more companies in two or more countries Electronic data interchange (EDI) – electronic movement of business documents between business partners Electronic funds transfer (EFT) – transfer of money using telecommunications Extranets – extended Intranets that link business partners Shared databases – databases that business partners both have access to Integrated messaging – delivery of email and fax messages through a single communication system.

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