CHAPTER 9 : ENABLING THE ORGANIZATION-DECISION MAKING

CHAPTER 9ENABLING THE ORGANIZATION – DECISION MAKING
Decision MakingReasons for the growth of decision-making information systems

1. People need to analyze large amounts of information

1. People must make decisions quickly

1. People must apply sophisticated analysis techniques, such as modeling and forecasting, to make good decisions

1. People must protect the corporate asset of organizational information

Model – a simplified representation or abstraction of realityIT systems in an enterprise

Transaction Processing SystemsMoving up through the organizational pyramid users move from requiring transactional information to analytical information

• Transaction processing system - the basic business system that serves the operational level (analysts) in an organization 

• Online transaction processing (OLTP) – the capturing of transaction and event information using technology to (1) process the information according to defined business rules, (2) store the information, (3) update existing information to reflect the new information

• Online analytical processing (OLAP) – the manipulation of information to create business intelligence in support of strategic decision making

Decision Support SystemsDecision support system (DSS) – models information to support managers and business professionals during the decision-making process
Three quantitative models used by DSSs include:

1. Sensitivity analysis – the study of the impact that changes in one (or more) parts of the model have on other parts of the model

1. What-if analysis – checks the impact of a change in an assumption on the proposed solution

1. Goal-seeking analysis – finds the inputs necessary to achieve a goal such as a desired level of output

Executive Information SystemsExecutive information system (EIS) – a specialized DSS that supports senior level executives within the organization
Most EISs offering the following capabilities:

1. Consolidation – involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information

1. Drill-down – enables users to get details, and details of details, of information

1. Slice-and-dice – looks at information from different perspectives

Digital dashboard – integrates information from multiple components and presents it in a unified displayArtificial Intelligence (AI)Intelligent system – various commercial applications of artificial intelligenceArtificial intelligence (AI) – simulates human intelligence such as the ability to reason and learnAdvantages: can check info on competitorFour most common categories of AI include:

1. Expert system – computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems

1. Neural Network – attempts to emulate the way the human brain works ;Fuzzy logic – a mathematical method of handling imprecise or subjective information

1. Genetic algorithm – an artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem

1. Intelligent agent – special-purposed knowledge-based information system that accomplishes specific tasks on behalf of its users;Multi-agent systems, Agent-based modeling

Data MiningData-mining software includes many forms of AI such as neural networks and expert systemsCommon forms of data-mining analysis capabilities include:

• Cluster analysis

• Association detection

• Statistical analysis

Cluster AnalysisCluster analysis – a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possibleCRM systems depend on cluster analysis to segment customer information and identify behavioral traitsAssociation DetectionAssociation detection – reveals the degree to which variables are related and the nature and frequency of these relationships in the informationMarket basket analysis – analyzes such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and servicesStatistical AnalysisStatistical analysis – performs such functions as information correlations, distributions, calculations, and variance analysisForecast – predictions made on the basis of time-series informationTime-series information – time-stamped information collected at a particular frequency