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Chapter 12

Chapter 12. Enhancing Decision Making. Types of decisions. Unstructured : Decision maker must provide judgment, evaluation, and insight to solve problem Structured : Repetitive and routine; involve definite procedure for handling so they do not have to be treated each time as new

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Chapter 12

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  1. Chapter 12 Enhancing Decision Making

  2. Types of decisions • Unstructured: Decision maker must provide judgment, evaluation, and insight to solve problem • Structured: Repetitive and routine; involve definite procedure for handling so they do not have to be treated each time as new • Semistructured: Only part of problem has clear-cut answer provided by accepted procedure

  3. Types of Decisions by Level • Senior managers: • Make many unstructured decisions • E.g. Should we enter a new market? • Middle managers: • Make more structured decisions but these may include unstructured components • E.g. Why is order fulfillment report showing decline in Minneapolis? • Operational managers, rank and file employees • Make more structured decisions • E.g. Does customer meet criteria for credit?

  4. Decision Making Process The decision-making process is broken down into four stages.

  5. Decision Making and Information • Three main reasons why investments in information technology do not always produce positive results • Information quality (see table 12-3 page 460) • Management filters • Organizational inertia and politics • High velocity automated decision making • Automate those structured, routine decision making

  6. Business Intelligence • Business intelligence • Infrastructure for collecting, storing, analyzing data produced by business • Databases, data warehouses, data marts • Business analytics • Tools and techniques for analyzing data • OLAP, statistics, models, data mining • Business intelligence vendors • Top five vendors SAP, Oracle, IBM, SAS Institute, and Microsoft (manage big data)

  7. Business Intelligence Environment

  8. Business Intelligence and Analytics Capabilities • Main functionalities of BI systems • Production reports • Parameterized reports • Dashboards/scorecards • Ad hoc query/search/report creation • Drill down • Forecasts, scenarios, models • Pre-defined/prepackaged production reports most widely used (see table 12-5)

  9. Business Intelligence and Analytics Capabilities (cont) • Examples of BI applications • Predictive analytics • Use patterns in data to predict future behavior • E.g. Credit card companies use predictive analytics to determine customers at risk for leaving • Data visualization • Help users see patterns and relationships that would be difficult to see in text lists (dashboards help) • Geographic information systems (GIS) • Ties location-related data to maps

  10. Decision Support Systems(Operational and Middle Mgmt) • Use mathematical or analytical models • Allow varied types of analysis • “What-if” analysis • Sensitivity analysis (see page 472) • Backward sensitivity analysis • Multidimensional analysis / OLAP • E. g. pivot tables (see page 473) • Use Management Information Systems (MIS) • Structured and semistructured decisions; data flow reports; routine production reports; exception reports

  11. Decision Support Systems (Senior Management) • Use Executive Support Systems (ESS) • Help executives focus on important performance information; allow them to drill down to detailed views of data • Methodology • Balanced scorecard method: • Measures outcomes on four dimensions: • Financial • Business process • Customer • Learning & growth • Key performance indicators (KPIs) measure each dimension • Business Performance Management (BPM)

  12. Decision Support Systems(Groups) • Group Decision Support Systems (GDSS) • Used for tasks involving idea generation, complex problems, large groups • Example

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