1. CHAPTER TWELVE ENHANCING DECISION-MAKING

2. Objectives Understand types of decisions

3. Types of Decisions Unstructured decisions require judgement Structured decisions require no judgment Semistructured decisions have characteristics of both

4. Unstructured Decisions Unstructured decisions require judgement No procedures to follow Often made by senior management Tend to have the greatest business value

5. Structured Decisions No real decision-making required Well-defined procedures drive the decision Machines can make some (or many) of these decisions Made by operational staff

6. Semistructured Decisions Typically made by middle- management They involve structured and unstructured parts The decision to extend credit is based on rules There might be extenuating customer circumstances that require a more unstructured decision

7. Business Value of a Decision We can estimate the value of “better decisions” It’s a simple calculation Number of decisions per year * decision value

8. Stages in Decision Making As you will see in the next chapter, this process mimics the software lifecycle Problem identification Solution discovery Solution evaluation Solution selection Solution testing

9. Roles of Management Classical model of management Plan, organize, coordinate, decide, control Behavioral models suggest that managerial methodologies are less systematic than once thought

10. Managerial Roles (1) Interpersonal Figurehead, leader or cheerleader Liaison between organizational units Informational Disseminator of information Spokesperson Champion Change agents

11. Managerial Roles (2) Decisional Resource allocation Negotiation with other organizational units Fight for budgets and projects

12. Information Quality (1) We have talked about this Accuracy Inaccurate information is useless or may be net negative Integrity and consistency Are data and their relationships consistent across the organization Completeness Does the data we have paint a complete picture

13. Information Quality (2) Validity Ties to accuracy and consistency Is data within normal or expected ranges Timeliness Available when needed? Accessibility Can we easily get to the data we need

14. High Velocity Automated Decision-Making The best examples Program trading on the stock exchanges Flash crash Knight Capital Airlines reservation systems

15. Using BI to Support Decision-making We have defined business intelligence already

16. The BI Ecosystem Structured and unstructured data from many sources Big data Database management systems Data warehouse Internal and external data A set of software tools to manipulate that data A delivery platform

17. BI Capabilities Production reports I categorize these as traditional MIS reports Parameterized reports These are the pivot tables and cubes already discussed Dashboards Dundas and GapMinder example Ad hoc queries Drill-down and Drill-up

18. Predictive Analytics This is the Harrah’s Total Rewards case Predict the possibility of a customer accepting an offer Determine what happened Refine the model as needed Some of this comes from “big data”

19. Operational Intelligence Using data to make operational decisions Transportation Where to stop for fuel Routing changes due to weather or traffic Data often collected using a myriad of sensors

20. Location Analytics and GIS These are called Geographical Information Systems ESRI is the dominant market leader with ARC

21. Strategies to Improve BI and Decision-making Buy it from a vendor SAP SAS Build it Or a hybrid of both

22. Analytical Methods Balanced Scorecard Analyze measureable outcomes across four dimensions Business processes Financial Customers Learning and growth