1. Chapter 1 DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE Skip subsections: 1.1, 1.2, 1.8, 1.10

2. I. DSS: Definitions System Information System Decision System Support System

3. Decisions, decisions,... When do you know, you have to make a decision? How will you go about making the decision? Why is that intuition and trial&error approaches to managerial decisions may not be effective in today’s business environment? What are some of the tools that can be helpful in making a decision?

4. DSS Definitions No universally accepted definition in literature “DSS couples the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions.” – Keen “DSS are interactive computer-based systems that help decision makers utilize data and models to solve unstructured problems.” – Sprague & Carlson “An interactive, flexible, and adaptable computer-based information system, especially developed for supporting the solution of a non- structured management problem for improved decision making. It utilizes data, provides an easy-to-use interface, and allows for the decision maker’s own insights.” - Turban Thus, DSS is a multi-disciplinary topic covering: Database research, AI, human-computer interaction, management science modeling, software engineering and telecommunications!

5. Benefits of DSS –Overcoming cognitive limits in processing and storing information –Utilize internal and external data –Uses robust mathematical/AI models –Helps understand the problem better –Speedy computations –Leads to consistent decisions –Useful in crisis –Improved communication and collaboration

6. Business as a decision-making entity What are the types of managerial control activities? What are the types of decisions?

7. Decision Characteristics –Managerial control activities Strategic planning: rare, long-term Management control: periodic, course corrections Operational control : highly repetitive, brings revenue, short-term –Types of decisions Structured: algorithmic, programmable Unstructured: subjective, vague problem space Semistructured: combination of above For Structured decisions, use MIS/TPS; Semi-structured &Unstructured decisions, use DSS

8. Gorry & Scott-Morton Framework of DSS Which of the cells has the most computer systems in use today? Why? Any more example decisions for cells 1-9?

9. Supporting Managerial Roles What are some of the ‘roles’ managers play in their job? Question: You are a Public Relations manager for your company. In what ways can a DSS help you?

10. Supporting Managerial Roles: The challenge for DSS Managerial roles (Mintzberg) –Interpersonal –Informational –Decisional

11. Question: How can a computer- based DSS assist a manager in each of these roles?

12. Supporting Decision Styles: Another challenge for DSS Decision style The manner in which a decision maker thinks and reacts to problems. It includes perceptions, cognitive responses, and beliefs –Analytic vs. Intuitive –Autocratic vs, Democratic –Consultative –Cooperative vs. Non-cooperative What characteristics a DSS should have to support each of these styles?

13. Components of DSS Network

14. Automated Decision Systems (ADS) Typically, a DSS requires user interaction. - However, if the Knowledge component is complete (eg. all manager’s decision rules / models are known), a DSS may be use AI to implement (not just recommend) solutions directly without user intervention - Useful in repetitive decisions (such as program trading, approving a loan online)

15. DSS Classifications –Model-driven DSS: quantitative models (statistical, financial, optimization, simulation) used to generate a recommended solution to a problem –Data-driven DSS: support ad-hoc reporting and queries on internal & external database –Communication-driven: multiple users, support shared tasks, either cooperative or hostile mode –Knowledge-driven: qualitative models; uses stored rules (Expert Sys & Mining) –Document-driven: search, retrieve, analyze, classify text documents (eg. Law firms use it to create a case)

16. II. Business Intelligence Companies collect a large amount of data from their business operations. To keep track of that information, a business uses disparate software applications, such as Excel, Access, etc. Using multiple software makes it difficult to retrieve information in a timely manner and to perform analysis of the data. Business Intelligence (BI) represents the tools and systems that play a key role in integrating and analyzing all corporate data. Generally illustrates intelligence in the areas of customer profiling, market research, product profitability (by product, region, year), etc.

17. BI  Custom reports Dashboard reports Production reports

18. Analytic Reports (slice & dice)

19. Sources of BI

20. BI Architecture Consists of 3 system components –Data warehouse –Business analytics –Performance management (BPM)

21. A Framework for Business Intelligence (BI)

22. Data warehouse –A repository of cleaned and integrated historical /stable data for the entire business –Extracted from independent databases (internal & external) –Transformed (ie. cleaned and reformatted) - A subset of a warehouse limited to a business function is called a Data Mart (eg. Sales).

23. DW vs. Transaction DBs DWs are not designed for performing transaction entries, but only for planning and analysis DWs are not designed for retrieval of individual records; emphasis is on summarized data DWs data pulled and integrated from disparate databases, unlike Transaction db’s which are individual applications Transaction db’s are concerned with ‘now’; DW focuses on activity over a period A transaction db is volatile (eg. an order may be cancelled); In a DW, data is only added, never deleted (as it maintains a history) Transaction db is optimized for rapid retrieval; not DWs

24. Business analytics –Reporting and queries (eg. 3-dimensional cubes) –Advanced analytics (LP, financial, stat, simulation models) –Data, text and Web mining and other sophisticated mathematical and statistical tools (searching for relationships) These are tools that help analyze the data towards finding solutions:

25. Business performance management (BPM) An advanced performance measurement and analysis approach that embraces planning and strategy –BPM extends the monitoring, measuring, and comparing of sales, profit, cost, profitability, and other performance indicators –BPM provides a top-down enforcement of corporate- wide strategy