C12 Enhancing Decision Making

1. C12 Enhancing Decision Making How demand responds to changes in price? Adjust pricing based on location? Price-sensitive customers? How much of a difference does this knowledge make?

2. Agora across Bangladesh

3. P&G’s Supply Chain- Complex?

4. Changes Are Constant! • 10-15 new product launches per year • Each product has multiple sizes and package designs

5. New product- Dove! • Where to locate the plant(s)? • What are the sources of raw materials? • Marketing Managers wants it in their respective countries • Corporate experts prefer one megaplant • And there are millions of other solutions in between • IT Global Analytics group used: • Excel enhanced by LINDO (add-on) for optimization • Palisade’s @Risk for Monte Carlo simulation (add-on) • X-press-MP from Dash Optimiztion Inc. (optimization models) • Cplex from Ilog Inc. (optimization models) • Extend from Imagine That Inc. (simulation models) Data from Oracle data warehouse (36 months of supplier, manufacturing, customer and consumer history by region)

6. P&G’s Supply Chain … • Optimization models to allocate supply chain resources • Simulation models to mathematically try various options to see the impact of changes in important variables • Decision trees to combine the possibilities of various outcomes with their financial results • Success of a supply chain is not necessarily the most optimal solution but rather a robust solution that would stand up in real world conditions • Result: • consolidation of plants by 20% • Supply chain costs reduced by $200 million each year

7. P&G’s Supply Chain … • Problem • Cost pressures, complex supply chain. • Solutions • Deploy modeling and optimization software to maximize return on investment and predict the most successful supply chain. Modeling software fueled with data from Oracle data warehouse improved efficiency and reduced costs. Illustrates digital technology improving decision making through information systems. Demonstrates IT’s role in restructuring a supply chain.

8. The Business Value • monetary value of improved decision • quality of decision making • 12.1 Decision making and information systems

9. IS for Key Decision-Making Groups Senior managers, middle managers, operational managers, and employees have different types of decisions and information requirements. • 12.1 Decision making and information systems

10. Types of Decisions • Unstructured decisions • decision maker must provide judgment, evaluation, and insight to solve the problem. • Structured decisions • repetitive and routine • they involve a definite procedure for handling them. • Many decisions have elements of both • Middle manager gets report from ES system about sales decline at Rajshahi, gets secondary (related) report from the ES. Now needs to do interview. Consider senior managers, middle managers, operational managers, and employees • 12.1 Decision making and information systems

11. Decision-support systems • Model-driven DSS • Earliest DSS were heavily model-driven • E.g. voyage-estimating DSS (Chapter 2) • Data-driven DSS • Some contemporary DSS are data-driven • Use OLAP (On-Line Analytical Processing) and data mining to analyze large pools of data Systems for Decision Support

12. The Decision-Making Process • 12.1 Decision making and information systems

13. Managers and Decision Making • in the Real World • What managers do? Five classical functions • planning, organizing, coordinating, deciding, and controlling • How do the do it? • Behavioral models state that the actual behavior of managers appears to be less systematic, more informal, less reflective, more reactive, and less well organized than the classical model would have us believe. • 12.1 Decision making and information systems

14. Managers and Decision Making • in the Real World • engage in more than 600 different activities each day • managerial activities are fragmented- most less than nine minutes, 10% exceed one hour • prefer current, specific, and ad hoc information • refer oral forms of communication- greater flexibility, ess effort, aster response • give high priority to maintaining a diverse and complex web of contacts- acts as an informal information system, helps them execute their personal agendas and short- and long-term goals Mintzberg’s Managerial Roles … • 12.1 Decision making and information systems

15. 12.1 Decision making and information systems

16. Managers and Decision Making • in the Real World • investments in information technology do not always produce positive results. There are three main reasons: • information quality • management filters • selective attention, biases • organizational culture • resist major change • decisions represent various interest groups rather thanthe best solution to the problem. • 12.1 Decision making and information systems

17. High-Velocity Automated Decision Making • Google’s search engine • High frequency traders at NYSE execute their trades in under 30 milliseconds • humans (including managers) are eliminated from the decision chain because they are too slow • Flash Crash- 2010 • 12.1 Decision making and information systems

18. Infrastructure for DSS • At the foundation of all of these DSSs are infrastructure • business intelligence (BI) and • business analytics (BA) • that supplies the • data and • analytic tools • for supporting decision making. • 12.2 Business Intelligence In The Enterprise

19. Business Intelligence? • Humans are intelligent beings • ability to take in data from their environment, • understand the meaning and significance of the information, and • then act appropriately. • “Business intelligence”- • the infrastructure for warehousing, integrating, reporting, and analyzing data that comes from the business environment • An infrastructure collects, stores, cleans, and makes relevant information available to managers • databases, data warehouses, and data marts • Just like human beings, some business firms do this well, and others poorly .) • 12.2 Business Intelligence In The Enterprise

20. BI and BA Capabilities • “Business analytics” focuses more on tools and techniques for analyzing/understanding data • OLAP, statistics, models, and data mining • BI and BA are about integrating all the information streams produced by a firm into a single, coherent enterprise-wide set of data, and then, using modeling, statistical analysis tools (like normal distributions, correlation and regression analysis, forecasting,), and data mining tools (pattern discovery and machine learning), to make sense out of all these data • 12.2 Business Intelligence In The Enterprise

21. BI and BA Vendors • 12.2 Business Intelligence In The Enterprise

22. BI and BA Vendors Business intelligence and analytics requires a strong database foundation, a set of analytic tools, and an involved management team that can ask intelligent questions and analyze data. • 12.2 Business Intelligence In The Enterprise

23. 5 analytic functionalities of BI systems Casual users are consumers of BI output, while intense power users are the producers of reports, new analyses, models, and forecasts. • 12.2 Business Intelligence In The Enterprise

24. Business Intelligence Applications • Predictive Analytics • Credit card risk • Data Visualization and Geographic Information Systems (GIS) • 12.2 Business Intelligence In The Enterprise

25. Management Strategies for Developing BI and BA Capabilities • One-stop integrated solutions versus multiple best-of-breed vendor solutions • Advantage/Not! • switching is very costly • When you adopt these systems, you are in essence taking in a new partner • 12.2 Business Intelligence In The Enterprise

26. Decision Support for Operational and Middle Management • 12.3 Business Intelligence Constituencies

27. Decision Support for Operational and Middle Management • Some managers are “super users”/ business analysts who • want to create their own reports • use more sophisticated analytics and models • find patterns in data • model alternative business scenarios • to test specific hypotheses. • Decision support systems (DSS) are the BI delivery platform • rely more heavily on modeling than MIS • what-if or other kinds of analysis • Sensitivity analysis - predict a range of outcomes • OLAP- pivot table • 12.3 Business Intelligence Constituencies

28. Sensitivity Analysis This table displays the results of a sensitivity analysis of the effect of changing the sales price of a necktie and the cost per unit on the product’s break-even point. It answers the question, “What happens to the break-even point if the sales price and the cost to make each unit increase or decrease?” • 12.3 Business Intelligence Constituencies

29. The Excel PivotTable Wizard The PivotTable Wizard in Excel makes it easy to analyze lists and databases by simply dragging and dropping elements from the Field List • 12.3 Business Intelligence Constituencies

30. Using spreadsheet pivot tables to support decision making • Online Management Training Inc. (OMT Inc.), sells online management training books and streaming online videos to corporations and individuals • Records of online transactions can be analyzed using Excel to help business decisions, e.g.: • Where do most customers come from? • Where are average purchases higher? • What time of day do people buy? • What kinds of ads work best? Systems for Decision Support

31. Example: ALICO Insurance • Using widely available insurance industry data, ALICO defines small groups of customers, or “cells,” such as motorcycle riders aged 30 or above with college educations, credit scores over a certain level, and no accidents. • For each “cell,” Progressive performs a regression analysis to identify factors most closely correlated with the insurance losses that are typical for this group. • It then sets prices for each cell, and uses simulation software to test whether this pricing arrangement will enable the company to make a profit. • These analytic techniques, make it possible for ALICO to profitably insure customers in traditionally high-risk categories that other insurers would have rejected. Consider GP Package • 12.3 Business Intelligence Constituencies

32. Example: Business value of DSS … • Burlington Coat Factory: DSS for pricing • DSS manages pricing and inventory nationwide, considering complex interdependencies between initial prices, promotions, markdowns, cross-item pricing effects and item seasonality • Syngenta: DSS for profitability analysis • DSS determines if freight charges, employee sales commissions, currency shifts, and other costs in proposed sale make that sale or product unprofitable • Compass Bank: DSS for customer relationship management • DSS analyzes relationship between checking and savings account activity and default risk to help it minimize default risk in credit card business Systems for Decision Support

33. DSS for CRM … Systems for Decision Support

34. Senior Management: The Balanced Scorecard and Enterprise Performance Management Methods • Executive Support Systems (ESS) • a methodology for understanding exactly what is “the really important performance information” • develop systems capable of delivering this information • The balanced scorecard • a framework for operationalizing a firm’s strategic plan by focusing on measurable outcomes on four dimensions of firm performance: financial, business process, customer, and learning and growth • Performance on each dimension is measured using key performance indicators (KPIs), which are the measures proposed by senior management • 12.3 Business Intelligence Constituencies

35. The balanced scorecard • If your firm is a bank, one KPI of business process performance is the length of time required to perform a basic function like creating a new customer account. • 12.3 Business Intelligence Constituencies

36. The balanced scorecard • 12.3 Business Intelligence Constituencies

37. Executive support systems (ESS) • Integrate data from different functional systems for firmwide view • Incorporate external data, e.g. stock market news, competitor information, industry trends, legislative action • Include tools for modeling and analysis • Primarily for status, comparison information about performance • Facilities for environmental scanning - detecting signals of problems, threats, or strategic opportunities • Able to drill down from summary information to lower levels of detail Executive Support Systems (ESS)

38. Business value of ESS • Enables executive to review more data in less time with greater clarity than paper-based systems • Result: Needed actions identified and carried out earlier • Increases upper management’s span of control • Can enable decision making to be decentralized and take place at lower operating levels • Increases executives’ ability to monitor activities of lower units reporting to them Executive Support Systems (ESS)

39. Case of National Life • National Life: Markets life insurance, health insurance, and retirement/investment products executive information system • Executive information system: • Allows senior managers to access corporate databases through Web interface • Shows premium dollars by salesperson • Authorized users can drill down into these data to see product, agent, and client for each sale • Data can be examined by region, by product, and by broker, and accessed for monthly, quarterly, and annual time periods ESS for business intelligence Executive Support Systems (ESS)

40. Group Decision-Support Systems (GDSS) • Much work is accomplished in groups within firms that a special category of systems called group decision-support systems (GDSS) has been developed to support group and organizational decision making. • An interactive computer-based system for facilitating the solution of unstructured problems by a set of decision makers working together as a group in the same location or in different locations • Collaboration systems type tools and technologies • Geared explicitly toward group decision making • promotes a collaboration by guaranteeing anonymity • 12.3 Business Intelligence Constituencies

41. California’s South Coast Air Quality Management District (AQMD) is responsible for monitoring and controlling emissions in all of Orange County and the urban portions of Los Angeles, Riverside, and San Bernardino counties. Displayed is a map produced with ESRI GIS software tracking particulate matter emissions from building construction activity in a two-by-two kilometer area. Systems for Decision Support

42. Overview of a GDSS meeting • Each attendee has workstation, networked to facilitator’s workstation and meeting’s file server • Whiteboards on either side of projection screen • Seating arrangements typically semicircular, tiered • Facilitator controls use of tools during meeting • All input saved to server, kept confidential • After meeting, full record (raw material and final output) assembled and distributed • Make meetings more productive by providing tools to facilitate: • Planning, generating, organizing, and evaluating ideas • Establishing priorities • Documenting meeting proceedings for others in firm

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44. MIS- Based • Help managers monitor and control business by providing information on firm’s performance and address structured problems • Typically produce fixed, regularly scheduled reports based on data from TPS • E.g. exception reports: Highlighting exceptional conditions, such as sales quotas below anticipated level • E.g. Pizzahut Kitchen MIS • For each restaurant, compares amount of ingredients used per ordered menu item to predefined portion measurements and identifies restaurants with out-of-line portions Systems for Decision Support

45. Components of DSS • Database used for query and analysis • Current or historical data from number of applications or groups • May be small database or large data warehouse • User interface • Often has Web interface • Software system with models, data mining, and other analytical tools Overview of a Decision-Support System Systems for Decision Support

46. Model • Abstract representation that illustrates components or relationships of phenomenon; may be physical, mathematical, or verbal model • Statistical models • Optimization models • Forecasting models • Sensitivity analysis models Systems for Decision Support

47. DSS for Supply Chain Management • Comprehensive examination of inventory, supplier performance, logistics data • To help managers search alternatives and decide on the most efficient and cost-effective combination • Reduces overall costs • Increases speed and accuracy of filling customer orders Systems for Decision Support

48. Data visualization tools: • Help users see patterns and relationships in large amounts of data that would be difficult to discern if data were presented as traditional lists of text • Geographic information systems (GIS): • Category of DSS that use data visualization technology to analyze and display data in form of digitized maps • Used for decisions that require knowledge about geographic distribution of people or other resources, e.g.: • Helping local governments calculate emergency response times to natural disasters • Help retail chains identify profitable new store locations Systems for Decision Support

49. Web-based customer decision-support systems (CDSS) • Support decision-making process of existing or potential customer • Automobile companies that use CDSS to allow Web site visitors to configure desired car • Financial services companies with Web-based asset-management tools for customers; Fidelity Investments: customer portfolio allocations, retirement savings plans... • Home.com: mortgage, rent or buy... Systems for Decision Support

50. Bonita Bay Properties • Digital dashboard: Displays on single screen key performance indicators as graphs and charts for executives • Bonita Bay Properties Inc.: Develops planned communities centered around golf courses and fitness centers • Executive dashboard displays: • Summaries from point-of-sale systems and general ledger accounts • Staffing levels • Executives can drill down to performance of fitness centers, activity on golf courses Monitoring corporate performance with digital dashboards Executive Support Systems (ESS)