1. McGraw-Hill-Ryerson ©2011 The McGraw-Hill Companies, All Rights Reserved CHAPTER 2 Decision Making and Business Processes Opening Case: Information Systems Improve Business Processes at Grocery Gateway

2. 2-2 Copyright © 2011 McGraw-Hill Ryerson Limited Chapter Two Overview SECTION 2.1 - DECISION-MAKING AND INFORMATION SYSTEMS –Decision Making –Transactional Data & Analytical Information –Measuring Decision Success –TPS, DSS, and EIS –Artificial Intelligence SECTION 2.2 – BUSINESS PROCESSES –Understanding the Importance of Business Processes –Business Process Improvement –Business Process Re-engineering –Business Process Modelling –Business Process Management –Business Process Modelling Examples

3. 2-3 Copyright © 2011 McGraw-Hill Ryerson Limited LEARNING OUTCOMES 1.Explain the difference between transactional data and analytical information, and between OLTP and OLAP. 2.Explain how organizations use TPS, DSS, and EIS to make decisions and how each can be used to help make unstructured, semi-structured, and structured decisions. 3.Describe what AI is and the five types of artificial intelligence systems used by organizations today.

4. 2-4 Copyright © 2011 McGraw-Hill Ryerson Limited LEARNING OUTCOMES 4.Describe how AI differs from TPS, DSS and EIS. 5.Describe the importance of business process improvement, business process re-engineering, business process modelling, and, business process management to an organization and how information systems can help in these areas.

5. McGraw-Hill-Ryerson ©2011 The McGraw-Hill Companies, All Rights Reserved SECTION 2.1 DECISION-MAKING AND INFORMATION SYSTEMS

6. 2-6 Copyright © 2011 McGraw-Hill Ryerson Limited Making Good Business Decisions Managerial decision-making challenges –Analyze large amounts of information –Apply sophisticated analysis techniques –Make decisions quickly 2-1 Learning Outcomes

7. 2-7 Copyright © 2011 McGraw-Hill Ryerson Limited Decision-making Decision-making and problem- solving occur at each level in an organization 2-2 Learning Outcomes

8. 2-8 Copyright © 2011 McGraw-Hill Ryerson Limited Operational Decision-Making Operational decision making - Employees develop, control, and maintain core business activities required to run the day-to-day operations Structured decisions - Situations where established processes offer potential solutions 2-2 Learning Outcomes

9. 2-9 Copyright © 2011 McGraw-Hill Ryerson Limited Managerial Decision-Making Managerial decision making – Employees evaluate company operations to identify, adapt to, and leverage change Semi-structured decisions – Occur in situations in which a few established processes help to evaluate potential solutions, but not enough to lead to a definite recommended decision 2-2 Learning Outcomes

10. 2-10 Copyright © 2011 McGraw-Hill Ryerson Limited Strategic Decision-Making Strategic decision making – Managers develop overall strategies, goals, and objectives Unstructured decisions – Occurs in situations in which no procedures or rules exist to guide decision makers toward the correct choice 2-2 Learning Outcomes

11. 2-11 Copyright © 2011 McGraw-Hill Ryerson Limited Transactional Data & Analytical Information Moving up through the organizational pyramid, users move from requiring transactional information to analytical information 2-1 Learning Outcomes 2-2 Figure 2.3

12. 2-12 Copyright © 2011 McGraw-Hill Ryerson Limited Metrics: Measuring Success Metrics – Measurements that evaluate results to determine whether a project is meeting its goals Common Types - –KPIs – Key Performance Indicators –Efficiency and Effectiveness 2-2 Learning Outcomes

13. 2-13 Copyright © 2011 McGraw-Hill Ryerson Limited Benchmarking Benchmark – Baseline values the system seeks to attain Benchmarking – A process of continuously measuring system results, comparing those results to optimal system performance (benchmark values), and identifying steps and procedures to improve system performance 2-2 Learning Outcomes

14. 2-14 Copyright © 2011 McGraw-Hill Ryerson Limited Key Performance Indicators Key performance indicators (KPIs) – The quantifiable metrics a company uses to evaluate progress toward critical success factors –Turnover rates of employees –Number of product returns –Number of new customers –Average customer spending 2-2 Learning Outcomes

15. 2-15 Copyright © 2011 McGraw-Hill Ryerson Limited Efficiency and Effectiveness Metrics Efficiency metrics – Measure the performance of IS itself, such as throughput, transaction speed, and system availability Effectiveness metrics – Measures the impact IS has on business processes and activities, including customer satisfaction and customer conversation rates 2-2 Learning Outcomes

16. 2-16 Copyright © 2011 McGraw-Hill Ryerson Limited Common Types of Efficiency IS Metrics Throughput The amount of information that can travel through a system at any point in time. Transaction Speed The amount of time a system takes to perform a transaction. System Availability The number of hours a system is available for users. Web Traffic Includes a host of benchmarks such as the number of pages viewed, the number of unique visitors and the average length of viewing time. Response Time The time it takes to respond to interactions such as a mouse click. 2-2 Learning Outcomes

17. 2-17 Copyright © 2011 McGraw-Hill Ryerson Limited Common Types of Effectiveness IS Metrics Usability The ease with which people perform transactions and/or find information. Customer Satisfaction Measured by such benchmarks as satisfaction surveys, customer retention percentages, and increasing revenue per customer. Conversion Rates The number of customers an organization “touches” for the first time and persuades to purchase a product/service. Financial Such as Return on Investment (the earning power of an organization’s assets), Cost/Benefit Analysis and Break Even Analysis. 2-2 Learning Outcomes

18. 2-18 Copyright © 2011 McGraw-Hill Ryerson Limited Efficiency and Effectiveness Metrics Efficiency and Effectiveness metrics are interrelated. The ideal operation occurs in the upper right corner. 2-2 Learning Outcomes Figure 2.7

19. 2-19 Copyright © 2011 McGraw-Hill Ryerson Limited Transaction Processing Systems Transaction processing system (TPS) – Basic business system that serves the operational level and assists in making structured decisions Online transaction processing (OLTP) - Capturing of transaction and event information using technology to process, store, and update Source document – The original transaction record 2-2 Learning Outcomes

20. 2-20 Copyright © 2011 McGraw-Hill Ryerson Limited Decision Support Systems Decision support system (DSS) – Models information to support managers and business professionals during the decision-making process Online analytical processing (OLAP) – Manipulation of information to create business intelligence in support of strategic decision making 2-1 Learning Outcomes 2-2

21. 2-21 Copyright © 2011 McGraw-Hill Ryerson Limited Decision Support Systems Three quantitative models used by DSS include 1.What-if analysis 2.Sensitivity analysis 3.Goal-seeking analysis 2-2 Learning Outcomes

22. 2-22 Copyright © 2011 McGraw-Hill Ryerson Limited Decision Support Systems 2-2 Learning Outcomes Figure 2.8 What-If Analysis in Microsoft Excel

23. 2-23 Copyright © 2011 McGraw-Hill Ryerson Limited Decision Support Systems 2-2 Learning Outcomes Figure 2.9 Goal-Seeking Analysis

24. 2-24 Copyright © 2011 McGraw-Hill Ryerson Limited Decision Support Systems 2-2 Learning Outcomes Figure 2.10 Interaction Between TPSs and DSSs

25. 2-25 Copyright © 2011 McGraw-Hill Ryerson Limited Executive Information Systems Specialized DSS supporting executive decision- making. 2-2 Learning Outcomes Figure 2.11

26. 2-26 Copyright © 2011 McGraw-Hill Ryerson Limited Executive Information Systems Information Levels Throughout An Organization 2-2 Learning Outcomes

27. 2-27 Copyright © 2011 McGraw-Hill Ryerson Limited Digital Dashboards Digital dashboard – integrates information from multiple components and presents it in a unified display 2-2 Learning Outcomes

28. 2-28 Copyright © 2011 McGraw-Hill Ryerson Limited Digital Dashboards Verison’s “Wall of Shaygan” updates the company’s performance every 15 seconds. 2-2 Learning Outcomes Figure 2.13

29. 2-29 Copyright © 2011 McGraw-Hill Ryerson Limited Artificial intelligence (AI) – Simulates human intelligence such as the ability to reason and learn Intelligent system – Various commercial applications of artificial intelligence 2-3 Learning Outcomes Artificial Intelligence (AI)

30. 2-30 Copyright © 2011 McGraw-Hill Ryerson Limited Artificial Intelligence AI Five most common categories of AI include: Expert systems, Neural Networks, Genetic algorithm, Intelligence Agent and Virtual Reality 1. Expert system – Computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems 2-3 Learning Outcomes

31. 2-31 Copyright © 2011 McGraw-Hill Ryerson Limited Artificial Intelligence (AI) 2.Neural Network – Attempts to emulate the way the human brain works Neural networks are most useful for decisions that involve patterns or image recognition For example its use in the finance industry to discover credit card fraud finding common elements in millions of fraudulent transactions –Fuzzy logic – A mathematical method of handling imprecise or subjective information 2-3 Learning Outcomes

32. 2-32 Copyright © 2011 McGraw-Hill Ryerson Limited Artificial Intelligence 3.Genetic algorithm – An artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem - Shopping bot – Software that will search several retailer websites and provide a comparison of each retailer’s offerings including price and availability 2-3 Learning Outcomes

33. 2-33 Copyright © 2011 McGraw-Hill Ryerson Limited Artificial Intelligence (AI) 4. Intelligent agent – Special-purpose knowledge- based information system that accomplishes specific tasks on behalf of its users 5. Virtual reality - A computer-simulated environment that can be a simulation of the real world or an imaginary world 2-3 Learning Outcomes

34. 2-34 Copyright © 2011 McGraw-Hill Ryerson Limited OPENING CASE QUESTIONS Information Systems Improve Business Processes at Grocery Gateway 1.What information systems are used at Grocery Gateway? Would you classify these systems as TPS, DSS, or EIS? 2.How do these systems support operational, analytical or strategic level decisions? 3.What steps could the company take to leverage the transactional information that is collected by the information systems outlined in the case to help make analytical and strategic decisions for the company? 4.Identify a few key metrics that Grocery Gateway marketing executives might want to monitor on a digital dashboard. How can these metrics be used to improve organizational decision making?

35. McGraw-Hill-Ryerson ©2011 The McGraw-Hill Companies, All Rights Reserved SECTION 2.2 BUSINESS PROCESSES

36. 2-36 Copyright © 2011 McGraw-Hill Ryerson Limited Understanding the Importance of Business Processes Sample Business Processes 2-5 Learning Outcomes

37. 2-37 Copyright © 2011 McGraw-Hill Ryerson Limited Understanding the Importance of Business Processes Customer facing processes – result in a product or service that is received by an organization’s external customer. Business facing processes – are invisible to the external customer but are essential to the effective management of the business 2-5 Learning Outcomes

38. 2-38 Copyright © 2011 McGraw-Hill Ryerson Limited Evaluating Business Processes The Order-to-Delivery Process 2-5 Learning Outcomes Figure 2.17

39. 2-39 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Re-engineering Business process – a standardized set of activities that accomplish a specific task, such as processing a customer’s order Business process improvement – attempts to understand and measure current processes and upgrade them. Business process re-engineering (BPR) – the analysis and redesign of workflow within and between enterprises 2-5 Learning Outcomes

40. 2-40 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Improvement Business Process Improvement is a cyclical activity. Metrics at the end are feedback for a new round of improvements. 2-5 Learning Outcomes Figure 2.19

41. 2-41 Copyright © 2011 McGraw-Hill Ryerson Limited Finding Opportunity Using BPR A company can improve the way it travels the road by moving from foot to horse and then horse to car BPR looks at taking a different path, such as an airplane which ignores the road completely 2-5 Learning Outcomes

42. 2-42 Copyright © 2011 McGraw-Hill Ryerson Limited Finding Opportunity Using BPR Progressive Insurance mobile claims process 2-5 Learning Outcomes Figure 2.22

43. 2-43 Copyright © 2011 McGraw-Hill Ryerson Limited Finding Opportunity Using BPR Types of change an organization can achieve, along with the magnitudes of change and the potential business benefit 2-5 Learning Outcomes Figure 2.23

44. 2-44 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling Business process modeling (or mapping) - The activity of creating a detailed flow chart or process map of a work process showing its inputs, tasks, and activities, in a structured sequence Business process model - A graphic description of a process, showing the sequence of process tasks, which is developed for a specific –As-Is process model –To-Be process model 2-5 Learning Outcomes

45. 2-45 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling As-Is and To-Be Process Model for Ordering a Meal 2-5 Learning Outcomes Figure 2.24

46. 2-46 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling As-Is and To-Be Process Model for Order Fulfillment 2-5 Learning Outcomes Figure 2.25

47. 2-47 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling Customer Service As-Is and To-Be Process Model 2-5 Learning Outcomes

48. 2-48 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Management Business Process Management (BPM) – integrates all of an organization’s business processes to make individual processes more efficient. Key reasons for using BPM: 2-5 Learning Outcomes Figure 2.27

49. 2-49 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling Examples Figure 2.28 Online Sales Process Model 2-5 Learning Outcomes

50. 2-50 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling Examples Online Banking Process Model 2-5 Learning Outcomes Figure 2.29

51. 2-51 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling Examples Order Fulfillment Process Model 2-5 Learning Outcomes Figure 2.30

52. 2-52 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling Examples eBay Buyer Business Process Model 2-5 Learning Outcomes Figure 2.31

53. 2-53 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling Examples eBay Seller Business Process Model 2-5 Learning Outcomes Figure 2.32

54. 2-54 Copyright © 2011 McGraw-Hill Ryerson Limited Business Process Modelling Examples Business Process Improvement Model 2-5 Learning Outcomes Figure 2.26

55. 2-55 Copyright © 2011 McGraw-Hill Ryerson Limited OPENING CASE QUESTIONS Information Systems are Central at Grocery Gateway 5.What does Grocery Gateway’s customer order process look like? 6.Describe how Grocery Gateway’s customer Web site supports Grocery Gateway’s business processes. 7.Describe how Descartes’ fleet management software improved Grocery Gateway’s logistics business processes. 8.How does the business process affect the customer experience? The company’s bottom line?

56. 2-56 Copyright © 2011 McGraw-Hill Ryerson Limited OPENING CASE QUESTIONS Information Systems Improve Business Processes at Grocery Gateway 9.What other kinds of information systems could be used by Grocery Gateway to improve its business processes? 10.Comment on the need for integration between the various types of information systems at Grocery Gateway. What benefits from integration do you see for the company’s various business processes? What challenges to you think will exist in facilitating such integration?

57. 2-57 Copyright © 2011 McGraw-Hill Ryerson Limited CLOSING CASE ONE Information Systems Are Critical For Take-Off in Canada’s Airline Industry 1.What advantages are there for an airline to use a revenue management system. 2.Are revenue management systems a competitive advantage or simply a new necessity for doing business in the airline industry today? 3.What type of decisions could a revenue management system be used to help make? 4.Is a revenue management system a TSP, DSS, or an EIS?

58. 2-58 Copyright © 2011 McGraw-Hill Ryerson Limited CLOSING CASE ONE Information Systems Are Critical For Take-Off in Canada’s Airline Industry 5.Would the revenue management system described in the case contain transactional data or analytical information? 6.What types of metrics would an airline executive want to see in a digital dashboard displaying revenue information? 7.How could AI enhance the use of an airline’s revenue management system for decision support?

59. 2-59 Copyright © 2011 McGraw-Hill Ryerson Limited CLOSING CASE TWO Leveraging the Power and Avoiding the Pitfalls of BPM 1.How can BPM help improve global outsourcing? Records management? Supply chain management? 2.What other business activities are excellent candidates for BPM? 3.Which of the five pitfalls mentioned above do you think is the most important? Why? 4.Which of the five pitfalls mentioned above do you think is the most common pitfall that organizations face when undergoing BPM? Why? 5.What is the advantage of treating BPM as a project, as opposed to some other type of business activity?

60. 2-60 Copyright © 2011 McGraw-Hill Ryerson Limited CLOSING CASE THREE Improving Business Processes at UK’s Woburn Safari Park 1.What were the benefits of creating “As-Is” models of current business processed at WSP? 2.How did information systems help identify problem areas in the feed logistics process? 3.How did information systems help improve the management of feed logistics? 4.Are information systems necessary for business process improvements? Explain.