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Mgt 20600: IT Management & Applications Decision Support Systems Tuesday April 11, 2006.

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Presentation on theme: "Mgt 20600: IT Management & Applications Decision Support Systems Tuesday April 11, 2006."— Presentation transcript:

1 Mgt 20600: IT Management & Applications Decision Support Systems Tuesday April 11, 2006

2 Reminders  Reading –For today  Fundamentals text, Chapter Six, Information and Decision Support Systems –For next class on April 18 th  Fundamentals text, Chapter Five, Electronic Commerce and Transaction Processing Systems  Homework –Homework Four  Databases  Due this Thursday, April 14 th, by 5pm –Homework Five  Decision Support Systems  Due Friday, April 21 st by 5pm  Exam 2 –Tuesday, April 25 th –75 points –Similar types of questions as on Exam 1 –Covers Telecom & Networks, Databases, Decision Support Systems  Next week: Electronic Commerce

3 Data Warehouses, Data Marts, and Data Mining  Data warehouse: collects business information from many sources in the enterprise  Data mart: a subset of a data warehouse  Data mining: an information- analysis tool for discovering patterns and relationships in a data warehouse or a data mart

4 Data Warehouses, Data Marts, and Data Mining Elements of a Data Warehouse

5 Data Warehouse Example  Home Depot in 2002 launched a 48 terabyte IBM DB2 data warehouse  Contains three years of sales history  The warehouse is intended to take the guesswork out of labor scheduling as well as inventory planning  Lowe's has had a Teradata warehouse with that functionality since 2000

6 Data Warehouse Example  Premier Inc. sells access to clinical data it gathers from 400 hospitals to pharmaceutical manufacturers  Last year, the company's IBM Red Brick data warehouse had grown to 3TB  One table included 3 billion entries  "When you go through 3 billion rows of data, you get long runtimes," says Chris Stewart, director of data warehouse architecture.  The problem wasn't just the size of the database, however, but how clients used the data.  "Our users want to access all of the data from top to bottom," says Stewart  The complex, multipass queries created by Premier's 4,000 users each week were slowing performance. Some wouldn't run at all  Stewart brought in an all-inclusive data warehouse appliance from Netezza Corp. in Framingham, Mass  Some calculations that took one or two days now finish in six to eight minutes on the appliance's 108 processors

7 Data Mart Example  ACNielsen's Paris offices  Customers are interested in very specific subsets of data and specific aggregations  ACNielson has produced thousands of data marts as part of a project called the Data Mart Factory  4TB master data warehouse that includes regularly updated data from retailers  Runs it through a system that cranks out 3,000 client-specific data marts that ACNielsen presents to 1,000 customers in the retailing and consumer product manufacturing industries  Each data mart is refreshed weekly

8 Data Warehouses, Data Marts, and Data Mining Common Data-Mining Applications

9 Data Mining Example 7-Eleven  Keyes' eyes were opened to the strategic importance of IT during a trip he made in 1990 to visit 7-Eleven's licensees in Japan  Stores customized their offerings to local demand and by the assortment of fresh foods they offered, from sushi to sandwiches  The Japanese did it with scanning data, rudimentary data warehouses and a nascent in-store ordering system  When he became CEO, Keyes knew that the U.S. stores had to do the same

10 Data Mining Example  Online retailer Inc. has begun connecting users to a real-time data warehouse it completed last month  The project's goal is to help employees gain insight into the effectiveness of the company's online and e-mail advertising campaigns.  Overstock is using transactional data management tools from GoldenGate Software Inc. to pull information directly from its business systems into the data warehouse  Now the data warehouse receives Web site clickstream data in real time, financial and product-sales data every 15 minutes and other information hourly.  "When we launch campaigns now, we can look within five minutes and see if they are producing lift or revenue that would not normally have happened," Garcella said.  "You can't wait until the next day or three hours later to get that data."

11 Online Analytical Processing (OLAP)  Software that allows users to explore data from a number of different perspectives Comparison of OLAP and Data Mining

12 OLAP in Depth  One core software tool is online analytical processing (OLAP)  Extracts, structures and stores warehoused data to enable quick, multidimensional analysis  A dimension can be any variable your company tracks: customer locations, sales volumes, product development costs and so on  An OLAP data set is made up of dimensions and measures, which can then be used for queries to elicit detailed data breakdowns and information on associations among variables  For example, a grill manufacturer could use an OLAP query to correlate grill sales with weather conditions across various locations, to determine how heat waves affect its business in different regions.

13 Business Intelligence  Business intelligence (BI): gathering the right information in a timely manner and usable form and analyzing it to have a positive impact on business  Knowledge management: capturing a company’s collective expertise and distributing it wherever it can help produce the biggest payoff

14 Business Intelligence Example  Continental Airlines Inc. from worst to first.  BI that Continental gleaned from its customers helped move it from last place in travelers' opinions nine years ago to the winner of this year's award for best airline from London-based OAG Worldwide Ltd.  The first move Continental made to improve frequent-flier relations back in the mid-'90s was to consolidate 55 databases worldwide into a single Teradata data warehouse  "We wanted one voice of the customer “  The goal was to identify high-yield customers, create loyalty programs and get more immediate data on the cost of each flight  Flight attendants now receive information from the data warehouse about high-value customers on a flight so they can personally express the airline's interest in and knowledge about the customers' recent flying experiences with Continental  The company's financial analysts can get information about the profitability of each flight instantly after "wheels up," Cook says.  In the future, Continental wants the data warehouse to use real- time clickstream data to automatically generate targeted offers to Continental's Web site visitors.

15 Business Intelligence Example  Data warehouse cuts costs for... cost-conscious Southwest Airlines Co  The Dallas-based carrier centralized its BI group two years ago around a Teradata data warehouse in order to keep a lid on IT costs through better systems management and more efficient staffing policies  "We're the low-cost airline, so we should have a low-cost infrastructure"  Besides helping to hold down IT spending, the 2TB data warehouse helps business analysts cut corporate costs  Annual savings from ideas generated through use of the data warehouse at between $1.2 million and $1.4 million  As a result of that success, the data warehouse is destined to grow. It will increase to 3TB by next summer and possibly double that volume by 2007.  IT team is developing better ways of handling ad hoc query requests from end users and creating dashboard-style tools for the airline's executives.

16 Management Information Systems in Perspective  A management information system (MIS) provides managers with information that supports effective decision making and provides feedback on daily operations  The use of MISs spans all levels of management

17 Management Information Systems in Perspective Sources of Managerial Information

18 Inputs to a Management Information System  Internal data sources –TPSs and ERP systems and related databases; data warehouses and data marts; specific functional areas throughout the firm  External data sources –Customers, suppliers, competitors, and stockholders, whose data is not already captured by the TPS; the Internet; extranets

19 Outputs of a Management Information System  Scheduled report: produced periodically, or on a schedule  Key-indicator report: summary of the previous day’s critical activities  Demand report: developed to give certain information at someone’s request  Exception report: automatically produced when a situation is unusual or requires management action  Drill-down report: provides increasingly detailed data about a situation

20 Functional Aspects of the MIS  Most organizations are structured along functional lines or areas  The MIS can be divided along functional lines to produce reports tailored to individual functions

21 Functional Aspects of the MIS The MIS is an integrated collection of functional information systems, each supporting particular functional areas.

22 Financial Management Information Systems  Financial MIS: provides financial information to all financial managers within an organization –Profit/loss and cost systems –Auditing –Uses and management of funds

23 Financial Management Information Systems Overview of a Financial MIS

24 Manufacturing Management Information Systems  The manufacturing MIS subsystems and outputs monitor and control the flow of materials, products, and services through the organization –Design and engineering –Production scheduling –Inventory control –MRP (material requirements planning) –Process control –Quality control

25 Manufacturing Management Information Systems Overview of a Manufacturing MIS

26 Marketing Management Information Systems  Marketing MIS: supports managerial activities in product development, distribution, pricing decisions, promotional effectiveness, and sales forecasting –Marketing research –Product development –Promotion and advertising –Product pricing

27 Marketing Management Information Systems Overview of a Marketing MIS

28 Human Resource Management Information Systems  Human resource MIS: concerned with activities related to employees and potential employees of an organization –Needs and planning assessments –Recruiting –Training and skills development –Scheduling and assignment –Employee benefits –Outplacement

29 Human Resource Management Information Systems Overview of a Human Resource MIS

30 Other Management Information Systems  Accounting MIS: provides aggregate information on accounts payable, accounts receivable, payroll, and many other applications  Geographic information system (GIS): capable of assembling, storing, manipulating, and displaying geographic information

31 Decision Making as a Component of Problem Solving How Decision Making Relates to Problem Solving

32 Decision Making as a Component of Problem Solving  Decision-making phase: first part of problem-solving process –Intelligence stage: potential problems or opportunities are identified and defined –Design stage: alternative solutions to the problem are developed –Choice stage: a course of action is selected

33 Decision Making as a Component of Problem Solving  Problem solving: a process that goes beyond decision making to include the implementation stage  Implementation stage: a solution is put into effect  Monitoring stage: decision makers evaluate the implementation

34 Programmed Versus Nonprogrammed Decisions  Programmed decisions –Decisions made using a rule, procedure, or quantitative method –Easy to computerize using traditional information systems –Example?  Nonprogrammed decisions –Decision that deals with unusual or exceptional situations –Not easily quantifiable –Example?

35 Optimization, Satisficing, and Heuristic Approaches  Optimization model: a process that finds the best solution, usually the one that will best help the organization meet its goals  Satisficing model: a process that finds a good—but not necessarily the best— problem solution  Heuristics: commonly accepted guidelines or procedures that usually find a good solution

36 An Overview of Decision Support Systems  A DSS is an organized collection of people, procedures, software, databases, and devices used to support problem-specific decision making and problem solving  The focus of a DSS is on decision- making effectiveness when faced with unstructured or semistructured business problems

37 Capabilities of a Decision Support System Capabilities of a Decision Support System  Support all problem-solving phases  Support different decision frequencies  Support different problem structures  Support various decision-making levels

38 Capabilities of a Decision Support System (continued) Decision-Making Level

39 A Comparison of DSS and MIS Comparison of DSSs and MISs

40 A Comparison of DSS and MIS (continued) Comparison of DSSs and MISs

41 Components of a Decision Support System Conceptual Model of a DSS

42 Components of a Decision Support System  Database  External database access  Access to the Internet and corporate intranet, networks, and other computer systems  Model base: provides decision makers access to a variety of models and assists them in decision making  Dialogue manager: allows decision makers to easily access and manipulate the DSS and to use common business terms and phrases

43 Intelligence Phase Support: Excel and Access  Excel –List capabilities: Sorting, filtering –Pivot tables –Charting  Access –Queries –Reports

44 Design Phase Support: Excel  Excel –What if analysis  Data tables  Scenario manager

45 Stages of the Decision Making Process: Choice  Selecting a course of action –Excel  Solver –Expert systems  Intended to perform at the level of a human expert in a particular domain –Decision Tree Analysis  Add-in to Excel that facilitates construction of decision trees

46 Common Expert System Architecture User Knowledge Engineer User Interface Inference Engine Knowledge Base User Environment Development Environment Blackboard Documented Knowledge Expert Knowledge

47 Decision Tree Analysis Output

48 Group Support Systems  Group support system (GSS) –Consists of most elements in a DSS, plus software to provide effective support in group decision making –Also called group decision support system or computerized collaborative work system

49 Characteristics of a GSS That Enhance Decision Making  Special design  Ease of use  Flexibility  Decision-making support  Anonymous input  Reduction of negative group behavior  Parallel communication  Automated record keeping

50 GSS Software  Often called groupware or workgroup software  Helps with joint workgroup scheduling, communication, and management  Examples: Lotus Notes, Microsoft’s NetMeeting, Microsoft Exchange, NetDocuments Enterprise, Collabra Share, OpenMind, TeamWare

51 GSS Alternatives

52 The GSS Decision Room

53 Group Support System Example  Meeting, Brainstorming, and Decision Making Tools for groups Meeting, Brainstorming, and Decision Making Tools for groups Meeting, Brainstorming, and Decision Making Tools for groups

54 Executive Support Systems  Executive support system (ESS): specialized DSS that includes all hardware, software, data, procedures, and people used to assist senior-level executives within the organization

55 Executive Support Systems in Perspective  Tailored to individual executives  Easy to use  Drill-down capable  Support the need for external data  Can help when uncertainty is high  Future-oriented  Linked to value-added processes

56 Capabilities of Executive Support Systems  Support for defining an overall vision  Support for strategic planning  Support for strategic organizing and staffing  Support for strategic control  Support for crisis management

57 Executive Support Systems –Xcelsius Xcelsius –Executive Dashboard Executive DashboardExecutive Dashboard  Identify, track, trend, and correct problems as managers evaluate the health of key areas of their organization  Identify operational efficiencies  Proactively identify and apply corrective measures

58 Executive Dashboard Features Dashboard Screen: The dashboard page displays the overall health of key performance indicators. Each box represents a key performance indicator (KPI) and the health for corresponding periods. The default executive dashboard shown can be unique to the individual logged in, or shared by the entire organization.

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