Enhancing Management Decision Making for the Digital Firm

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5 Chapter 12 Enhancing Management Decision Making for the Digital Firm 12.1 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا سوه How can information systems help individual managers make better decisions when the problems are nonroutine and constantly changing? . How can information systems help people working in a group make decisions more efficiently? ©0006 by Prevace “I 1 12.2 

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و مدا مس ما ۱ ا سوه Are there any special systems that can facilitate decision making among senior managers? Exactly what can these systems do to help high-level management? What value can systems to support management decision making provide for the organization as a whole? ©0006 by Prevace “I 3) 4. 12.3 

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و مدا مس ما ۱ ا Oe Ola ree 1. Building information systems that can actually fulfill executive information requirements 2. Create meaningful reporting and management decision-making processes 12.4 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) * Computer system at the management level of an organization ٠ Combines data, analytical tools, and models * Supports semistructured and unstructured decision making 125 ©0008 by Prevece We 

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و مدا مس ما ۱ ا 00 rece (NCIC) O16 wad DOC MIS ٠ Provides reports based on routine flow of data * Assists in general control of the organization 12.6 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) O16 wad DOC DSS * Emphasizes change, flexibility, rapid response, models, assumptions, ad-hoc queries, and display graphics 12.7 ©0008 by Prevece We 

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و مدا مس ما ۱ ا 00 rece (NCIC) Types of Orv Cupp Cystews Model-Driven DSS * Primarily stand-alone ¢ Uses model to perform “what-if” and other kinds of analysis 12.8 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) Types of Orv Cupp Cystews * Data-driven DSS: Supports decision making by allowing users to extract and analyze useful information previously buried in large databases ۰ Datamining: Finds hidden patterns and relationships in large databases to infer rules from them and predict future behavior ما سم ‎by‏ 0008© 12.9 

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و مدا مس ما ۱ ا 00 rece (NCIC) Ordo oa Orquctraious Data Drive Customer Care at Intrawest * How does this customer care DSS help Intrawest make decisions? ¢ How has it provided value for the firm? 12.10 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) 12.11 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) Types of Orv Cupp Cystews ¢ Associations: Occurrences linked to a single event * Sequences: Events linked over time ما سم ‎by‏ 0008© 12.12 

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و مدا مس ما ۱ ا 00 rece (NCIC) Types of Orv Cupp Cystews * Classification: Recognizing patterns that describe the group to which an item belongs * Clustering: Similar to classification when no groups have yet been defined. Discovers different groupings within data pie ©0008 by ‏ما سم‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) Overview ۴ ۰ ‏جمججمووط‎ svete (DOO) Overview of a decision-support system (DSS) eno foes rower Peo Prue (6-0 12.14 ©0008 by ‏ما سم‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) Cowpens oP OGG * DSS Database: Collection of current or historical data from a number of applications or groups. Can be a small PC database or a massive data warehouse 12.15 ©0008 by Prevece We 

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و مدا مس ما ۱ ا 00 rece (NCIC) Cowpens oP OGG * DSS Software System: Collection of software tools used for data analysis, such as OLAP tools, datamining tools, or a collections of mathematical and analytical models 12.16 ©0008 by Prevece We 

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‎ae‏ متا مس ما متا مت ماس اس مس رس ده وت وت 7 ‎ ‎00 ‎Cowpens oP OGG ‎* Model: Abstract representation illustrating components or relationships of a phenomenon ‎¢ Sensitivity Analysis: Models that ask “what-if” questions repeatedly to determine the impact of changes in one or more factors on the outcomes ‎12.17 ©0008 by Prevece We 

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و مدا مس ما ۱ ا 00 rece (NCIC) otal fixed costs 19000 Variable cost per unit 3 Average sales price 17 Contribution margin 14 Breakeven point 1387 Variable Cost per Unit Sales 1387 2 3 4 5 0 ‎Price [14 ۱583 ۰ ۱727 ۰ 1900212378‏ ۷ ۰ 199۵ ۰ ۱727 ۰ ۱5۵3 ۰ 1462 وا ۵ ۰ ۱727 . ۱583 14642 ۱397 ۱6 ۶ ۰ ۱588 ۱4۵2 . ۱3۶7 ۱260 ۱7 35714621583 12647 1188 18 و سب ‎12.18 ©0008 by Preece ‏ادنلا"‎ ‎ ‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) OCG Opphectow wad the Digit Piro Examples of Decision-Support Systems * General Accident Insurance: Customer buying patterns and fraud detection ¢ Bank of America: Customer profiles ¢ Frito-Lay, Inc.: Price, advertising, and promotion selection 12.19 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) OCG Opphectocs werd the ‏مسو لب‎ Examples of Decision-Support Systems * Southern Railway: Train dispatching and routing * Texas Oil and Gas Corporation: Evaluation of potential drilling sites ٠ The Gap: Inventory stocking and merchandising 12.20 ©0008 by Preece ‏ادنلا"‎ 

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‎eae Mi ems ca ee‏ را تست ا 4 ‎ ‎00 rece (NCIC) ‎OCG Opphectow wad the Digit Piro ‎Examples of Decision-Support Systems ‎* United Airlines: Flight scheduling, passenger demand forecasting ‎¢ U.S. Department of Defense: Defense contract analysis ‎12.21 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) OGG Por Prictry Devoe * By analyzing several years of sales data for similar items, the software estimates a “seasonal demand curve” for each item and predicts how many units would sell each week at various prices. ¢ The software uses sales history to predict how sensitive customer demand will be to price changes 12.22 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) اجه( 0۵ راب6 ۴ 0866 * Can help firms model inventory stocking levels, production schedules, or transportation plans * Can provide firms with information on key performance indicators such as lead time, cycle time, inventory turns, or total supply chain costs 12.23 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) Ondow va Teck A DSS Makes Subaru More Parts- Savvy * How does the Servigistics system provide value for Subaru of New England? * How did it change the way the company ran its business? 12.24 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) O66 Por net wer wet wad secre Analysis Use statistical analysis. to dently the top 25% of frequent shoppers Establish correlation between location and sales frequency Verify new customer segmencs * frequent customers not living near a store + frequent customers living near a store ‘infrequent customers living near a store Query the database for detailed information fon each customer ©0006 by Prevace “I Questions |.Who are our most. <——>| ‏جما‎ ‎frequent customers? eee 2, Do they ie close ro ‘our retail outlets? ‏ده‎ ‎3. How can we re-segment those customers? 4, How can we berter reach those segments? 06-6 سب 12.25 

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و مدا مس ما ۱ ا 00 rece (NCIC) OGG Por Cwtewer Rettiowhip )1( ‏مجه‎ Predictive Analysis ٠ Use of datamining techniques, historical data, and assumptions about future conditions to predict outcomes of events 12.26 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 00 rece (NCIC) ‎Booyropht “Purana Oystrws (B10)‏ لب سح م۳ ‎Data Visualization: Technology for helping users see patterns and relationships in large amounts of data by presenting the data in graphical form. ‎Geographic Information System (GIS): System with software that can analyze and display data using digitized maps to enhance planning and decision making ‎©0008 by Preece ‏ادنلا"‎ ‎ ‎12.27 

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و مدا مس ما ۱ ا 00 rece (NCIC) Orb-Bwsred Owtower Dever Oupport Gystews Customer Decision-Support System (CDSS) ٠ System to support the decision- making process of an existing or potential customer 12.28 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 0 ۵۳ ۰ 7 Group Decision-Support System (GDSS): An interactive computer- based system to facilitate the solution to unstructured problems by a set of decision makers working together as a group ©0008 by Preece ‏ادنلا"‎ 12.29 

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و مدا مس ما ۱ ا 0 06 ۶و 0 Hardware: Conference facility, electronic hardware Software tools: Tools for organizing ideas, gathering information, and ranking and seeking priorities People: Participants, trained facilitator, staff supporting hardware and software ©0006 by Prevace “I 12.30 

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و مدا مس ما ۱ ا 0 06 ۶و 0 * Electronic questionnaires ٠ Electronic brainstorming tools ۰ Idea organizers ٠ Questionnaire tools 12.31 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 0 06 ۶و 0 ٠ Tools for voting or setting priorities ٠ Stakeholder identification and analysis tools ¢ Policy formation tools ¢ Group dictionaries 12.32 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 0 Overvew oP a BOO Ovvtey ٠ Each attendee has a workstation ٠ Workstations are networked and connected to the facilitator’s console ٠ Data the attendees forward to the group are collected and saved on a file server ٠ Facilitator projects computer images onto the projection screen 12.33 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 0 ع ] 06-6 صعب ما" ‎by Previce‏ 0008© 12.34 

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و مدا مس ما ۱ ا 0 ‘Low BOC Cus 1۶ Crow Devers Dchiery ¢* Number of attendees can increase while productivity increases ¢ More collaborative atmosphere ٠ Software tools follow structured methods for organizing and evaluating ideas and preserving the results of meetings 12.35 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا 0 ‘Low BOC Cus 1۶ Crow Devers Dchiery Increase the number of ideas generated Can lead to more participative and democratic decision making ©0006 by Prevace “I 12.36 

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و مدا مس ما ۱ ا 0 ‘Low BOC Cus 1۶ Crow Devers Dchiery Organizational Memory ٠ Store learning from an organization’s history that can be used for decision making and other purposes 12.37 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا CRC at ‏وه‎ Crovive Gupport Gystews (EGG) ٠ Focus on the information needs of senior management ٠ Combine data from internal and external sources * Create a generalized computing and communications environment that can be focused and applied to a changing array of problems 12.38 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا CRC at ‏وه‎ Crovive Gupport Gystews (EGG) ٠ Monitor organizational performance ٠ Track activities of competitors ٠ Spot problems ٠ Identify opportunities ٠ Forecast trends 12.39 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا CRC at ‏وه‎ The Roe oP @xevutve Gupport Gystews ta the Organization ٠ Bring together data from the entire organization ٠ Allow managers to select, access, and tailor data * Enable executive and any subordinates to look at the same data in the same way 12.40 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا CRC at ‏وه‎ The Roe oP @xevutve Gupport Gystews ta the Organization Drill Down ٠ The ability to move from summary data to lower and lower levels of detail uae ©0008 by Prevece We 

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و مدا مس ما ۱ ا CRC at ‏وه‎ The Roe oP @xevutve Gupport Gystews ta the Organization Developing ESS ٠ Ease of use ٠ Facility for environmental scanning ¢ External and internal sources of information to be used for environmental scanning 12.42 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا CRC at ‏وه‎ ‎Oystews‏ بمب شحو و سس ‎Analyze, compare, and highlight trends ‎Provide greater clarity and insight into data ‎Speed up decision making ‎©0006 by Prevace “I ‎ ‎12.43 

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و مدا مس ما ۱ ا CRC at ‏وه‎ ‎Oystews‏ بمب شحو و سس ‎* Improve management performance ‎٠ Increase management’s span of control ‎٠ Better monitoring of activities ‎12.44 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا CRC at ‏وه‎ Gxevuve Gupport Opstews und the Oigid Piro ESS for Competitive Intelligence ٠ Identify changing market conditions * Formulate responses ٠ Track implementation efforts ¢ Learn from feedback 12.45 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا Oe See Exenive Guppont Gystews und the Died Pro Balanced Scorecard * Model for analyzing firm performance that supplements traditional financial measures with measurements from additional business perspectives, such as customers, internal business processes, and learning and growth 12.46 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا Oe See Crterprie-Onte Reportog wad odor Strategic performance management tools for enterprise systems ٠ SAP: Web-enabled mySAP.com™, Management Cockpit * PeopleSoft: Web-enabled Enterprise Performance Management (EPM) 12.47 ©0008 by Preece ‏ادنلا"‎ 

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و مدا مس ما ۱ ا CRC at ‏وه‎ Crterprie-Onte Reportog wad odor Activity-Based Costing Model for identifying all the company activities that cause costs to occur while producing a specific product or service so that managers can see which products or services are profitable or losing money and make changes to maximize firm profitability ©0008 by Preece ‏ادنلا"‎ 12.48 

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و مدا مس ما ۱ ا س8 د02 © ۱9 Land's vat Ookeqaa Gua: ® Te ۴ ۲ ‏مب‎ 008 Analyze Harrah’s and Mohegan Sun using the competitive forces and value chain models. Compare the business strategies of Harrah’s and Mohegan sun. What role do customer reward systems play in these strategies? How are they similar? How are they different? ©0006 by Prevace “I 1. 12.49 

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و مدا مس ما ۱ ا س8 د02 © ۱9 Land's vat Ookeqaa Gua: ® Te ۴ ۲ ‏مب‎ 008 What kind of decision-support systems did Harrah’s and Mohegan Sun develop? How are they related to their business strategy? Are Harrah’s and Mohegan Sun successful? Which casino is more successful? Why? Can its competitive advantage be sustained? Why or why not? Are there any ethical problems raised by these casinos’ use of customer data? Explain your response. ©0006 by Prevace “I 12.50