Module 1

1. Module 1 MIS Hot Topics and IT For Better Decision Making Dr. Venkatraman

2. HOT TOPICS IT tools MUST be aligned with Business Needs Decision Making Tools (Module 1) TPS, MIS, DSS, EIS, AI-Based tools Collaborative Tools (Module 2) Web 2.0 (Wiki, YouTube, FaceBook, MySpace, Digg) Allows users to interactively add/change web content – Security Risk is higher! Integration Tools (Module 2) XML, Web-Services, SOA (Service-Oriented Architecture). Allows the building of new software from existing software (either within, or even outside organization) Dr. Venkatraman

3. Business Value of Improved Decision Making • Measuring the value of improved decision making • Identifyingkeydecisions that may benefit from new system investments that could improvedecisionmaking • Decisions may be • common, routine, and numerous (structured) • Non-routine, not well-understood (Unstructured) • Value of improvingmultitudes of smalldecisions Adds up to a large annual value Dr. Venkatraman

4. Types of Decisions (Next Slide has examples) • Unstructured • Non-routine (novel), not well understood (causes and solutions are not clear), needs judgment • Senior executives • Structured • Routine, understood (known causes and solutions) • Lower level managers • Semistructured: in-between – middle managers Dr. Venkatraman

5. Information Requirements of Key Decision-Making Groups in a Firm Senior managers, middle managers, operational managers, and employees have different types of decisions and information requirements. Dr. Venkatraman

6. Stages in Decision Making The decision-making process can be broken down into four stages. Dr. Venkatraman

7. Quality of Decisions and Decision Making Accuracy – Reflects reality Comprehensiveness – full consideration of all factors Fairness – reflects interests of all stakeholders Speed (efficiency) – Time and other resources Coherence – follows a rational process – can be explained Dueprocess – result of a known decision making process – stakeholders can appeal Dr. Venkatraman

8. Systems and Technologies for Supporting Decisions • Transaction Processing Systems – Keeps record of all Transactions. Very little direct decision making help (TPS). Data feeds into all other systems shown below – so important! • Management information systems (MIS) • Decision-support systems (DSS) • Executive support systems (ESS) • Group-decision support systems (GDSS) • Intelligent techniques (ArtificialIntelligence – Expert Systems, Fuzzy Logic, Neural Nets, Genetic Algorithms, etc.) Dr. Venkatraman

9. Management Information Systems (MIS) • Help managersmonitor and control a business • Produce regularreports on performance, such as monthly or annual sales • Sometimes highlight exceptional conditions • Reports often available online • Structured – Semi-Structured Dr. Venkatraman

10. Decision-Support Systems (DSS) • Support semistructured and unstructured problem analysis • Model-driven • Model: Abstract representation of a real phenomenon (ex: The effect of marketing expenditure on Sales, Profitability etc.) • “What-if” analysis • Data-driven (historical and current) • Online analytical processing (OLAP) • Data Mining Dr. Venkatraman

11. Examples of DSS • Burlington Coat Factory: DSS for pricing decisions • Price Optimization(too low – then profits suffer; if too high, loose sales to competition!) • Parkway Corporation: DSS for asset utilization • ImplementedDataMiningandOLAPfor analyzing revenue/profits by parking lots, types of garages (valet, self etc.), damage, customer complaints etc. • CompassBank: DSS for customer relationship management • Built a CRM/Data Warehouse + analyzeddata. Best/worst customers, marketing targets etc. Dr. Venkatraman

12. Data Visualization and Geographic Information Systems (GIS) Data visualization tools Present data in graphical form to help users see patterns and relationships in large quantities of data Geographic information systems (GIS) Use datavisualizationtechnology to analyze and displaydata in the form of digitized maps GIS support decisions that require knowledge about the geographicdistribution of people or other resources (Diseases, Pollution, Oil Reserves, Types of plants/animals, Health-care costs, sales, etc.). Dr. Venkatraman

13. Web-Based Customer Decision-Support Systems (CDSS) • Customer decision-support systems assist customers in the decision-making process • Interactivity and personalization to selectproduct an services • Usuallyweb-based • Intensity of information (consider several factors and lots of information) • Search engines, intelligent agents, online catalogs, Web directories, newsgroups, e-mail, etc. Dr. Venkatraman

14. Executive Support Systems (ESS) • Give senior executives a BIG picture of the overallperformance of an organization • Digital Dashboard • Enable an executive to • zoomin (details) • zoom out (broaderview) • Drill down capability Dr. Venkatraman

15. Interrelationships Among Systems The various types of systems in the organization have interdependencies. TPS are major producers of information that is required by many other systems in the firm, which, in turn, produce information for other systems. These different types of systems have been loosely coupled in most organizations. Figure 2-13 Dr. Venkatraman

16. Group Decision-Support Systems (GDSS) Interactive, computer-based systems that facilitates solving of unstructured problems for a group of decisionmakers Faster Decisions(increased productivity) Better Quality decisions Used in conferencerooms with specialhardware and software Helps setting up meetingtimes, keepminutes of meetings, automaticallysave the activities. Dr. Venkatraman

17. Group Decision-Support Systems (GDSS) Vote Dr. Venkatraman

18. Customer Relationship Management Systems Coordinate all of the businessprocesses that deal with customers to optimizerevenue and customersatisfaction, and increasesales Sales, marketing, and service record data from multiplecommunicationchannels can be combined – Can identify MOST & LEAST profitable customers Saab implemented CRM applications from Siebel Systems to achieve a 360ºview of customers, resulting in a greaterfollow-uprate on salesleads and increasedcustomersatisfaction Dr. Venkatraman

19. CRM- 3600 Customer View Dr. Venkatraman

20. Supply Chain Management Systems • Aim to move the correctamount of product from source to point of consumption as quickly as possible and at the lowestcost • Used by firms to managerelationships with suppliers, purchasing firms, distributors, and logisticscompanies through shared information about orders, production, inventory levels, and more • Early detection of Problems or Opportunities • Lessen Uncertainty (Less Inventories) • More Responsive to Market Changes • Makes Company more efficient and decision making more effective Dr. Venkatraman

21. Intelligent Systems for Decision Support • Artificial intelligence (AI) – enable computers to display intelligence normally associated by humans. • Expert systems – rules and the processingsteps - gleaned from an “expert” (see next slide) • Knowledge base (contains rules) • Inference engine (processes data/rules) • Knowledge engineer (extracts expert knowledge) • Very domain specific – cannot solve other problems Dr. Venkatraman

22. Expert System Rules Dr. Venkatraman

23. CBR - Some Expert systems use Case-basedreasoning (CBR) instead of explicit rules – use pastcases to solvesimilarnewProblems Dr. Venkatraman

24. Fuzzy Logic for Decision Support • Allows computer systems to makedecisions based on vagueconcepts (Sometimes, maybe, normally, warm etc..) – A “smart” thermostat for a HVAC system below: Dr. Venkatraman

25. Neural Networks for Decision Support • Good for solvingcomplex, poorlyunderstoodproblems with largecollection of data. • Findpatterns by buildingmodels, searching for relationships – iteratively with selffeedback – until an acceptablesolution has emerged! • Not aimed at specific solutions – a more generalized intelligence Dr. Venkatraman

26. Genetic Algorithms for Decision Support Based on Darwin’s “Survival of the fittest” theory – more adaptivespeciessurvive - rest get extinct! Mimics the process of evolution. Solutions for complexproblems are tried, combined reproduce), altered (mutated) – and only the bettersolutionssurvive – bad solutions die - until the bestemerges! Like Neural networks – the system is self-learning – not every step is programmed! EXAMPLES: GE uses it to help optimize design of jet engines – each design deals with more than 100 variables I2 Technologies software (Supply Chain Software vendor) – uses genetic algorithms to schedule productions (using 1000s of variables) Dr. Venkatraman

27. Intelligent Agents for Decision Support Intelligent Agents in P&G’s Supply Chain Network Intelligent agents are helping Procter & Gamble shorten the replenishment cycles for products, such as a box of Tide. Dr. Venkatraman

28. Systems for Managing Knowledge – Knowledge Management Knowledge management: business processes developed for creating, storing, transferring, and applyingknowledge Enterprise-Wide Knowledge Management Systems • Structured knowledge systems • Semistructured knowledge systems • Knowledge network systems • Portals, collaboration tools, and learning management systems Dr. Venkatraman

29. Structured knowledge systems • Structured Knowledge: Explicit knowledge found in formaldocuments and formalrules that organizations derive by observingexperts making their decisions. • Categorize the Structured knowledge • Tagging them • Store • Allow for easyretrieval at the righttime by employees. Dr. Venkatraman

30. Semi-structured knowledge systems UnStructured Knowledge: Implicit DIGITAL information with NOformaldocuments or rules 80% of knowledge is Unstructured Also called “Tacit” knowledge Information in folders, memos, emails, slidepresentations, videos etc Software tools are being created to manage this important knowledge. Dr. Venkatraman

31. Semi-structured knowledge systems Hummingbird’s Integrated KM system Dr. Venkatraman

32. Knowledge Network Systems • Expertise located in the memory of human experts – nodocumentation • Tacit Knowledge • System catalogsexperts – who they are, what they know, how to contact them etc. • Provide onlineaccess to search and browse catalog Dr. Venkatraman

33. Systems for Managing Knowledge – Knowledge Management • Portals & Collaboration Tools • A web page through which employees can • access knowledge management systems, documents, • Use collaboration features such as email, Instant messaging (IM), chat, videoconferencing etc. • Learning Management Systems (LMS) • Use tools for employee learning, training, and assessment Dr. Venkatraman

34. Stikeman Elliott Computerizes Its Brainpower Describes how a knowledge-intensive law firm having employees, offices, and knowledge resources distributed in many different locations implemented Hummingbird tools to help it leverage this knowledge and use it more efficiently. Problems: Stikeman Elliott is a knowledge-intensive law firm having employees, offices, and knowledge resources distributed in many different locations. Stikeman Elliott needed an effective knowledge management (KM) system to enable the firm’s lawyers to be moreproductive and contribute to sustaining the growth of the firm over the long term. Knowledgecritical to lawyers are precedents, which can include documents, forms, guidelines, and best practices. The firm needed to find a way to document this information into a system that was accessible to everyone. Knowledge is recognized as a valuable commodity and it resides in the brains of the employees. Stikeman Elliott wanted a way to harness and document this “humanknowledge” Challenges: Need to find a way to leverage the firm’s knowledge and to enable them to use it more effectively. Create and maintain their culture by finding the bestway to share the vastrepositories of knowledge that reside in the brains of the lawyers and in the documents and files that the lawyers have been collecting throughout their careers. Develop a system that could be used by everyone in the organization. Continue to seek ways to promote a culture of initiative and high-performance standards that they felt gave them their competitive advantage. Solutions to solve these problems? Stikeman Elliott selected HummingbirdEnterpriseWebtop from Hummingbird Ltd. to build a portal for the firm’s corporate intranet - a knowledge management system that was able to meet their needs. Stikeman Elliott was also able to integrate the portal closely with its documentmanagementsystem. Dr. Venkatraman

35. Stikeman Elliott Computerizes Its Brainpower How did implementing Hummingbird address these problems? All of the firm’s lawyers have easy access to the firm’s knowledge assets, including important precedents, through a singleaccesspoint using a Webbrowser. They formed a very effective team that included library staff and law clerks in addition to lawyers. The team emphasized the importance of the human presence in KM and keeps in close contact with the firm’s lawyers to make sure that they have access to the knowledge they need. A humansubjectmatterexpert also reviewscontent that has been added and categorized by automated procedures, which ensures the quality of the information. How successful was the solution? The knowledge management system selected and implemented by Stikeman Elliott has proven to be very successful. Items listed in the case are as follows: System includes an expertisedatabase, which identifieslawyers with proficiency in specific areas. Portal codifies the generation and organization of new precedents Portal provides access to vital resource required by junioremployees. The system encourages the sense of community that Stikeman Elliott wish to foster in its firms by growing organically rather than through mergers or acquisitions. Allemployees within the firm have access to the sameresources. With everyone on equal footing, the multiple-office structure maintains the feel of a single organization. Increased level of communication among the offices prevents lawyers from duplicatingwork that has already been done. MORE.. In Next Slide Dr. Venkatraman

36. Stikeman Elliott Computerizes Its Brainpower Lawyers can customize the portal’shomepage so that they have quick access to the information they need most. Portal is closelyintegrated with its documentmanagementsystem. This enables employees to use the search engine to search through the firm’s document repository and internal legal and business content, including e-mail, and some external resources, such as LexisNexis. To assist busy lawyers, tools have been built to assist them in populating the knowledge database. Lawyers can easilycreateWebsites for their cases, clients, and industryresearch. Portal has extranetcapabilities that enable the company to create sites on which clients can review and work with documents pertaining to their cases in a collaborative manner. Dr. Venkatraman