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11626 Bitt I 2008 Lec 2

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BITT1 Lecture 2

BITT1 Lecture 2

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  • 1.
    • BITT-I
    • LECTURE-2
  • 2. Entity Relationship Diagram
  • 3. Types of Databases
  • 4. Operational Databases
    • Stores detailed data needed to support business processes and operations
      • Also called subject area databases (SADB), transaction databases , and production databases
      • Database examples: customer, human resource, inventory
  • 5. Distributed Databases
    • Distributed databases are copies or parts of databases stored on servers at multiple locations
      • Improves database performance at worksites
    • Advantages
      • Protection of valuable data
      • Data can be distributed into smaller databases
      • Each location has control of its local data
      • All locations can access any data, any where
    • Disadvantages
      • Maintaining data accuracy
  • 6. External Databases
    • Databases available for a fee from commercial online services, or free from the Web
      • Examples: hypermedia databases, statistical databases, bibliographic and full text databases
      • Search engines like Google or Yahoo are external databases
  • 7. Hypermedia Databases
    • A hypermedia database contains
      • Hyperlinked pages of multimedia
      • Interrelated hypermedia page elements, rather than interrelated data records
  • 8. Cross-Functional Systems
    • Cross the boundaries of traditional business functions
      • Used to reengineer and improve vital business processes all across the enterprise
  • 9. Enterprise Application Architecture
  • 10. Transaction Processing Systems
    • Cross-functional information systems that process data resulting from the occurrence of business transactions
      • Transactions include sales, purchases, deposits, withdrawals, refunds, and payments
      • Online transaction processing (OLTP) is a real-time system that captures transactions immediately
  • 11. The Transaction Processing Cycle
  • 12. What is CRM?
    • Managing the full range of the customer relationship involves
      • Providing customer-facing employees with a single, complete view of every customer at every touch point and across all channels
      • Providing the customer with a single, complete view of the company and its extended channels
    • CRM uses IT to create a cross-functional enterprise system that integrates and automates many of the customer-serving processes
  • 13. Application Clusters in CRM
  • 14. Retention and Loyalty Programs
    • It costs 6 times more to sell to a new customer
    • An unhappy customer will tell 8-10 others
    • Boosting customer retention by 5 percent can boost profits by 85 percent
    • The odds of selling to an existing customer are 50 percent; a new one 15 percent
    • About 70 percent of customers will do business with the company again if a problem is quickly taken care of
  • 15. Retention and Loyalty Programs
    • Enhancing and optimizing customer retention and loyalty is a primary objective of CRM
      • Identify, reward, and market to the most loyal and profitable customers
      • Evaluate targeted marketing and relationship programs
  • 16. Benefits of CRM
    • Benefits of CRM
      • Identify and target the best customers
      • Real-time customization and personalization of products and services
      • Track when and how a customer contacts the company
      • Provide a consistent customer experience
      • Provide superior service and support across all customer contact points
  • 17. CRM Failures
    • Business benefits of CRM are not guaranteed
      • 50 percent of CRM projects did not produce promised results
      • 20 percent damaged customer relationships
    • Reasons for failure
      • Lack of understanding and preparation
      • Not solving business process problems first
      • No participation on part of business stakeholders involved
  • 18. ERP: The Business Backbone
    • ERP is a cross-functional enterprise backbone that integrates and automates processes within
      • Manufacturing
      • Logistics
      • Distribution
      • Accounting
      • Finance
      • Human resources
  • 19. What is ERP?
    • Enterprise resource planning is a cross-functional enterprise system
      • An integrated suite of software modules
      • Supports basic internal business processes
      • Facilitates business, supplier, and customer information flows
  • 20. ERP Application Components
  • 21. Benefits and Challenges of ERP
    • ERP Business Benefits
      • Quality and efficiency
      • Decreased costs
      • Decision support
      • Enterprise agility
    • ERP Costs
      • Risks and costs are considerable
      • Hardware and software are a small part of total costs
      • Failure can cripple or kill a business
  • 22. Costs of Implementing a New ERP
  • 23. Causes of ERP Failures
    • Most common causes of ERP failure
      • Under-estimating the complexity of planning, development, training
      • Failure to involve affected employees in planning and development
      • Trying to do too much too fast
      • Insufficient training
      • Insufficient data conversion and testing
      • Over-reliance on ERP vendor or consultants
  • 24. Supply Chain Management (SCM)
    • Fundamentally, supply chain management helps a company
      • Get the right products
      • To the right place
      • At the right time
      • In the proper quantity
      • At an acceptable cost
  • 25. Goals of SCM
    • The goal of SCM is to efficiently
      • Forecast demand
      • Control inventory
      • Enhance relationships with customers, suppliers, distributors, and others
      • Receive feedback on the status of every link in the supply chain
  • 26. Levels of Managerial Decision Making
  • 27. Decision Structure
    • Structured (operational)
      • The procedures to follow when decision is needed can be specified in advance
    • Unstructured (strategic)
      • It is not possible to specify in advance most of the decision procedures to follow
    • Semi-structured (tactical)
      • Decision procedures can be pre-specified, but not enough to lead to the correct decision
  • 28. Decision Support Systems Information produced by analytical modeling of business data Information produced by extraction and manipulation of business data Information processing methodology Ad hoc, flexible, and adaptable format Prespecified, fixed format Information format Interactive inquiries and responses Periodic, exception, demand, and push reports and responses Information form and frequency Provide information and techniques to analyze specific problems Provide information about the performance of the organization Decision support provided Decision Support Systems Management Information Systems
  • 29. Decision Support Trends
    • The emerging class of applications focuses on
      • Personalized decision support
      • Modeling
      • Information retrieval
      • Data warehousing
      • What-if scenarios
      • Reporting
  • 30. Decision Support Systems
    • Decision support systems use the following to support the making of semi-structured business decisions
      • Analytical models
      • Specialized databases
      • A decision-maker’s own insights and judgments
      • An interactive, computer-based modeling process
    • DSS systems are designed to be ad hoc, quick-response systems that are initiated and controlled by decision makers
  • 31. DSS Components
  • 32. DSS Model Base
    • Model Base
      • A software component that consists of models used in computational and analytical routines that mathematically express relations among variables
    • Spreadsheet Examples
      • Linear programming
      • Multiple regression forecasting
      • Capital budgeting present value
  • 33. Executive Information Systems
    • EIS
      • Combines many features of MIS and DSS
      • Provide top executives with immediate and easy access to information
      • Identify factors that are critical to accomplishing strategic objectives (critical success factors)
      • So popular that it has been expanded to managers, analysis, and other knowledge workers
  • 34. Features of an EIS
    • Information presented in forms tailored to the preferences of the executives using the system
      • Customizable graphical user interfaces
      • Exception reports
      • Trend analysis
      • Drill down capability
  • 35. Business Intelligence Applications
  • 36. Changing Business Environments and Computerized Decision Support
    • The Business Pressures-Responses-Support Model
      • The business environment
      • Organizational responses: be reactive, anticipative, adaptive, and proactive
      • Computerized support
        • Closing the Strategy Gap One of the major objectives of BI is to facilitate closing the gap between the current performance of an organization and its desired performance as expressed in its mission, objectives, and goals and the strategy for achieving them
  • 37. Changing Business Environments and Computerized Decision Support
  • 38. A Framework for Business Intelligence (BI)
    • business intelligence (BI)
    • A conceptual framework for decision support. It combines architecture, databases (or data warehouse), analytical tools and applications
  • 39. A Framework for Business Intelligence
  • 40. A Framework for Business Intelligence (BI)
    • The Origins and Drivers of Business Intelligence
      • Organizations are being compelled to capture, understand, and harness their data to support decision making in order to improve business operations
      • Managers need the right information at the right time and in the right place
  • 41. A Framework for Business Intelligence (BI)
    • BI’s Architecture and Components
      • Data Warehouse
      • Business Analytics
        • Automated decision systems
      • Performance and Strategy
  • 42. A Framework for Business Intelligence (BI)
  • 43. A Framework for Business Intelligence (BI)
    • BI’s Architecture and Components
      • Data Warehouse
      • Business Analytics
        • Automated decision systems
  • 44. A Framework for Business Intelligence (BI)
    • BI’s Architecture and Components
      • Data Mining
      • A class of information analysis based on databases that looks for hidden patterns in a collection of data which can be used to predict future behavior
  • 45. A Framework for Business Intelligence (BI)
    • BI’s Architecture and Components
      • business (or corporate) performance management (BPM)
      • A component of BI based on the balanced scorecard methodology, which is a framework for defining, implementing, and managing an enterprise’s business strategy by linking objectives with factual measures
  • 46. A Framework for Business Intelligence (BI)
    • BI’s Architecture and Components
      • User Interface: Dashboards and Other Information Broadcasting Tools
        • Dashboards
        • A visual presentation of critical data for executives to view. It allows executives to see hot spots in seconds and explore the situation
  • 47. A Framework for Business Intelligence (BI)
    • Time savings
    • Single version of truth
    • Improved strategies and plans
    • Improved tactical decisions
    • More efficient processes
    • Cost savings
    • Faster, more accurate reporting
    • Improved decision making
    • Improved customer service
    • Increased revenue
    • The Benefits of BI
  • 48. A Framework for Business Intelligence (BI)
    • The Business Value of BI
      • How BI Can Help
        • Assess their readiness for meeting the challenges posed by these new business realities
        • Take a holistic approach to BI functionality
        • Leverage best practices and anticipate hidden costs
  • 49. A Framework for Business Intelligence (BI)
    • The Business Value of BI
      • Key Issues and Framework for BI Analysis
        • How can enterprises maximize their BI investments?
        • What BI functionality do enterprises need, and what are they using today?
        • What are some of the hidden costs associated with BI initiatives?
  • 50. Intelligence Creation and Use and BI Governance
  • 51. Intelligence Creation and Use and BI Governance
    • BI Governance
    • The project prioritization process within organizations
  • 52. Intelligence Creation and Use and BI Governance
    • A typical set of issues for the BI governance team is to address
      • Creating categories of projects (investment, business opportunity, strategic, mandatory, etc.)
      • Defining criteria for project selection
      • Determining and setting a framework for managing project risk
      • Managing and leveraging project interdependencies
      • Continually monitoring and adjusting the composition of the portfolio
  • 53. Intelligence Creation and Use and BI Governance
    • Intelligence Gathering
      • How modern companies ethically and legally organize themselves to glean as much information as they can from their:
        • Customers
        • Business environment
        • Stakeholders
        • Business processes
        • Competitors
        • Other sources of potentially valuable information
  • 54. Intelligence Creation and Use and BI Governance
    • Intelligence Gathering
      • In order to be useful in decision making and improving the bottom line, the data must be:
        • Cataloged
        • Tagged
        • Analyzed
        • Sorted
        • Filtered
  • 55. The Major Theories and Characteristics of Business Intelligence
    • online transaction processing systems (OLTP)
    • Systems that handle a company’s routine ongoing business
    • online analytic processing (OLAP)
    • An information system that enables the user, while at a PC, to query the system, conduct an analysis, and so on. The result is generated in seconds
  • 56. The Major Theories and Characteristics of Business Intelligence
    • Some Theories of BI
      • A factory and warehouse
      • The information factory
      • Data warehousing and business intelligence
      • Teradata advanced analytics methodology
      • Oracle BI system
  • 57. Toward Competitive Intelligence and Advantage
    • The Strategic Imperative of BI
      • Barriers to entry of a new competitor are being significantly diminished
      • Because of the Web revolution and increasing globalization, companies throughout the world are challenging major players in industries
      • The ability to deliver goods worldwide is making it easier for potential competitors to get products and services to more customers almost anywhere
      • Companies are finding better or less expensive suppliers all over the globe
  • 58. Toward Competitive Intelligence and Advantage
    • Competitive Intelligence (CI)
      • CI implies tracking what competitors are doing by gathering material on their recent and in-process activities
      • Competitive strategy in an industry
        • low-cost leader
        • market niche
      • Sustaining competitive advantage through building brand and customer loyalty using BI applications
  • 59. Successful Business Intelligence Implementation
    • The Typical BI User Community
      • IT staff
      • Power users
      • Executives
      • Functional managers
      • Occasional information customers
      • Partners
      • Consumers
  • 60. Successful Business Intelligence Implementation
    • Appropriate Planning and Alignment with the Business Strategy
      • Planning and execution components
        • Business
        • Organization
        • Functionality
        • Infrastructure
    • Establish a BI Competency Center (BICC) within the Company
  • 61. Successful Business Intelligence Implementation
    • Real-time, On-Demand BI Is Attainable
    • Developing or Acquiring BI Systems
    • Justification and Cost/Benefit Analysis
    • Security and Protection of Privacy
    • Integration of Systems and Applications
  • 62. Conclusion: Business Intelligence Today and Tomorrow
    • Today’s organizations are deriving more value from BI by extending actionable information to many types of employees, maximizing the use of existing data assets
    • Visualization tools including dashboards are used by producers, retailers, governments, and special agencies
  • 63. Conclusion: Business Intelligence Today and Tomorrow
    • More and more industry-specific analytical tools will flood the market to perform almost any kind of analysis and to facilitate informed decision making from the top level to the user level
    • A potential trend involving BI is its possible merger with artificial intelligence (AI)
  • 64.
    • THANK YOU