Business Intelligence - A Management Perspective

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A presentation on Business Intelligence by Dr. Lakshmi Mohan

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  • Hello My Beloved One .



    I greet you with the name of our Lord Jesus Christ, It is true that this letter may come to you as a surprise. Nevertheless, I humbly ask you to give me your attention and hear me well.

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    beneficiary of this money. I also want you to always put me in prayer.
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Business Intelligence - A Management Perspective

  1. 1. <ul><li>1. Why is BI an Imperative Today? </li></ul><ul><li>2. BI: A Key Component of Enterprise Systems </li></ul><ul><li>3. Evolution of BI Systems </li></ul><ul><li>4. Hard Data vs Soft Data </li></ul><ul><li>5. The “Satisficing Concept” </li></ul><ul><li>What Is Actionable Information? </li></ul><ul><li>Efficiency vs. Effectiveness </li></ul>Business Intelligence : A Management Perspective
  2. 2. The Consultant’s Café - “Today’s Special” Has Changed Over the Years <ul><li>Executive Information Systems (EIS) </li></ul><ul><li>Total Quality Management (TQM) </li></ul><ul><li>Business Process Reengineering (BPR) </li></ul><ul><li>Enterprise Resource Planning Systems (ERP) </li></ul><ul><li>Supply Chain Management (SCM) </li></ul><ul><li>Customer Relationship Management (CRM) </li></ul><ul><li>Human Capital Management (HCM) </li></ul><ul><li>BUSINESS INTELLIGENCE (BI) </li></ul>
  3. 3. One Idea, So Many Names! <ul><li>“ Business Intelligence” Term Coined by Gartner in 1989 – Simply defined as using information effectively to make better decisions </li></ul><ul><li>Gartner’s Emphasis Today: Corporate Performance Management – CPM means getting a better finger on the pulse of an organization to make a better, more accurate, and more timely assessment of how an organization is doing. Enterprises need to move away from asking, “ How did we do last month or last quarter” to “How are we doing right now” as well as “ How will we do next week ” </li></ul><ul><li>Meta Group: Business Performance Management - Companies realize they have six different tools, but they do not have a consistent approach to results reporting, management reporting, planning and budgeting, etc. </li></ul>
  4. 4. The Computer Made It to the Executive Suite In Late 80s! <ul><li>The computer has little to offer executives since their work is unstructured &quot;Fortune&quot;, Nov. 1983. </li></ul><ul><li>Executives are finally getting fast, clear information about what's happening in the bowels of their business. The new systems can change the way top managers work </li></ul><ul><li> &quot;Fortune&quot;, Mar. 1989. </li></ul>
  5. 5. But Not Quite ! <ul><li>&quot;Every business manager I know shares </li></ul><ul><li>one frustration: </li></ul><ul><li>the difficulty of obtaining fast, accurate </li></ul><ul><li>and comprehensive market information.&quot; </li></ul><ul><li>President, Frito-Lay </li></ul><ul><li>Wall St. Journal, June 11, 1990 </li></ul>
  6. 6. What Happened in the Mid-1980s? <ul><li>1. INCREASING GLOBAL COMPETITION </li></ul><ul><li>&quot;In today's environment, a businessman without access to good information is playing with one hand behind his back&quot; </li></ul><ul><li>2. TIMELY &quot; INFORMATION &quot; BECAME CRITICAL </li></ul><ul><li>&quot;We need enough advance warning to steer around the iceberg. What we have had so far is the world's best damage report&quot; </li></ul><ul><li>3. CORPORATE DOWNSIZING </li></ul><ul><li>&quot;Fewer staff analysts available to sift through the mountain of ‘ data’ and cull out relevant ‘ information ’ ” </li></ul><ul><li>4. TECHNOLOGICAL ADVANCES </li></ul><ul><li>Made Executive Information Systems systems a reality </li></ul>
  7. 7. Major Growth Drivers for BI in 2005 <ul><li>Need for organizations to make a sense of the “data tsunami” that is hitting them from their enterprise applications </li></ul><ul><li>Focus on performance management and the need to develop and measure the associated key performance indicators </li></ul><ul><li>Ensuring accuracy, timeliness and consistency of data for regulatory reporting </li></ul><ul><li>Source: Gartner Management Update, Nov. 2004 </li></ul>Market for BI tools is estimated to grow from $ 3.7B in 2002 to $4.5B in 2007, according to industry analyst, IDC. Source: DM Review , April 2003
  8. 8. Case Example: 7-Eleven Japan - BI for Implementing a Customer-Centric Strategy <ul><li>1974: Ito-Yokado acquired franchise rights to 7-Eleven in Japan </li></ul><ul><ul><li>By 1998, expanded to over 5,000 stores </li></ul></ul><ul><ul><li>Company’s profitability reached 40% of sales </li></ul></ul><ul><ul><li>In contrast, 7-Eleven USA filed for bankruptcy </li></ul></ul><ul><ul><li>Sold 70% of its stores to Ito-Yokado </li></ul></ul><ul><li>IT systems captured information about customers and their needs </li></ul><ul><ul><li>Every clerk recorded customer features (gender, approx age, etc) at the time of purchase </li></ul></ul><ul><ul><li>Also, products requested that were not available in the store’s inventory </li></ul></ul><ul><li>Inventory management systems based on customer information </li></ul><ul><ul><li>Which products to stock in each store? </li></ul></ul><ul><ul><li>How much shelf space for each product? </li></ul></ul><ul><ul><li>Which are the most sellable items at different hours of the day and hence should be displayed? </li></ul></ul>
  9. 9. HSBC’s Foray into Consumer Finance - Differentiated Customer Strategy Requires BI <ul><li>Acquired Household International in the US </li></ul><ul><ul><li>53M customers </li></ul></ul><ul><ul><li>33% are categorized as “sub prime” … those at the lower end of the market </li></ul></ul><ul><li>Sub-prime Market is Lucrative </li></ul><ul><ul><li>Can charge higher interest rates </li></ul></ul><ul><ul><li>But, higher risk of default </li></ul></ul><ul><li>BI for Managing Credit Risk </li></ul><ul><ul><li>A state-of-the-art consumer analytics system </li></ul></ul><ul><ul><li>Each customer is analyzed down to the last detail, including his choice of colours … a man buying a red car is assumed to be flashy and more daring! </li></ul></ul>
  10. 10. The Urgency for BI <ul><li>Gartner’s March 2005 BI Summit in Chicago and London drew over 750 attendees at each event! </li></ul><ul><li>Mountains of data; growing at 30% to 50% a year </li></ul><ul><li>Pressure of regulations such as the US Sarbanes-Oxley Act and in financial services, the Basel II capital adequacy rules forcing companies to “fix-up” their practices </li></ul><ul><li>Competition and customer demands requiring timely – and often real-time – information, and in plenty of detail - to “drill down” from high-level summarized reports, with the intervals between updates coming down, especially in financial services (“from 4 hours to 15-25 minutes”) </li></ul>
  11. 11. One Version of the Truth? <ul><li>Data resides in disparate systems cobbled together over the years </li></ul><ul><li>Duplication of data in different systems, frequently conflicting – Which data is accurate? MIS reports causing confusion – Which report has the correct data? </li></ul><ul><li>Spreadsheet Hell! - Multiple spreadsheet databases created by users - Slow process; Prone to Error - Multiple Versions of the Truth </li></ul>The goal of BI systems is to pull data from all internal systems AND external sources to present a SINGLE version of the Truth.
  12. 12. BI for the Masses - Not just for Statisticians and Corporate Analysts <ul><li>Instead of a small number of analysts spending 100% of their time analyzing data, all managers and professionals should spend 10% of their time using BI software </li></ul><ul><li>Smart companies are democratizing data access with dashboards and other BI tools to empower everyone in the organization, at all levels , with analytics, alerts and feedback mechanisms - Transforms every employee into an “organization of one” who can make the right decisions at the right time in step with company objectives. - Everyone can work smarter! </li></ul><ul><li>Smarter Companies will ensure the payoff of investments in BI systems by making the masses accountable for data-driven action and results . - Accountability could be in the form of rewards, penalties Or simply, a mandated workflow </li></ul>
  13. 13. GE’s Concept of “Span” - Measures the operational reliability for meeting a customer request … the time window around the Customer Requested Delivery Date in which the delivery will happen - High Span  Poor capability to meet customer need Objective  Zero span - Squeeze the two sides of the delivery span - days early and days late - ever closer to the center - the exact day the customer desired RESULTS : Plastics : 50 days span to 5 Aircraft Engines : 80 days span to 5 Mortgage Insurance : 54 days span to 1
  14. 14. The GE Process - In the CEO’s Annual Letter (Feb 2001) When the order is taken, that date becomes known to everyone, from the first person in the process receiving the castings, circuit boards or any other components from the supplier, all the way through to the service reps who stand next to the customer as the process is started up for the first time. Every single delivery to every single customer is measured and in the line of sight of everyone ; and, everyone in the process knows he or she is affecting the business-wide measurement of span with every action taken. WHAT GETS MEASURED AND REWARDED GETS DONE !
  15. 15. Two Perspectives for BI Systems <ul><li>Technical Perspective – Preferred by Vendors - Business Objects, SAS, Cognos, Brio, SAP, … - “Technology enables organizations to transform data stored in core business systems into useful information.” </li></ul><ul><li>Business Perspective – Preferred by Managers - “Focus on getting the RIGHT information to the RIGHT people at the RIGHT time to make MORE EFFECTIVE decisions” - THE PERSPECTIVE OF THIS COURSE. </li></ul>
  16. 16. What are Enterprise Systems? An integrated suite of information systems that form the backbone of the enterprise for running and managing its operations
  17. 17. Back To Back: Enterprise Systems Encompass <ul><li>Front-end systems like Customer Relationship Management </li></ul><ul><li>AND </li></ul><ul><li>- Back-end systems like Enterprise Resource Planning and Supply Chain Management </li></ul>Objective: Seamless and Transparent Flow of Data Across the Entire Value Chain
  18. 18. The Big Problem with Information Systems Today… <ul><li>…“ Islands of Automation ” </li></ul><ul><li>Stand-alone systems designed for specific processes </li></ul><ul><li>Cannot “talk” to each other within the organization </li></ul><ul><li>Much less, externally with the systems of customers or suppliers </li></ul>
  19. 19. Drivers of Enterprise Systems <ul><li>Inefficient operations </li></ul><ul><li>Higher internal costs </li></ul><ul><li>Lack of coordination with suppliers </li></ul><ul><li>Poor customer service </li></ul><ul><li>Missed opportunities for revenue </li></ul><ul><li>Most Important: Emergence of the Internet </li></ul><ul><li>A cost-effective means to connect </li></ul><ul><li>the back-office and front-end systems </li></ul>
  20. 20. IT Architecture Should Integrate Information, Processes and Functions Traditional View Enterprise View
  21. 21. Four Major Components of Enterprise Systems <ul><li>ERP </li></ul><ul><ul><li>Enterprise Resource Planning systems evolved from Manufacturing Resource Planning (MRP) systems </li></ul></ul><ul><ul><li>Integrate all the internal processes and data flowing through the organization: the “back-end” systems </li></ul></ul><ul><li>CRM </li></ul><ul><ul><li>Customer Relationship Management systems evolved from Sales Force Automation (SFA) for contact and lead management </li></ul></ul><ul><ul><li>A full suite of applications for telemarketing, call center (today, contact center), … for supporting marketing, sales and services: the “front-end” systems dealing with the customer </li></ul></ul>
  22. 22. Four Major Components of Enterprise Systems (…contd) <ul><li>SCM </li></ul><ul><ul><li>Supply Chain Management systems address the problem of fulfilling, and responding to changes in, demand at a minimum cost. </li></ul></ul><ul><ul><li>Advanced planning applications that take into account demand forecasts, production constraints, …. front-end systems connecting to suppliers, logistics providers, …to get the right product to the right place at the right time at the right cost . </li></ul></ul><ul><li>BI </li></ul><ul><ul><li>Business Intelligence systems, the new label for Decision Support Systems (DSS) and Executive Information Systems (EIS), including Data Warehousing and Data Mining </li></ul></ul><ul><ul><li>Systems for analyzing the vast amount of internal transaction data and external data about customers and competitors to track performance and manage the business more effectively </li></ul></ul>
  23. 23. New Applications targeted by ERP vendors
  24. 24. The Time Value of Information - Key Benefit of Enterprise Systems Frito-Lay System: Sales data from the hand-held computers of salespeople provided the foundation for “time synchronizing” the entire business process: Purchasing Manufacturing Logistics Sales P&G’s Continuous Product Replenishment System: An inter-organizational system using EDI to transfer the scanner data from retailers to P&G’s computers, which figures out when and where to replenish the product -- minimizes mistakes and bill-backs, lowers inventory and improves cash-flow for both P&G and retailers Enterprise Systems compress the time taken for information flows.
  25. 25. An Opportunity To Be Seized . . . . - Computers used in Business for Nearly 50 Years - Dazzling Progress in Technology - Significant Investments in IT Infrastructure Hardware, Software and Peopleware Focus on OPERATIONAL SYSTEMS has blurred the potential of using IT for MANAGING the Business YET . .
  26. 26. The Information Age Paradox Lots of DATA . . . but no INFORMATION to manage the business The 1980s launched the Information Age. Still, most managers are less than satisfied with their information systems.
  27. 27. Computer Usage Evolution <ul><li>ERA I: Accounting (1950s to early 1960s) </li></ul><ul><li>e.g. Payroll, Invoicing </li></ul><ul><li>Benefit: “Manumation” </li></ul><ul><li>ERA II: Operations (mid 1960s to early 1970s) </li></ul><ul><li>e.g. Airline Reservations, Inventory Control </li></ul><ul><li>Benefit: Improved Customer Service </li></ul><ul><li>Better Utilization of Capital </li></ul><ul><li>ERA III: Information Support (early 1970s - ) </li></ul><ul><li>e.g. Market Analysis, Succession Planning </li></ul><ul><li>Benefit: Better Decisions </li></ul><ul><li>Increased “People Productivity” </li></ul>
  28. 28. Evolution of BI Systems <ul><li>Expert Systems </li></ul><ul><li>To Manage by Wire </li></ul><ul><li>To extract news from the data </li></ul>Decision Support Systems (DSS) Support , not replace, mangers in making decisions Executive Information Systems (EIS) Support top management Group Decision Support systems (GDSS) Support a group of managers
  29. 29. Managerial Data Encompasses Hard and Soft Data <ul><li>Subjective judgments are an important source for quantities that are difficult to measure, or which cannot be measured in the time available before a deicsion is made </li></ul><ul><li>Soft data is more essential for certain functions... ... Marketing: Competitive Intelligence ... Human Resources: Succession Planning ... Corporate Planning: Forecasts And, for upper levels of management ... External data about the environment </li></ul>The greatest challenge of the computer industry is to learn how to build information bases, not databases. The really important information cannot be easily quantified and exists outside the organization. - Peter Drucker
  30. 30. HARD vs. SOFT DATA <ul><li>HARD DATA ... Fairly Accurate, Easy To Get </li></ul><ul><ul><li>Historical Data </li></ul></ul><ul><ul><li>e.g., Revenue, Direct Costs </li></ul></ul><ul><ul><li>Measured Data </li></ul></ul><ul><ul><li>e.g., Bill of Materials for a Product </li></ul></ul><ul><li>SOFT DATA ... Fairly Inaccurate, Difficult to Get </li></ul><ul><ul><li>Future Data </li></ul></ul><ul><ul><li>e.g., Sales Forecasts </li></ul></ul><ul><ul><li>Judgemental Data </li></ul></ul><ul><ul><li>e.g., Allocation of Overhead Costs </li></ul></ul><ul><ul><li>Qualitative Data </li></ul></ul><ul><ul><li>e.g., High Potential of an Employee </li></ul></ul>
  31. 31. Information Must be Tailored to Management Level Management Level Lower Middle Top Operational Control Narrow Narrow Internal Historical Micro Management Control Strategic Planning Wide Wide External Future Macro ? 1. Function 3. Scope of Information 2. Scope of Responsibility 4. Sources of Data 5. Time Horizon 6. Level of Detail
  32. 32. The Data Isn’t Where We Need It! Senior Managers -Strategic Planning Middle Managers - Management Control Front-Lines - Operational Control External, Soft Data Internal, Hard Data Corporate Data Warehouse The greatest challenge of the computer industry is to learn how to build information bases, not databases. The really important information cannot be easily quantified and exists outside the organization. - Peter Drucker (1993)
  33. 33. Type of Data in the BI System <ul><li>Not just Hard, Internal Data </li></ul><ul><li>Not limited to Financial Data </li></ul><ul><li>Must include Soft, External Data </li></ul><ul><li>Key Areas to be Considered: </li></ul><ul><ul><li>Measurement of Customer Service </li></ul></ul><ul><ul><li>Market Information on Customers & Competition </li></ul></ul><ul><ul><li>High-Potential Evaluation, Succession Planning & Career Development of Employees </li></ul></ul>
  34. 34. Two Distinct Types of Systems <ul><li>Operational Systems will be used because they run the “bread-and-butter” business processes of the organization - they are mission-critical </li></ul><ul><li>Information Support Systems depend on managers’ desire and ability to use them in their decision-making processes to manage the business </li></ul><ul><li>Prerequisite: </li></ul><ul><li>The management process must be driven by the information provided by the system. Only then will the system be used. </li></ul>
  35. 35. A Different Perspective on Data Quality ... Depending on Use <ul><li>Emphasis on getting complete, accurate and timely data </li></ul><ul><li>But limited to internal, hard data </li></ul><ul><li>Cost of data quality justifiable because systems will be used </li></ul>Operational Systems (e.g., Invoicing, Airline Reservations, Electronic Commerce, etc.) <ul><li>Information Support Systems </li></ul><ul><li>(e.g., Performance Evaluation, Market Analysis, etc.) </li></ul><ul><li>Scope of Data is Wider - External and Soft data </li></ul><ul><li>But ... Is “Better” Data Worthwhile? </li></ul><ul><li>Value is zero if system is not used </li></ul>
  36. 36. Payoff from Data Warehouses Depends on the Management Process <ul><li>Easier to upgrade quality of the data than the management process for utilizing the high quality data </li></ul><ul><li>Improving the quality of data will be all costs and no benefits if the data is not used. </li></ul><ul><li>Need to upgrade the management process to effectively use better quality data. </li></ul>If a magic fairy instantly gave you all the information...the company would ever need, do you think people would instantly know what to do with it and use it well. Peter Keen (1998)
  37. 37. Mere Access to Quality Data . . . Will create a data overload that can affect managerial productivity. Investments on market research, telecommunications, etc. to deliver better quality data should be complemented by investments in systems to convert the data into useful information. Quality of the data conversion process is equally important.
  38. 38. A Data Warehouse is Not Enough Because... <ul><li>... Managers Ask for Analysis, NOT just Retrieval of Data </li></ul>Sometimes retrieval questions come up of course, but most often the answers to important questions require non-trivial manipulation of stored data. Knowing this tells us much about the kind of software required. For example, a database management system is not enough. - John Little (1979) <ul><li>“ Data” has to be converted into “Information” that triggers managerial action. </li></ul><ul><li>The conversion process is critical to get value from the data warehouse. </li></ul>
  39. 39. A Manufacturing Analogy Raw Data = Raw Material <ul><li>Conversion Process </li></ul><ul><ul><li>DSS/EIS/BI Systems </li></ul></ul><ul><ul><li>Expert Systems </li></ul></ul><ul><ul><li>Data Mining, etc. </li></ul></ul>Actionable Information = Finished Product <ul><li>Quality of the Conversion Process </li></ul><ul><ul><li>As Important as the Quality of the Data </li></ul></ul>
  40. 40. COST versus VALUE OF DATA - “Satisficing” Concept <ul><li>Better data Higher cost Value Impact on the decision </li></ul>&quot;We are subjecting every activity, every function to the most rigorous review, distinguishing between those things which we absolutely need to do and know versus those which would be merely nice to do and know.&quot; General Electric CEO Aim: Get a Satisficing Solution for Decision-Making - Select a satisfactory decision with limited information in a limited time instead of searching for the best solution entailing more time and information
  41. 41. Actionable Information <ul><li>… Information that becomes the basis for action </li></ul><ul><li>Must be Timely </li></ul><ul><li>“ Satisficing ” Accuracy is Enough </li></ul><ul><li>Must Help in ... </li></ul><ul><li>Problem-Finding and Problem-Solving </li></ul>
  42. 42. Attributes of “ Actionable ” Information <ul><li>Timeliness </li></ul><ul><ul><li>If it is late, managers will make decisions without it </li></ul></ul><ul><li>Complete and Accurate? How much? </li></ul><ul><ul><li>– Just good enough for decision-making </li></ul></ul><ul><ul><li>What is absolutely needed in relation to What is at stake </li></ul></ul><ul><ul><li>Reason: $$$$$$ 100% Complete and Accurate takes time and is expensive </li></ul></ul><ul><ul><li>The key concept in information accuracy and completeness is “Satisficing.” </li></ul></ul>
  43. 43. Timeliness vs. Accuracy Problem <ul><li>Precise Financial Data Has a Price: Time </li></ul><ul><ul><li>Accruals, adjustment entries and allocations lengthen Monthly Closing Cycles </li></ul></ul><ul><ul><li>Is the Precision worth the Time Lag in the Data? </li></ul></ul><ul><li>“ Just-In-Time” Monthly Closing </li></ul><ul><ul><li>Timely Data with Satisficing Accuracy </li></ul></ul><ul><ul><li>Frees up time of financial staff for value-added analysis </li></ul></ul>
  44. 44. The DURACELL EIS: How It Provides “Information ”  The CEO, Robert Kidder, manipulated a mouse attached to his workstation.  To compare the performance of work forces in the U.S. and overseas.  Computer displayed a crisp table in colors showing higher sales per employee in the U.S.  He asked the computer to drill down for more data to explain the difference.  At the end of the data-browsing session, the real problem was found: .... TOO MANY SALESPEOPLE IN GERMANY WERE WASTING TIME CALLING ON SMALL CUSTOMERS.
  45. 45. Efficiency vs Effectiveness <ul><li>There’s nothing so useless as doing efficiently that which should not be done at all Companies wrench their guts to downsize a business they shouldn’t be in at all </li></ul><ul><li>…… Peter Drucker says it well </li></ul><ul><li>Effectiveness: Doing the Right Thing </li></ul><ul><li>Efficiency: Doing IT Right </li></ul>Which is more important in a BI system?
  46. 46. A Home Truth: A System That Is Not Used Is a Waste <ul><li>Operational Systems Will be Used </li></ul><ul><li>Because they are mission-critical for running </li></ul><ul><li>the organization </li></ul><ul><li>DSS / EIS / BI Systems ??? </li></ul><ul><li>Will not be used unless the management process is driven by these systems </li></ul>
  47. 47. Two “Big” Factors Affect Use of BI System <ul><li>1. Organization Culture </li></ul><ul><li> “ Business as Usual ” - Complacent Culture </li></ul><ul><li>versus </li></ul><ul><li> “ How Can We Improve ” </li></ul><ul><li>2. Management Style </li></ul><ul><li> “ Left Brain ” - Analytical </li></ul><ul><li>versus </li></ul><ul><li> “ Right Brain ” - Intuitive </li></ul>

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