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Section 6-1 IS with STRATEGIC DECISION SUPPORTING SYSTEM & BUSINESS INTELLIGENCE SYSTEM DECISION SUPPORTING SYSTEM (DSS) LEARNING OUTCOMES 1. Explain the difference between transactional information and analytical information. 2. Define TPS, DSS, and EIS and explain how an organization can use these systems to make decisions and gain competitive advantages 3. Describe the three quantitative models typically used by decision support systems 4. Explain trend and technology of Business Intelligence System 5. Describe the relationship between visualization and Business Intelligence systems DECISION MAKING • Reasons for the growth of decision-making information systems – People need to analyze large amounts of information – People must make decisions quickly – People must apply sophisticated analysis techniques, such as modeling and forecasting, to make good decisions – People must protect the corporate asset of organizational information DECISION MAKING • Model – a simplified representation or abstraction of reality • IT systems in an enterprise TRANSACTION PROCESSING SYSTEMS • Moving up through the organizational pyramid users move from requiring transactional information to analytical information Fine Coarse TRANSACTION PROCESSING SYSTEMS • Transaction processing system (TPS) - the basic business system that serves the operational level (analysts) in an organization • Online transaction processing (OLTP) – the capturing of transaction and event information using technology to (1) process the information according to defined business rules, (2) store the information, (3) update existing information to reflect the new information • Online analytical processing (OLAP) – the manipulation of information to create business intelligence in support of strategic decision making • Cf. Online analytical mining (OLAM) DECISION SUPPORT SYSTEMS • Decision support system (DSS) – models information to support managers and business professionals during the decision-making process • Three quantitative models used by DSSs include: 1. Sensitivity analysis – the study of the impact that changes in one (or more) parts of the model have on other parts of the model 2. What-if analysis – checks the impact of a change in an assumption on the proposed solution 3. Goal-seeking analysis – finds the inputs necessary to achieve a goal such as a desired level of output DECISION SUPPORT SYSTEMS • What-if analysis DECISION SUPPORT SYSTEMS • Goal-seeking analysis DECISION SUPPORT SYSTEMS • Interaction between a TPS and a DSS EXECUTIVE INFORMATION SYSTEMS • Executive information system (EIS) – a specialized DSS that supports senior level executives within the organization • Most EISs offering the following capabilities: – Consolidation – involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information – Drill-down – enables users to get details, and details of details, of information – Slice-and-dice – looks at information from different perspectives EXECUTIVE INFORMATION SYSTEMS • Interaction between a TPS and an EIS Digital Dashboards • Digital dashboard – integrates information from multiple components and presents it in a unified display BUSINESS INTELLIGENCE SYSTEM (BI) Special Thanks to Matt Schwartz Chapter Overview • Decision-enabling, problem-solving, and opportunity-seizing systems What is Business Intelligence? Business Intelligence enables the business to make even more intelligent, faster decision based on DSS. Aggregate Data Database, Data Mart, Data Warehouse, ETL Tools, Integration Tools Present Data Reporting Tools, Dashboards, Static Reports, Mobile Reporting, OLAP Cubes Enrich Data Add Context to Create Information, Descriptive Statistics, Benchmarks, Variance to Plan or LY Inform a Decision Decisions are Fact-based and Data-driven Artificial Intelligence (AI) • Intelligent system – various commercial applications of artificial intelligence • Artificial intelligence (AI) – simulates human intelligence such as the ability to reason and learn Artificial Intelligence (AI) • The ultimate goal of AI is the ability to build a system that can mimic human intelligence Artificial Intelligence (AI) • Four most common categories of AI include: 1. Expert system – computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems 2. Neural Network – attempts to emulate the way the human brain works – Fuzzy logic – a mathematical method of handling imprecise or subjective information Artificial Intelligence (AI) • Four most common categories of AI include: 3. Genetic algorithm – an artificial intelligent system that mimics the evolutionary, survival-ofthe-fittest process to generate increasingly better solutions to a problem 4. Intelligent agent – special-purposed knowledge-based information system that accomplishes specific tasks on behalf of its users CPU – Content, Performance, Usability • Content – The business determines the “what”, BI enables the “how” • Performance – Minimize report creation and collection times (near zero) • Usability – Delivery Method Push vs Pull – Medium Excel, PDF, Dashboard, Cube, Mobile Device – Enhance Digestion “A-ha” is readily apparent, fewer clicks – Tell a Story Trend, Context, Related Metrics, Multiple Views How Important is BI? Top 10 Business and Technology Priorities for 2011: 1. Cloud computing 2. Virtualization 3. Mobile technologies 4. IT Management 5. Business Intelligence 6. Networking, voice and data communications 7. Enterprise applications 8. Collaboration technologies 9. Infrastructure 10. Web 2.0 Source: Gartner’s 2011 CIO Agenda (aka “Reimagining IT: The 2011 CIO Agenda”). Why is Business Intelligence So Important? Time Data Opinion (Professional Judgment) Making Business Decisions is a Balance In the absence of data, business decisions are often made by the HiPPO. With Business Intelligence, we can get data to you in a timely manner. The July 2010 Forrester report “Technology Trends That Retail CIOs Must Tap to Drive Growth” identified the following technologies that retail CIOs should be considering as part of an overall architecture strategy: Mobile Social Computing Cloud Supply Chain Micropayments Business Intelligence/Analytics Major BI Trends • Mobile • Cloud • Social Media • Advanced Analytics Most Important BI technologies What BI technologies will be the most important to your organization in the next 3 years? 1. Predictive Analytics 2. Visualization/Dashboards 3. Master Data Management 4. The Cloud 5. Analytic Databases 6. Mobile BI 7. Open Source 8. Text Analytics BI Today vs Tomorrow • “BI today is like reading the newspaper” – BI reporting tool on top of a data warehouse that loads nightly and produces historical reporting • BI tomorrow will focus more on real-time events and predicting tomorrow’s headlines Who does use BI? only Business firm? • Essential to the success of companies in a wide range of industries, and more famously essential to the success of professional sports teams such as the Boston Red Sox, Oakland A’s and New England Patriots. • With an analytical approach, the Patriots managed to win the Super Bowl three times in four years. The team uses data and analytical models extensively, both on and off the field. In-depth analytics help the team select players and stay below the NFL salary cap. Patriots coaches and players are renowned for their extensive study of game film and statistics. • Off the field, the team uses detailed analytics to assess and improve the "total fan experience." At every home game, for example, 20 to 25 people have specific assignments to make quantitative measurements of the stadium food, parking, personnel, bathroom cleanliness and other factors. www.cio.com A Framework for Computerized Decision Analysis Problem Structure The first dimension deals with the problem structure, where the decision making processes fall along the continuum ranging from highly structured to highly unstructured decisions. Highly structured Order entry Semistructured Loan approval Higly unstructured Building new plant Unstructured Text Processing Facebook Page Twitter Page Customer Sat Survey Comments Call Center Notes, Voice Services Quality Competitors’ Facebook Pages Email Blogs 32 Cost Friendliness Public Web Sites, Discussion Boards, Product Reviews Adhoc Feedback Alerts, Real-time Action The Scope of Business Intelligence Smaller organizations: Excel spreadsheets Larger organizations: Data mining, predictive analytics, dashboards Source: Dundas Software, www.dundas.com/ dashboard/online-examples/ screenshots/Marketing-Dashboard.aspx BI Technologies •Analytic Databases DB2 Oracle SQL Server Teradata Netezza Vertica Aster Data Par Accel Greenplum Semantic Databases •BI is a consolidating industry – – – – – – Oracle: Siebel, Hyperion, Brio, Sun SAP: Business Objects, Sybase IBM: Cognos, SPSS, Coremetrics, Unica, Netezza EMC: Greenplum HP: Vertica Teradata: Aster Data •Independent vendors: MicroStrategy, Informatica, SAS •Reporting standards determined mainly by Microsoft, Apple and Adobe CLOSING QUESTIONS Revving Up Sales at Harley-Davidson 1. How does Talon help Harley-Davidson employees improve their decision-making capabilities? 2. Identify a few key metrics a Harley-Davidson marketing executive might want to monitor on a digital dashboard 3. How can Harley-Davidson benefit from using decision support systems in its business Appendix – Dash board Digital Dashboard (example) Source: MicroStrategy Digital Dashboard (example) Source: Dundas Software, www.dundas.com/ dashboard/online-examples/ screenshots/Marketing-Dashboard.aspx Digital Dashboard Demo • Informationbuilders http://www.informationbuilders.com/rfr/qtde mo/AdvVis_ExecDash/AdvVis_ExecDash. html • Open source : Dojo http://dojotoolkit.org/features/graphics-andcharting A Bloomberg Terminal Source: Carlos Osario/Zuma Press Management Cockpit Source: The Management Cockpit is a registered trademark of SAP,created by Professor M.Georges . Data Visualization Systems The Power of Visualization Even though a picture is “worth a thousand words,” we have to be very careful about just what we are seeing.