1. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Business Analytics 70-451 Management Information Systems Robert Monroe November 13, 2011

2. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Today’s Quiz

3. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Goals – By The End Of Today's Class You Should: Be able to name some of the major categories of Business Analytics tools and describe at a very basic level what they do, including tools for: –Reporting –Visualization –Data mining –Performance dashboards Understand the role of Key Performance Indicators (KPI’s) in business performance management and the role of BI tools and data warehouse in monitoring and evaluating your organization’s KPI’s

4. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Tools for Business Analytics

5. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Business Intelligence Tools: Reporting Reporting tools present the data contained in a data warehouse, data mart (or even a transactional database) in a human-readable format (possibly with exploration) Reports are primarily used for three purposes: –Making decisions –Tracking status of business processes –Identifying exceptions/problems

6. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Business Intelligence Tools: Visualization Basic idea: use interactive visual representations of large sets of data so that humans can use their innate visual pattern recognition abilities to extract information from the data

7. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Reporting and Visualization Examples GIS mapping of crime statistics in Chicago –http://chicago.everyblock.com/crime/ SmartMoney’s TreeMaps of the NYSE stock market –http://www.smartmoney.com/map-of-the-market/

8. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Business Intelligence Tools: Data Mining Data mining is the art and science of automatically analyzing large data stores to discover meaningful patterns and relationships –Professor Michael Trick, Carnegie Mellon University Example data mining tasks and tools: –Classification –Clustering and affinity discover –Prediction Basic requirements: –Availability of large data sets –A desire to discover patterns and relationships among the data

9. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Business Intelligence Tools: Dashboards Performance dashboards are a category of BI tools that display high-level summarized information on Key Performance Indicators (KPI’s) for a business, or a unit within a business Performance dashboards are part of a broader movement towards data-driven management, supported by tools that can get the right information to the right person, at the right time

10. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Dashboards Typically Support Three Functions Monitoring –Operational metrics, progress towards goals, key indicators Analysis –Portal to reporting and OLAP capabilities Management –Collaboration, e-mail, task assignment, on- and off-line An effective dashboard system transparently integrates the three tasks, with context flowing between them

11. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Dashboard Examples http://www.sap.com:80/solutions/sap-crystal- solutions/dashboards-visualization/demos/software- demos.epx Reporting-focused dashboards –Sales visual model –Standard income statement Operational or Tactical Dashboard-focused –Daily executive report –Sales map

12. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Making Whizzy Dashboards Is The Easy Part… EAI/Data Integration Data Warehouse & Data Marts ETL/Data Cleansing Systems/ Business Analysis Image Source http://www.earthfuture.com Selecting KPIs

13. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Operational, Tactical, and Strategic Dashboards Strategic Tactical Operational

14. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Operational, Tactical, and Strategic Dashboards OperationalTacticalStrategic Purpose Monitor operationsMeasure progressExecute strategy Users Supervisors, Specialists Managers, Analysts Executives, Managers, Staff Scope OperationalDepartmentalEnterprise Information DetailedDetailed and summary Updates Intra-dayDaily or weeklyMonthly or quarterly Emphasis MonitoringAnalysisManagement Source: [Eck06]

15. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Metrics and Key Performance Indicators

16. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Selecting Key Performance Indicators (KPI’s) Choosing what to measure is arguably the most important step in dashboard design and deployment –Business truism: “What gets measured gets done” –Monroe’s corollary: so choose what you measure carefully… Doing so is at least as much art as science Beware unintended consequences –Malicious/self-interested gaming of the system –Mixed signals –Too many metrics cause loss of focus

17. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Characteristics of Effective KPI’s Aligned Owned Predictive Actionable Few in number Easy to understand Balanced and linked Accurate Standardized Presented in context Reinforced w/incentives Relevant Source: [Eck06] “We never create a report that won’t change behavior” -- Wise policy of an anonymous CIO

18. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Leading vs. Lagging Performance Indicators For BPM, dashboards should focus on leading rather than lagging indicators –Change what is coming up, not what has already happened –Doing so may require a bit of a shift in mindset How might you convert the following lagging indicators into leading indicators? Are any of them leading indicators for other metrics? –Sales revenue –Market share for product x –New customers acquired per quarter –% of Salespeople meeting quota –Employee satisfaction –Customer satisfaction –Returns due to defects Source: [Eck06]

19. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Developing KPI’s Requires effective business and systems analysis work Can be done top-down and/or bottom-up Standardize, standardize, standardize! Basic elements of a KPI specification –Identify what is being measured and how it is calculated –Identify where the data for the KPI will come from –Identify units, thresholds, and targets (configurably) Less is more

20. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems In-Class Exercise: Key Performance Indicators Form groups of 2-4 people Work in groups on exercise handed out Discuss results and findings

21. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems Wrap-up

22. Carnegie Mellon University ©2006 - 2011 Robert T. Monroe 70-451 Management Information Systems References [HPM05] Jeffrey Hoffer, Mary Prescott, Fred McFadden, Modern Database Management, 7 th Ed., Pearson - Prentice Hall, 2009, ISBN: 0-13-600391-5. [Eck06] Eckerson, Wayne, Performance Dashboards, Wiley, 2006, ISBN: 0-471-72417-3