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Mobilizing Transparency

Mobilizing Transparency. September 10, 2008. Gregg Le Blanc Chief Michael Doppelganger Transpara Corporation. Agenda. Using KPI’s effectively About Transpara & Visual KPI How Visual KPI is used Demo / Screens Visual KPI 4.0 and beyond. The downside of data wealth. Information poverty

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Mobilizing Transparency

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  1. Mobilizing Transparency September 10, 2008 Gregg Le Blanc Chief Michael Doppelganger Transpara Corporation

  2. Agenda • Using KPI’s effectively • About Transpara & Visual KPI • How Visual KPI is used • Demo / Screens • Visual KPI 4.0 and beyond

  3. The downside of data wealth Information poverty • What does the data mean? • Is the data the same? • Does more data help? Conflicting actions • Does it mean the same thing to everyone? • Which system or person is right?

  4. About Transpara & Visual KPI Transpara • Founded 2005 • 100+ installed systems Visual KPI • Visualization for Business Intelligence and Mfg Intelligence • Thin layer used to “Composite” together data from many systems • Can roll out complete new site in a single afternoon • KPIs, Scorecards, Dashboards are quickly assembled using Excel • Distribution to any browser, including WM 5/6, iPhone, Blackberry

  5. Simply having KPI’s is not enough • Studies have shown KPI’s that are well integrated into your business are a tool for change. • However, sometimes KPI’s: • Increase stress on employees • Create unintentional parallel workflows • Can dissolve collaboration between groups Need to create a ecosystem where culture, information, and action combine!

  6. KPI’s aren’t just for executives anymore • Mechanic • I&C Technician • Control Room Operator • Performance Engineer • Regulatory Manager • Test Engineer • PPO Engineer • Quality Assurance • Mfg Sciences Engineer • Executive • Field Supervisor • Plant Engineer • Operation Manager • Control Manager • Maintenance Manager • Watch Supervisor • Process Engineering • Process Development Executive

  7. Characteristics of good KPI’s • MESA Metrics that Matter study • Companies that found: • A 10% improvement in a single key area • A 1% improvement across at least 6 out of 11 areas • They have this in common: • Metrics linked to operations • Fully automated data collection • Rapid recalculation • Timely action taken based on metrics

  8. The process of KPI creation* Someone tells thecompany how important these KPI’s are Someone wrangles data together Someone creates visualizations People sit in a room and decide what’s important * Not to scale

  9. Assumptions about KPI’s • You have all the information you need • Systems talk to each other • The important metrics you derive can be answered • You have a culture ready to accept KPI’s • “Is ‘Management’ spying on me?” • “I don’t know how that KPI was made.” • KPI’s lead to (unique) action • When my favorite KPI dips below the low limit I… • When someone takes action, there is no duplication

  10. KPI evolution from Central to Local Centralized Intelligence Localized Intelligence Actionable Decisions • Sources: • SAP PM • SAP BW • OSIsoft PI • MS SQL • Oracle Mobile Consumer Visual KPI Someone wrangles data together Desktop and Mobile User Someone creates visualizations People sit in a room and decide what’s important User and KPI Creator • Local Sources: • Site Web services • Site databases

  11. KPI’s at real customers • Large installation • Using around 125,000 KPI’s to track a site • Currently deployed in 3 sites, expanding further • At least 5 different user roles use Visual KPI daily • Targeted installation • Research In Motion (RIM) • Tracks their Blackberry production rate on their Blackberrys (Blackberries?)

  12. Now KPI’s can come from everywhere

  13. Solving the transparency problem • Make use of what you have • Leverage existing technology investments • Leverage mobile technology already in the hands of employees • Align strategies • Map corporate strategy (will of the few) to collective strategy (will of the masses) • Link strategy to execution

  14. Leverage existing data sources • Re-purpose existing data • Assembled, not programmed • Extend value of data already created • Example: MW Delivered to Customer X • Target value from EMS / DMS • Actual real-time data from PI • High and Low quality limits from SQL Server • Max and Min of line capability from MRO

  15. Visual KPI 3.x architecture Data Sources Any Mobile or Desktop Client Visual KPI Excel Editor • Excel 2003 or Excel 2007with VSTO • Configuration only, no run-time association or storage • PI System • Real-time Data • Meta Data • Equations • Any RDB • Existing Data • External KPIs • LOB App • Link to financials • Planned values • SAP, MRO, etc. Publish Scorecards via Web Services Web Services Web Services XML over HTTP Visual KPI Server • Composite KPI Engine • All meta data in SQL 2005 or 2008 • Windows Server 2003 or 2008 • XML and Web Services-based • Extensible, Programmable

  16. Visualizing KPI’s

  17. Anatomy of a KPI Status = GOOD Actual Min Target Max Low Low High High Low High

  18. Anatomy of a KPI Status = HIGH Actual Min Target Max Low Low High High Low High

  19. Anatomy of a KPI Status = HIGH HIGH Actual Min Target Max Low Low High High Low High

  20. Typical KPI Configuration • KPI Attributes can include: • Actual Value (the only required attribute!) • Sourced from PI, AF 2.0, RDB or an application • Dynamic Attributes (time-varying) • Sourced from PI, AF 2.0, RDB or an application • Static Attributes (non time-varying meta-data) • Auxiliary Data • Responsible Party • Notification Definition • Associated Displays and Links

  21. Anatomy of a single Scorecard • A collection of KPIs related to each other in some significant way at run-time • Collection criteria can be a combination of Dynamic and Static KPI Attributes • Some examples: • All KPIs for Equipment Type 1300, With Priority 1 Alarms in the Western Region • All KPIs for Asset 67 with Status <> Good

  22. Metadata and you

  23. Visual KPI metadata Derived by Visual KPI Status = GOOD Derived from live data Min Low Low Low Target High High High Max Plus 20 user definable attributes of metadata goodness: Create what you like – Area, Unit, Asset, Type, Material, Product… • Tip: • Create a standard set of 20 categories for KPI’s • Create a set of consistent values for the categories for uniform scorecarding everywhere!

  24. How attributes work as metadata Views Scorecards KPI’s KPI 1 KPI 4 KPI 7 KPI 10 KPI 13 KPI 16 KPI 2 KPI 5 KPI 8 KPI 11 KPI 14 KPI 17 KPI 3 KPI 6 KPI 9 KPI 12 KPI 15 KPI 18

  25. Each KPI can have different attributes Views Scorecards Attributes: Asset: Location: Fuel: … Turbine Scranton Coal … Attributes: Asset: Location: Fuel: … Turbine Altamont Wind … KPI 1 KPI 4 KPI 7 KPI 10 KPI 13 KPI 16 KPI 2 KPI 5 KPI 8 KPI 11 KPI 14 KPI 17 KPI 3 KPI 6 KPI 9 KPI 12 KPI 15 KPI 18

  26. Scorecard organization Select KPI’s where Equipment = Turbine and Plant = St. Paul and Fuel = Wind Views Scorecards Scorecard 1 Scorecard 4 Scorecard 8 Scorecard 14 Scorecard 15 KPI’s KPI 1 KPI 4 KPI 7 KPI 10 KPI 13 KPI 16 KPI 2 KPI 5 KPI 8 KPI 11 KPI 14 KPI 17 KPI 3 KPI 6 KPI 9 KPI 12 KPI 15 KPI 18

  27. Scorecard organization Select KPI’s where Equipment = Turbine and Plant = Denver and Fuel = Hope Views Scorecards Scorecard 1 Scorecard 4 Scorecard 8 Scorecard 14 Scorecard 15 KPI’s KPI 1 KPI 4 KPI 7 KPI 10 KPI 13 KPI 16 KPI 2 KPI 5 KPI 8 KPI 11 KPI 14 KPI 17 KPI 3 KPI 6 KPI 9 KPI 12 KPI 15 KPI 18

  28. View organization Select Scorecards where Assets = Turbine Views View 13 View 16 View 14 View 17 Scorecards Scorecard 1 Scorecard 4 Scorecard 8 Scorecard 14 Scorecard 15 KPI’s KPI 1 KPI 4 KPI 7 KPI 10 KPI 13 KPI 16 KPI 2 KPI 5 KPI 8 KPI 11 KPI 14 KPI 17 KPI 3 KPI 6 KPI 9 KPI 12 KPI 15 KPI 18

  29. Dealing with Many KPIs is Hard • Most companies have hundreds or even thousands of KPIs • Beyond a few dozen KPIs, the Scorecard Format suffers. Enter the KPI Map • KPI Map is good for up to hundreds of KPIs • Example: • All KPIs from the NE region • All Wind Farm Assets

  30. Even more KPIs – Use Rollups! Introducing Transpara’s True Roll-UpTM • The downside of typical rollup strategies: • Rollups typically use “worst-case” • Overstates low-level problems • Transpara’s True Roll-Up (TRU): • Designed to accurately reflect the state of the entire hierarchy regardless of the number of KPIs involved.

  31. What is True Roll-UpTM? • Not “worst-case” but the entire state map of all KPIs • TRU Chart as Percentage Bar or a Percentage Pie chart. • Drill-downs automatically adjustfor total number of KPIs in hierarchy • The TRU Chart at any level in the hierarchy shows the percentage in any state for all KPIs below that level

  32. Example Screens

  33. Configuration

  34. Thunderstorm Ramp Event Demo Visual KPI Demo

  35. On-demand data • Leverage data from existing systems • Use any desktop, tablet or laptop • Access from any mobile device • Gives field personnel “one version of the truth” • Increases compliance with unified view of assets • Speeds response to critical events 100’s of Data Sources

  36. Reported Financial Benefits • Western Power • Projected: over $35 million USD in benefits in first 3 years • National Grid • $100,000’s saved after initial roll out • Cost avoidance – saves up to $100,000/incident • Cost savings – leverages existing • Mobile devices, networks • In-place systems • Reduced overtime • ROI in less than 6 months • Wide acceptance: more expected savings

  37. Visual KPI enhancements • Scalability: • Response times and reliability • More robust connection to PI • Friendly PI data management • SharePoint 2007: • Visual KPI Web Parts • Interoperable with RtWebParts from OSIsoft • Visual KPI SDK: • Mashups • Integration with desktop apps • Auto-creation of scorecards based on databases • Time-based KPI’s • Embedding PI into Visual KPI • Allows time-based selection: • Show me all the KPIs whose status has been High or HighHigh for at least 1 hour • Show me all the KPIs who have entered a non-normal state in the last 30 minutes • Visual AF: • Walks in-place AF hierarchy • Allows users to easily create scorecards based on AF

  38. Visual KPI 4.0 and beyond • Scalability improvements- 100K KPIs • Export Trend & scorecard data to Excel • Auto column expansion • Pagination, Sort by column, Second y-axis • Multi-select Actuals from Scorecard to Trend • Table scorecards • KPI Type, Color Schemes • Write-backs to PI

  39. Visual KPI Summary • Creates Corporate Transparency by repurposing and delivering hard-to-access data to mobile and desktop devices • Uses existing security infrastructure; leverages existing technology investment • Encourages new use and improved analysis of existing data – do more with less • Meets user demand by providing actionable information sized to fit display restrictions of device • Deployment and configuration is simple and can be accomplished in a few hours • AEP, Genentech, Allegheny and National Grid projects were less than a single day.

  40. Contact information: • Michael@Transpara.com (both e-mail and IM) • (925) 218-6983 • Gregg@Transpara.com • Try the demo on your own device: • http://demo.transpara.com

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