1. September 10, 2008 Mobilizing Transparency 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. 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 About Transpara & Visual KPI

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 N EED 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* People sit in a room and decide what’s important Someone wrangles data together Someone creates visualizations Someone tells the company how important these KPI’s are * 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 People sit in a room and decide what’s important Someone wrangles data together Someone creates visualizations Sources: SAP PM SAP BW OSIsoft PI MS SQL Oracle Mobile Consumer Desktop and Mobile User Actionable Decisions User and KPI Creator Local Sources: Site Web services Site databases Centralized IntelligenceLocalized Intelligence Visual KPI

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 Site Level Roles Division Level Roles Business Roles and Objectives Site-centric information Process or line-specific Division Objectives Supervisory Objectives Performance Planned Performance

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 PI System Real-time Data Meta Data Equations Any RDB Existing Data External KPIs LOB App Link to financials Planned values SAP, MRO, etc. 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 Visual KPI Excel Editor Excel 2003 or Excel 2007 with VSTO Configuration only, no run- time association or storage Publish Scorecards via Web Services Data Sources Any Mobile or Desktop Client Web Services XML over HTTP

16. VISUALIZING KPI’S

17. Anatomy of a KPI MinMax Actual Low High LowHigh Target Status = GOOD

18. Anatomy of a KPI MinMax Actual Low High LowHigh Target Status = HIGH

19. Anatomy of a KPI MinMax Actual Low High LowHigh Target Status = HIGH 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. Derived by Visual KPI Derived from live data Visual KPI metadata MinMaxLow High LowHighTarget Status = GOOD Plus 20 user definable attributes of metadata goodness: Create what you like – Area, Unit, Asset, Type, Material, Product… 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! 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 KPI 1 KPI 2 KPI 3 KPI 4 KPI 5 KPI 6 KPI 7 KPI 8 KPI 9 KPI 10 KPI 11 KPI 12 KPI 13 KPI 14 KPI 15 KPI 16 KPI 17 KPI 18 Scorecards Views KPI’s

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

26. Scorecard organization S ELECT KPI’ S WHERE E QUIPMENT = T URBINE AND P LANT = S T. P AUL AND F UEL = W IND KPI 1 KPI 2 KPI 3 KPI 4 KPI 5 KPI 6 KPI 7 KPI 8 KPI 9 KPI 10 KPI 11 KPI 12 KPI 13 KPI 14 KPI 15 KPI 16 KPI 17 KPI 18 Scorecard 1Scorecard 4 Scorecard 8 Scorecard 14 Scorecard 15 KPI’s Scorecards Views

27. Scorecard organization S ELECT KPI’ S WHERE E QUIPMENT = T URBINE AND P LANT = D ENVER AND F UEL = H OPE KPI 1 KPI 2 KPI 3 KPI 4 KPI 5 KPI 6 KPI 7 KPI 8 KPI 9 KPI 10 KPI 11 KPI 12 KPI 13 KPI 14 KPI 15 KPI 16 KPI 17 KPI 18 Scorecard 1Scorecard 4 Scorecard 8Scorecard 14 Scorecard 15 KPI’s Scorecards Views

28. View organization S ELECT S CORECARDS WHERE A SSETS = T URBINE KPI 1 KPI 2 KPI 3 KPI 4 KPI 5 KPI 6 KPI 7 KPI 8 KPI 9 KPI 10 KPI 11 KPI 12 KPI 13 KPI 14 KPI 15 KPI 16 KPI 17 KPI 18 Scorecard 1Scorecard 4 Scorecard 8 Scorecard 14 Scorecard 15 View 13 View 14 View 16 View 17 KPI’s Scorecards Views

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! 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. I NTRODUCING T RANSPARA ’ S T RUE R OLL -U P TM

31. What is True Roll-Up TM ? Not “worst-case” but the entire state map of all KPIs TRU Chart as Percentage Bar or a Percentage Pie chart. Drill-downs automatically adjust for 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

33. Example Screens

34. Configuration

35. VISUAL KPI DEMO Thunderstorm Ramp Event Demo

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

37. 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

38. 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

39. 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

40. 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.

41. 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