- Количество слайдов: 41
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 Conflicting actions • What does the data mean? • Is the data the same? • Does more data help? • Does it mean the same thing to everyone? • Which system or person is right?
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, i. Phone, Blackberry
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!
KPI’s aren’t just for executives anymore • • • Executive • 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
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
The process of KPI creation* Someone tells the company how important these KPI’s are Someone wrangles data together People sit in a room and decide what’s important Someone creates visualizations * Not to scale
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
KPI evolution from Central to Local Centralized Intelligence Sources: Visual KPI SAP PM SAP BW OSIsoft PI MS SQL Oracle Mobile Consumer Someone wrangles data together People sit in a room and decide what’s important Desktop and Mobile User Someone creates visualizations User and KPI Creator Local Sources: • Site Web services • Site databases Actionable Decisions • • • Localized Intelligence
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? )
Now KPI’s can come from everywhere Site Level Roles • Site-centric information • Process or line-specific Division Level Roles • Division Objectives • Supervisory Objectives Business Roles and Objectives • Performance • Planned Performance
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
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
Visual KPI 3. x architecture Any Mobile or Desktop Client Data Sources Visual KPI Excel Editor l l PI System l Meta Data l Equations Configuration only, no runtime association or storage Any RDB l Existing Data l Publish Scorecards via Web Services XML over HTTP Web Services Real-time Data Web Services l Excel 2003 or Excel 2007 with VSTO External KPIs LOB App Visual KPI Server l Link to financials l Composite KPI Engine l Planned values l All meta data in SQL 2005 or 2008 l SAP, MRO, etc. l Windows Server 2003 or 2008 l XML and Web Services-based l Extensible, Programmable
Anatomy of a KPI Status = GOOD Actual Min Target Max Low High
Anatomy of a KPI Status = HIGH Actual Min Target Max Low High
Anatomy of a KPI Status = HIGH Actual Min Target Max Low High
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
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
Metadata and you
Visual KPI metadata Status = GOOD Min Low Low Target Derived by Visual KPI High Max Derived from live data 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!
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
Each KPI can have different attributes Views Scorecards Attributes: Asset: Location: Fuel: … Turbine Altamont Wind … Attributes: Asset: Location: KPIFuel: 16 … KPI 1 KPI 4 KPI 7 KPI 10 KPI 13 KPI 2 KPI 5 KPI 8 KPI 11 KPI 14 KPI 17 KPI 3 KPI 6 KPI 9 KPI 12 KPI 15 KPI 18 Turbine Scranton Coal …
Scorecard organization SELECT KPI’S WHERE EQUIPMENT = TURBINE AND PLANT = ST. PAUL AND FUEL = WIND Views 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
Scorecard organization SELECT KPI’S WHERE EQUIPMENT = TURBINE AND PLANT = DENVER AND FUEL = HOPE Views 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
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
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
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.
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
Thunderstorm Ramp Event Demo VISUAL KPI DEMO
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
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
Visual KPI enhancements • Scalability: – Response times and reliability – More robust connection to PI – Friendly PI data management • Share. Point 2007: – Visual KPI Web Parts – Interoperable with Rt. Web. Parts 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 High 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
Visual KPI 4. 0 and beyond • • Scalability improvements- 100 K 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
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.