2012 04-19 gis interest group webcast - final

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  • 1. GIS Interest Group Mitigating Data Quality IssuesBaker Lyon, Mike Tao and Robert Sarfi Boreas Group John J. Simmins Senior Project Manager GIS Interest Group Webcast April 19, 2012
  • 2. Agenda • Legal Notice • Mitigating Data Quality Issues – Introduction – Data Maintenance Processes – Technology Enablers – Conclusion • General Discussion • Next meeting…© 2012 Electric Power Research Institute, Inc. All rights reserved. 2
  • 3. Legal Notices • Please observe these Antitrust Compliance Guidelines: – Do not discuss pricing, production capacity, or cost information which is not publicly available; confidential market strategies or business plans; or other competitively sensitive information – Be accurate, objective, and factual in any discussion of goods and services offered in the market by others. – Do not agree with others to discriminate against or refuse to deal with a supplier; or to do business only on certain terms and conditions; or to divide markets, or allocate customers – Do not try to influence or advise others on their business decisions and do not discuss yours except to the extent that they are already public© 2012 Electric Power Research Institute, Inc. All rights reserved. 3
  • 4. Helpful Ground Rules • Please silence your cell phone and place away from your desk phone. It can cause interference. • Please mute your phone when you are not speaking. • Do NOT place the call on hold to take an incoming call. • This webcast is being recorded. Your continued participation in the call is considered your acceptance to being recorded. – Do not disclose any information you consider proprietary. – Remember that any you say will be available to the members of the interest group© 2012 Electric Power Research Institute, Inc. All rights reserved. 4
  • 5. Mitigating Data Quality Issues© 2012 Electric Power Research Institute, Inc. All rights reserved. 5
  • 6. Common Data Quality Concerns “We react inconsistently “We react slowly to to information shifting work requests.” volumes due to “We execute “We have costly manual resource simple business and inconsistent allocation tasks with high asset processes.” skill and high maintenance cost resources.” processes.” “Process automation is “We have minimal limited by our “Process ability to accurately incomplete and standardization is and quickly inaccurate limited by vertically measure our operational data.” business integrated systems.” performance.”© 2012 Electric Power Research Institute, Inc. All rights reserved. 6
  • 7. The Smart Grid and Data Reliance© 2012 Electric Power Research Institute, Inc. All rights reserved. 7
  • 8. Causes of Data Issues Initial Data Quality • Poor quality source data; • Incomplete data migration and conversion from paper maps and field data collection. GIS Data Quality Data Maintenance Issues • Ambiguous definition of data ownership and access rights; • Poor data quality control processes / practices; • Deferred data update and maintenance.© 2012 Electric Power Research Institute, Inc. All rights reserved. 8
  • 9. Facets of Data Quality and Typical Issues • Data gaps Cost (Update and Consequence) • Redundancies with other systems • Lack of currency with system “as-built”Accuracy Timeliness • Inaccuracies with the field To Spatial OfReal World Update • Inaccurate or unavailable Data landbase, • Customer to transformer connectivity by phase is Ease of uncertain. Completeness Correlation © 2012 Electric Power Research Institute, Inc. All rights reserved. 9
  • 10. Benefits of Improved GIS Data • Reduction in the overall cost of operations as a whole: o Sloppy data may be easier and cheaper to maintain, but yields poor engineering decisions which cost more; • Increase efficiencies in implementing and troubleshooting Smart Grid communications issues; • OMS and DMS improvement, e.g. reduced outage duration and cost; • Improved crew efficiencies due to improved distribution system representation; • Improved load forecasting and system planning effectiveness; • Reduced work order creation, construction, and close out process time • Improved material management and forecasting efficiency • Enabled information exchange with internal and external agencies • Improved safety due to more accurate facilities records© 2012 Electric Power Research Institute, Inc. All rights reserved. 10
  • 11. Data Maintenance Challenges • Define data ownership and access rights; • Understanding touchpoints with other business areas – Who are the GIS users; • Develop processes and practices to fill current data gaps; • How to correlate multiple data sources; • Reduce data redundancies – Create a single source of GIS data; • Reduce duplicate data entries; and • Implement work process to enable efficient and accurate data creation, quality control, and maintenance.© 2012 Electric Power Research Institute, Inc. All rights reserved. 11
  • 12. Integrated Design Process© 2012 Electric Power Research Institute, Inc. All rights reserved. 12
  • 13. Graphical Design Functions and Benefits Analysis Asset Permit/ Management Financials Tools Mgmt. ROW Reporting Functions Graphical Design • Work Initiation Benefits • Graphical Location of Work Request • Work Request Estimating • Expediting designs • Graphical Placement of Facilities • Construction standards • Auto-Generation of Graphical Designs • Accurate facility information • Auto-Design Templates • Accurate connectivity model • Back Population of Facility Attribution • Efficiency between WMS/ GIS • Auto-Facility Connectivity • Auto posting of facilities • GIS - WMS Integration • Less tedious than WMS design Outage Mobile Workforce Work Graphical Maintenance Management Management Management Design Management GIS and Facilities Management Facility Network Model and Analysis Tools 13© 2012 Electric Power Research Institute, Inc. All rights reserved.
  • 14. Technology Enablers© 2012 Electric Power Research Institute, Inc. All rights reserved. 14
  • 15. Smart Grid – A Convergence of Technologies Network Analysis Planning & Engineering GIS Work Order Drafting (Graphic Design) & Design AMI Home WMS (MDM) Automation and Demand Response Schedule and DMS Dispatch WAN & Distribution MDT Automation© 2012 Electric Power Research Institute, Inc. All rights reserved. 15
  • 16. Smart Grid Technology Architecture© 2012 Electric Power Research Institute, Inc. All rights reserved. 16
  • 17. Key Concepts Concept of a Data Store • Conceptualization of a single, “virtual” data repository o Defined system and data owners o Some data stored in GIS, other shared but, to users, appears to be stored in GIS • System integration is the enabler • Integration of data maintenance into work processes o Eliminate processes specific to maintaining data Benefits of a Data Store • Centralize the enforcement / validation / business rules • Enterprise level performance measurements, including data quality • Development of a consolidated data quality improvement plan© 2012 Electric Power Research Institute, Inc. All rights reserved. 17
  • 18. Conclusion • Smart Grid consists of systems already in many utilities – GIS, OMS, SCADA, MDA, CMMS, AMI, etc. • High GIS data quality is necessary for the Smart Grid to be effective • GIS data quality improvement can be achieved through implementing process changes to automated data flows • The true cost of bad data quality is not known© 2012 Electric Power Research Institute, Inc. All rights reserved. 18
  • 19. Data Quality Survey • Part 1 of a two part survey • Question include – Demographics – Estimated completeness – Estimated correctness – Effects of bad data – Process questions – Change of data w/time© 2012 Electric Power Research Institute, Inc. All rights reserved. 19
  • 20. Data Quality Survey• Survey available through the GIS Interest Group and at: – http://www.surveymonkey.com/s/EPRI_GIS_Data_Quality_Project_1• Also – www.smartgrid.epri.com – Select the Resources tab – Select GIS Interest GroupPlease complete the survey by Thursday, April 26th!© 2012 Electric Power Research Institute, Inc. All rights reserved. 20
  • 21. EPRI and CPS Energy Invite Attendees and Exhibitors to the 2012 PQ and Smart Distribution Conference and Exhibition Join Us for This Special Event in San Antonio, Texas, USA Monday, June 4, 2012 - Thursday, June 7, 2012© 2012 Electric Power Research Institute, Inc. All rights reserved. 21
  • 22. Together…Shaping the Future of Electricity© 2012 Electric Power Research Institute, Inc. All rights reserved. 22