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Using hana to add value to electric & gas revenue integrity

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  • 1. A collaboration of: Using HANA To Add Value to Electric & Gas Revenue Integrity Gelyn M. Almanzar Public Service Enterprise Group (PSEG) Tracy Kirk Public Service Enterprise Group (PSEG)
  • 2. P • Introduction & Overview of PSE&G S • HANA Business Case E • SAP HANA POV for PSE&G G • PSEG HANA RID Roadmap H • Crawl, Walk, Run Approach A • PSE&G HANA Next Steps N • Lessons Learned Points to Take Home A • Questions Slide 2
  • 3. PSE&G at a Glance 3 • New Jersey’s oldest and largest regulated utility • Provide service to 75% of New Jersey’s population • 2.4 million customers – 2.2 million Electric customers and 1.8 million Gas customers • Robust Appliance Service and HVAC competitive business • Most Reliable Electric Utility in 2012 – 5th time in last 8 years • PSE&G ranks 3rd among all utilities in installed solar capacity
  • 4. Revenue Integrity Department (RID) 4 Prevent, identify, and correct any and all meter conditions causing potential lost revenue to PSE&G, including malfunctioning equipment, non-registering meters, incorrect multipliers, human error, and theft of service 10 Investigators handle approximately 7000 cases annually The Employee Incentive Award Program offers a cash award to an office or field employee providing a lead resulting in the recovery of lost revenue. This is a $300,000 program annually
  • 5. Slide 5 Revenue Integrity Department (RID) Use Case Meter Corrected Meter Goes Bad Meter Identified Once the bad meter is identified and corrected, the customer is billed for lost revenue. Collecting this is not always successful. After the meter is corrected, a new revenue stream is created. Faster, more accurate identification of bad meters is the key to revenue recovery
  • 6. • We engaged with SAP in a Proof of Value for HANA exercise • SAP conducted a series of workshops with the Line of Business • Captured high-level business requirements from the business • Worked with business to identify ECC tables needed for RID Reporting • Business Intelligence team worked with SAP to extract data and send it to SAP HANA Labs to conduct a Proof Of Value Revenue Integrity HANA Proof of Value Slide 6
  • 7. 7 RID Manual Reporting and Analytics Challenges 6 months Extract X 4 hours = 24 hours 2 HRS Manually Emailed
  • 8. 8 RID Future State with HANA
  • 9. 9 SAP Proof of Value HANA Results PSEG BI group packaged the extracted ECC tables and sent to SAP Labs SAP produced HANA data models and provided a look into the basic reporting and analytics needs for RID SAP Table Tech Name SAP Table Description Number of Records ETTIFN Installation Table 1,709,155,620 EABL Meter Reading Documents 164,311,266 EABLG Meter Reading Reason 165,344,425 EVER IS-U Contract 6,525,758 EANLH Installation Time Slice 7,429,901
  • 10. PSEG RID HANA SAP - POV Results Slide 10 2.6M Customers 3.7M Meter 200M Rows Data 6 Months Data 93 Seconds Response Time SAP HANA In Memory System
  • 11. PSEG HANA Roadmap Slide 11 Crawl Walk Run Hardware Purchase BI Team Training Investment Proposal System Readiness Define 3 Project Tracks Business Requirement Gathering Project Plan (Agile) Extracted tables from Prod system Created CSV Files HANA CSV Data Loads HANA Data Model BOBJ Webi & Dashboard Reports Data Services ETL Jan Feb March Apr May June July Aug
  • 12. PSEG HANA Investment - Crawl Slide 12  Our IT SLT team decided to build HANA expertise in-house  Invested $50K in HANA training for BI group (6 resources)  HA100 – HANA – Introduction & Overview  HA200 – Operation and Administration  HA300 – Implementation & Modeling  Purchased HANA  Purchased DELL R910 with Fusion IO Cards  Racked up DELL server in local Data Center (Newark, NJ)
  • 13. PSEG HANA Investment - Walk Slide 13  In-depth Business Requirement Gathering Sessions  Interactive discussions with SMEs to finalize the business Logic  Project Planned with “Agile” approach  Defining the “Start to Finish” implementation path (3 Project Tracks)  Get the System Ready  Data Identification and ETL Plan  Alternate Data Extraction Strategy (.CSV files) to mitigate the delay in Data Services Deployment  Coordinate with SAP to resolve the Data Services Technical Issues
  • 14. PSEG HANA Investment - Run Slide 14  File specification and coordination for Flat File extraction  Initial HANA Data Modeling – Evaluation of alternate Models  Iterative and interactive approach with Business for Data modeling to avoid any “misses” in project Deliverables  Clear definition and strict adherence of Project Plan and Deliverables.  Well integrated team work with HANA and BOBJ resources  Refine the HANA and BOBJ development for Performance and “look and feel” of the reports / Dashboards  Resolve Data Services issues and Optimum Strategy (Full / Delta) Data extraction using Data Services  Switch from HANA modeling to Data Extracted using Data Services
  • 15. Slide 15 Data Extraction • 16 ECC Tables • 240M Rows • CSV Files Created Manual Load • Largest Table 58M Records • Initial Load Average 10hrs Data Service ETL • Largest Table 58M Records • Initial Load Average 4hrs • Delta Monthly load average 7 minutes Model / Reports • Created 8 Models • BOBJ Webi 5 monthly Reports • 2 Xcelsius Dashboards HANA Data Extraction / Load and Models Plan Build Execute
  • 16. 2.6Mcustomers 367M 13 3.7M rows of data months of history meters 60 seconds 26 hours Standard System In-Memory System 1500xfaster PSEG RID POC HANA Results
  • 17. Anticipated Business Benefits Slide 17 Increase the number of cases identified Shorten overall cycle time by reducing time to identify cases Increase percentage of good leads Increase revenue by identifying and working high value leads first Save on Incentive Award program
  • 18. Greatest Insights Engage SAP as a preferred Consultant Partner Identified areas of expertise needed, e.g. ECC, HANA, Data Provisioning, BO, etc. are required to produce a HANA application that can’t be handled by a single area. The sizing of the HANA server affect the sizing of the BO servers. Optimizing the Services configuration on BO 4 start only service that are required and stop those not required. Webi reports have to consider segmenting the data so they can be processed by the BO server. HANA allowed us to load data using complicated business rules processing large amounts of data that couldn’t be previously performed Need to better understand the SAP Router process and what is required to permit SAP to access your system. SAP Modeling Expert may help you to model but will not necessarily have the business expertise to produce a business ready model There are always unforeseen obstacles and roadblocks encountered when utilizing new technologies
  • 19. What did we get right?  System Check and HANA expertise:  SAP performing the system check prior to starting the project and engaging SAP Consulting Service to assist, e.g. Data Services, Modeling, etc  Data Extraction Strategy:  Extracting Data as .csv files (while configuring Data Services)  In Depth, Interactive Discussions with Business:  To understand business scenarios and rules.  Business Expectations:  Setting appropriate and relevant business expectations (Data and Performance)  Proof of Value (Crawl, Walk and then Run):  Deliver limited scope and then extend.  Go Forward strategy for Data Extraction:  Got Data Services fully configured and working to load data into HANA  Agile Project Approach:  Continuous engagement of business through design, build and data validation
  • 20. What would we do differently? • Build a flexible project plan to accommodate the fact that many tasks and durations are not known since it is the first time we are using this technology • Get commitment from other areas (Basis, UNIX, etc.)within IT department to help resolve issues more quickly • Isolate the project team, and have dedicated HANA project resources committed to HANA solution
  • 21. Potential Future PSEG Use Cases Operations  Profitability Analysis at the appliance level  Annual Work Planning  Outside leak investigation review  Spatial representation of operational data  Optimized scheduling of meter route Customer Ops & Service  Accelerate Sales Stats process by improving the extraction performance of bill header data  Campaign planning and tracking  Customer segmentation  Improve worry free contract by better analysis  Proactive management of bill shock  Outage management / Storm Restoration Finance & Trade  Rate Case Analysis  BPC on HANA  Improve FERC Reporting  Risk analysis of trade positions  Generation dispatch from trading floor based on complex models including causal factors  POD analysis for regulatory reporting
  • 22. A collaboration of: Gelyn M. Almanzar PSEG Gelyn.Almanzar@pseg.com Tracy Kirk PSEG Tracy.Kirk@pseg.com