................................................................................................. How to turn challenges into benefits in large scale
................................................................................................. How to turn challenges into benefits in large scale multi-national, multi-vendor EDM projects NGU Summit 2009 Portugal 25th June 2009 Gerko Baarslag Managing Director Eneco IT Solutions Simo Makkonen CEO, Process Vision Contents ................................................................................................. • Context: Eneco and Process Vision shortly • Customer case: large scale EDM project – Project drivers and targets – Challenges and lessons learned – Successes – Conclusions • Hyphotheses and discussion • Summary 2 ........................................................................ Introduction Process Vision: Profile ................................................................................................. • Process Vision Oy is one of the leading energy IT suppliers in Europe • Process Vision provides versatile IT systems, solutions and services for energy markets • Process Vision GENERIS energy IT platform delivers solutions for – meter data management, meter asset management, energy data management, contract and porfolio management, trades and risks management, and billing and customer services • With over 300 installations and over 200 customers in Europe, Process Vision has strong footprint and extensive experience – also for supporting future business needs of energy market 3 ........................................................................ GENERIS Manage all energy data with one standard product ................................................................................................. Meter roll-out management Versatile reporting Regulatory compliance duties Second generation solution with over 300 installations for low risk implementation Forecasting Pricing and quotes management Open position management Meter asset repository Meter Assets Mgmt Extranet services Validated meter data Profitability analyses Balance Contract Settlement & Portfolio & Mgmt Mgmt Trade & Risk Mgmt Control Displays Meter Data Mgmt Price fixing and hedging Scenario analyses Validated billing data Billing Data Mgmt Reporting Platform Info Flow Manager System Integration & B2B communication SCADA NIS CRM/CIS/ERP Modularity and scalability enables extending system according to business needs for optimal TCO Comprehensive task automation and data quality control save resources Optimal user experience with business process based user interface improves quality GENERIS Platform AMR/AMM/AMI For electricity, gas, district heating, district cooling, water and for all parties for streamlined IT landscape Business partners Flexibility provides cost effective regulatory compliancy ........................................................................ Introduction Eneco: Profile ................................................................................................. • Eneco is among the top energy suppliers in the Netherlands. • Eneco has an integrated distribution strategy covering the generation, transmission, supply, metering and billing of gas, electricity and heat. • Eneco Energie serves a total of around 2 million business en residential customers. • Eneco employs appr. 5,300 people. • Eneco Value: continuity of energy on a sustainable basis • Eneco Holding consist of three companies: Eneco; Joulz (Infrastructure) & Stedin (Grid Operator) 5 ........................................................................ ................................................................................................. Customer case: large scale EDM project Aorta 6 ........................................................................ Project Aorta introduction Overview ................................................................................................. Aorta = Application optimisation for reconciliation and allocation (balance settlement) Challenge: deliver and deploy a 4 000 000 metering points allocation and reconciliation system harmonization project for electricity and gas 7 ........................................................................ Key drivers and targets ................................................................................................. Project drivers and targets •To get allocation and reconciliation processes under proper control and provide correct and timely results. •To clamp down on administrative losses in allocation. •Flexible and Future proof IT landscape •Rationalization of the IT landschape: – Reduction in Total Cost of Ownership – Modernization of Process Architecture 8 ........................................................................ Key Drivers and targets ................................................................................................. Before Aorta situation Gegevensregister Mecsico e-Netbeheer Reconciliatie G GENERIS XIB RIA Reconciliatie E ARIE Allocatie E TENNET Mecsico Allocatie G MVS Kopie AR EHTO/ GENERIS Reconciliatie G XIB NetBeheer Message Handler (NBMH) ECH HERA+ Allocatie G ENBU Contracten & Billing Logisch Aansluit Register (LAR) SVO berichtenverkeer Reconciliatie E Allocatie E Targeted situation SVO berichtenverkeer Contracten & Billing Gegevensregister 9 Allocatie G Additionele functionaliteit CAS1 Additionele functionaliteit Additionele functionaliteit GENERIS XIB Huidige knelpunten Huidige knelpunten HERA+ functionaliteit Reconciliatie G Reconciliatie E Huidige knelpunten ........................................................................ Allocatie E TENNET NetBeheer Message Handler (NBMH) ECH Procesondersteuning Challenges and lessons learned Challenges ................................................................................................. Main challenges: •Initial project plan: too optimistic; wishful thinking planning •Requirements based on as is situation •Too many layers of communication between different parties (in Netherlands & Finland) •Master data quality dubious •Advanced database settings and fine-tuning as data amount increased 10 ........................................................................ Challenges and lessons learned Lessons learned ................................................................................................. •Too many cooks spoil the broth – get a few good ones, and then: •Involve all parties in project planning and steering groups since the beginning •Do not underestimate efforts needed to verify, correct and maintain master data quality •Enough technical & functional expertise shall be involved during the comple project timeline and onsite! 11 ........................................................................ Situation today ................................................................................................. New system architecture implemented and in production since March 2008 for allocation and since September 2008 for the complete project scope Application is stable and the allocation and reconciliation processes are in control for all 4 000 000 metering points. Results are up-to-date Administrative losses reduced by 30% 12 ........................................................................ Conclusions ................................................................................................. Project was challenging from very beginning but ended up with great success. The persistance of Eneco and the project team to ’get it done’ pulled the project through some rough patches. Trust, and good, direct communication are crucial. The GENERIS platform that was selected for its high performance and flexibility showed its strengths by supporting performance and usability targets well over the limits. 13 ........................................................................ ................................................................................................. Hypothesis and discussion 14 ........................................................................ Hypotheses – EDM project ................................................................................................. 1. Implementation: Challenge with EDM is NOT software but real issues are – Expectation management – Data cleansing 2. Go Live: After implementation EDM project should do a ‘change stop’ 15 – Forces the users to get used to the system – Stabilize processes and software version ........................................................................ Hypotheses – Future aspects ................................................................................................. 1. The amount of energy measurement data will increase dramatically during the next decade due to - Smart metering - EU 2020 objectives - Environmental awareness lures citizens to ask for more information Future EDM project will require much more attention and budget than earlier; are you prepared to put more management attention to information management in the future? 16 ........................................................................ Hypotheses – Future aspects ................................................................................................. 2. Challenges to gather, validate and store all the measurement data will increase due to - Data volumes are extremely large - Privacy policies and confidentiality will be increasingly discussed Is your organisation ready for the big change that will take place in the future? 17 ........................................................................ Hypotheses – Future aspects ................................................................................................. 3. In the future, measurement data will be utilized by increasing number of processes and users which requires re-thinking of IT system architectures like - Billing engine only one user of the measurement data - EDM used only for market regulatory compliance MDM required as a central hub to manage new needs. Is your IT landscape ready for this change? 18 ........................................................................ Summary ................................................................................................. The experiences in large scale EDM projects shows that – implementation project requires more resources than usually is expected e.g. due to data cleansing – EDM and MDM solutions are critical and should not be under estimated by top management The – – – – 19 future proven EDM must take into consideration increased number of meter data new architecture by separating MDM from EDM flexibility in system integration increased number of data users ........................................................................ Q&A ................................................................................................. Thank you for your attention! 20 ........................................................................
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