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SEAMS SWIM Dec 2016
- 1. Update on UK Water Industry - Data Analytics for Asset Management Jon Greensill
- 2. SEAMS is the Market Leader for Asset Planning Systems in the UK Water Industry • Founded in 2002 from water sponsored academic research • Company shareholders still included… • Chair of the Analytics working group for • Now working internationally, for example –
- 3. Why SWIM might take advice from the UK…?
- 4. Political Change in 2016 We have a lot in common…
- 5. Of all the privatisations of the Thatcher government, perhaps the most controversial was the privatisation of water… Political Change in 1989
- 6. An Example UK Water Company
- 7. Asset Scope$Spent$IncomeTimetoPlan Price Review Price Review Price Review 5 Years 5 Years 5 Years Price Review 6 months 3 months month+ 7 Days ? v1 v2 v3
- 8. Continue to Simplify the Planning Process… 8 Manages decision analytics from raw data to optimised investment plans. Simple to rerun the analysis given new data.
- 9. Automated Analysis Reports 9 Previously a manual/consultancy exercise – now new results automatically re-configure the model
- 10. Data Quality – Measured and Improved 10
- 11. Output Delivery Incentives What’s the challenge? • Each company has a set of specific outcomes that they must deliver – hard, measurable targets • Companies could choose from a ‘menu’ but had to prove it was choosing items relevant to its own customer base - (Customer Willingness To Pay) • There is serious money at stake. The incentives for the timely completion of major capital projects are high-impact, as minor delays can result in large penalties. • The incentives to reduce water leakage expose companies to penalties in excess of $1.1Bn and rewards of up to $450M.
- 12. Some Example ODI Measures…
- 13. Who is winning so far…?
- 14. 14 DESCRIPTIVE PREDICTIVE PRESCRIPTIVE STRATEGICTACTICALOPERATIONAL What happened to all our assets in the last 10yrs? What happened to groups of assets in the last year? What is happening to our assets today? What will happen to our assets in the next 25yrs? What will happen to our assets in the next year? What will happen to our assets tomorrow? What future investments do we need to make on our assets? What assets do we need to replace or maintain this year? What assets do we need to inspect or maintain tomorrow? Analytics Techniques BusinessRequirements • Long term data collection • Trend analysis on historic data • Understand past performance • Scorecards • Data warehousing • Data mining • Forecasting the future • Probability of failure • Asset deterioration • Statistical analysis software • Long term investment scenarios • Whole life cost modelling • Optimisation and simulation • Uncertainty and sensitivity • Decision support tools • Annual data collection & refresh • Review seasonal trends • Identify localised issues • Dashboards • Annual business reporting • Daily data collection • Real time monitoring of assets • Early warning of faults • Rapid response to asset failure • SCADA and monitoring tools • Detailed data mining • Forecast annual performance • Account for localised factors • Engineering validation • GIS tools and techniques • Annual investment scenarios • Set annual budgets • Set annual performance targets • Candidate assets for investment • Decision support tools • Real time data analysis • Predict highest risk assets • Condition and criticality scores • Process engineering • Integration of analytics to SCADA • Daily schedules of work • Improve operational efficiency • Optimise proactive Investment • Prioritise reactive Investment • Job optimisation schedulers Analytics Matrix
- 15. Another Financial Challenge - Money is Money
- 16. So we offer our support... • • • • 16