Case study - South East Water Implementation of a risk-based approach to asset management planning

1. Case study - South East WaterImplementation of a risk-based approach to asset management planning A Neemann, Investment Planning Team Leader Tynemarch Systems Engineering South East Water S C Cook, Managing Director

2. Overview of Approach/Methodology for Risk Assessment • High-level Nature of analysis Not detailed QRA Source to DMA • Components Resource and supply system broken down into components • Service measures Interruptions, Water Quality, Health & Safety, ... Pair-wise comparisons • Risk Related to asset failures Clear separation of tendency and consequence

3. Overall Risk Assessment Methodology Raw water Water treatment Pumping Transmission Storage Distribution Serviceability to Customers Statistical Analysis Translation Failure data Raw water failure of given magnitude Failure duration > survival time Demand vs Storage Analysis Attributes Attributes

4. Dependency Trees Interruptions Bursts Operation Infrastructure Environment High pressure Change in pressure Frost damage potential Mains age Mains dia Mains material AC, Cu, Pb Alk, DI, GRP,.. CI, GI, Mains material type for a given DMA

5. Dependency Trees Service measure “risk” for a specific DMA Weighted Service Measure Interruptions Water Quality Pressure .... Tendency tree Consequence tree Tendency tree Consequence tree Data from a specific DMA

6. Integrated Consequence Modelling & Optimisation

7. Interpretation of Results - Pareto Plots • Single Service Measure, stacked Service Measure • Shape of curves • Flat/steep, hot-spots etc. • Target scores • Identification of areas for attention Weighted Risk Grade /1000km 12 Water Quality Low Pressure 10 Leakage Interruptions 8 H&S 6 4 2 0 DMA

8. Verification

9. Analysis for Investment Planning • Objectives Identifying most serious problems (which assets, which DMAs, which SMs) Where and how to make greatest impact on risk/service to customers How to ensure similar levels of risk across all DMAs Anticipating future problems Assess efficacy of schemes Identifying economic levels of investment • Analysis Ranking/banding/pareto/drill-down Change in risk with time Sensitivity/contributions Scenario analysis Optimisation Determination of most cost-effective means (capex/opex) of achieving specific risk objectives accounting for change in risk with time spatial distribution of risk distribution of risk across service measures

10. Next steps Optimisation of risk (idealised) Optimisation of risk Stage 1 • 1st pass optimisation of risk reduction • Generic projects options • Unit price models for used costing of pipes, valves etc. • Risk reduction calculated in terms of cost using risk and costing models Aim to decease risk to just below SEW Acceptable without overspending Current 10 8 Acceptable 6 Risk Score 4 2 0 1 50 100 150 200 250 300 350 400 450 Post-investment DMA Ranking 10 Inherent Risk 8 Acceptable 6 4 Risk Score Over Spend 2 0 1 50 100 150 200 250 300 350 400 450 DMA Ranking

11. Next steps Optimisation of risk Engineering to supply actual projects in highlighted DMAs Optimise the combination of actual schemes Combination 1 Combination 2 Combination 3 Combination 4 Combination 5 Residual Risk Combination 6 Combination 7 Combination 8 Combination 9 Combination 10 Combination 11 Combination 12 Combination 13 Increasing Cost

12. Example results - Distribution system risk profile • 35% of DMAs have unacceptable levels of risk • Capital maintenance will be targeted on a customer weighted risk basis

13. Southern Region - Overall Risk Example results - Distribution system risk geographically

14. Example results - Distribution costs of asset failure per DMA • Profile more pronounced when risk is converted to £’s using the ‘Costs of asset failure model’ • Leading to improved targeting of assets

15. Utilising elements of the approach • Elements of the approach are currently being used to prioritise capital maintenance for underground assets • For example all prospective mains renewals projects have ‘Before and After’ risk scores calculated to aid the capital approvals process

16. Results - Works unit processes ranked by total risk over a 3 year period Barcombe All scores for all 3 years 3500 3000 2002 2007 2012 2500 2000 1500 1000 500 0 Works Ozonation Abstraction Contact Tank GAC Filtration De-Chlorination Control Services Electricity Supply Coagulant dosing Sludge Treatment Roads and Fences Chemical Services Filterwash Services Polyelectrolyte dosing Upward-flow Clarifiers Intermediate-lift Pumping Flocculation & Coagulation RG Filtration (sand filtration) Chlorination - Final disinfection

17. Results - works unit processes ranked by serviceability criteria Barcombe All scores for year 1 1400 Capacity/throughput Sludge 1200 Abstraction Licence 1000 Discharge Consent 800 Health and Safety Water Quality 600 400 200 0 Works Ozonation Abstraction Contact Tank GAC Filtration De-Chlorination Control Services Electricity Supply Sludge Treatment Coagulant dosing Chemical Services Roads and Fences Filterwash Services Upward-flow Clarifiers Polyelectrolyte dosing Intermediate-lift Pumping Flocculation & Coagulation RG Filtration (sand filtration) Chlorination - Final disinfection

18. Results - expected number of events by unit process Expected number of events/year 9 8 2002 2007 2012 7 6 5 4 3 2 1 0 Works dosing dosing Supply Sludge Fences Services Services Clarifiers Pumping Chemical Electricity Ozonation Coagulant Treatment Filterwash Roads and Abstraction Coagulation Upward-flow RG Filtration Contact Tank Chlorination - Flocculation & GAC Filtration Polyelectrolyte (sand filtration) Intermediate-lift De-Chlorination Control Services Final disinfection

19. Results - works ranked by risk throughput reduction index Pareto plot of Capacity/throughput scores 3,000 Year 10 2,500 Year 5 2,000 Year 1 1,500 1,000 500 0 Clayton Britty Hill Rathfinny Greatham Friston PS Cliddesden Forest Row Barcombe 1 Birling Farm Tower House Tilford Meads Tilford Wellesley Sweet Willow Wood Hindhead Reservoir Poverty Bottom No.4 Sheet (inc. Oakshott) Victoria (inc. Bourne) Bray Pumping Station Coggins Mill (incl. Sharnden)

20. Key Challenges • Initial lack of data in appropriate format • Obtaining buy-in from key internal business units such as operations • Data collection and collation from various company systems • Data collection from key operational staff/experts • Utilising results most effectively Indirect Benefits • Focusing our data collection efforts and systems going forward • An improved above ground asset planned and reactive maintenance system (linked to risk model) • Improved asset inventory system • Improved strategic model of company

21. Summary • We are making good progress on determining our capital maintenance requirements using a bottom-up risk based approach • Will be the first time SEW can objectively identify the priority of projects uniformly on a company-wide basis • Already utilising elements of the approach as part of the capital approvals process • Focus over the coming months is to complete the model and determine capital maintenance schemes for SEW’s PR04 business plan using the bottom-up approach