Prescriptive analytics can provide 7-17% cost savings for asset management planning by optimizing investment decisions. Electricity North West piloted prescriptive analytics to understand benefits and answer "what if" scenarios, like minimizing expenditure while maintaining risk levels or finding the lowest risk score within a budget. Their dashboards and reports visualized optimized investment plans across asset classes under different constraints. The presentation encouraged attendees to identify their own useful "what if" questions and assess their ability to implement analytics.

1. Making Asset Management Active
with Analytics
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April Hutchen a.hutchen@seamsltd.com
Phil McFarlane – Electricity North West

2. Agenda
• Benefits - why use Analytics?
• Overview of Analytics in Asset Management
• What is required?
• Dashboards, Reports & Visuals
• View from the industry
– Electricity North West’s journey
– ‘What if’ scenario modelling’
• Break-out Session - ‘what if’ questions
• Close
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3. Benefits of Prescriptive Analytics
• 7-17% cost savings compared to a triggered or
prioritised approach to planning
• Defensible business plans & budgets
• Reduced planning costs
• Improved customer service levels
• Achieve key KPIs, both regulatory and non-regulatory, at
lowest whole life cost
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4. IAM Asset Management Anatomy
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5. What is needed?
1. Data – asset health, intervention (cost/benefit), faults, project
– Source systems, expert opinion, best practice and data infill
2. Way to analyse information
– spreadsheets, software, agreed processes
3. Business Objectives & KPIs – regulatory & non-regulatory
4. Business commitment & buy-in from key personnel
5. Means to understand and present the information
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6. What is Analytics?
Analytics is the use of data to deliver insight & support better
decision making
• Analytics is a combination of mathematics & statistics, data techniques and
advanced algorithms to quantify and predict performance, risk, condition, service,
cost & revenue with rich data visualization to communicate insight
• Successful Analytics projects rely on the experience and expertise of specialists to
enable the organisation to understand their data, use it to generate value and
communicate effectively to stakeholders
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7. 7
DESCRIPTIVE PREDICTIVE PRESCRIPTIVE
STRATEGICTACTICALOPERATIONAL
What happened to our assets
in the last 10yrs?
What happened to our 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 are the future needs
of our assets?
What do we need to do to our
assets this year?
What activities do we need to
tomorrow?
• Historic asset trends
• Performance
• Reliability
• Utilisation
• Demand profiling
• Asset deterioration
• Forecasting Risk
• Sustainability
• Climate impacts
• Long term investment scenarios
• Financabilty
• Risk mitigation & management
• Revenue modelling
• Supply & Demand balancing
• Asset policy
• Customer trends & preferences
• Annual cost & revenue reporting
• Unit cost analysis
• Asset reliability & utilisation
• Root cause analysis
• Real time monitoring of assets
• Operational efficiency
• Early warning of faults
• Rapid response to asset issues
• Asset survey
• Reliability analysis
• Forecast annual performance
• Management account forecasts
• Resource gap identification
• Seasonal impacts
• Annual investment scenarios
• Annual targets
• Assets maintenance planning
• Asset utilisation planning
• Resource planning
• Contractor & purchasing planning
• Issue identification
• Hotspot analysis
• Client feedback analysis
• Peak demand forecasting
• Weather impacts
• Optimise proactive Investment
• Prioritise reactive Investment
• Job scheduling
• Customer notification process
Describing Analytics – Analytics Matrix

8. Definition of Prescriptive Analytics
• “…the application of logic and mathematics to data to specify a
preferred course of action. While all types of analytics ultimately
support better decision making, prescriptive analytics outputs a
decision rather than a report, statistic, probability or estimate of
future outcomes.”
• Gartner predicts that its use will grow from 10% of
organizations today using some form of prescriptive analytics to
35% by 2020, making it the fastest growing category of software.
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9. Analytics & Optimisation Process
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10. Analytics & Optimisation Process

11. Understanding & Presenting Information using
Dashboards, Reports & Visual Tools
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12. Sample Strategic Dashboard – Risk Matrix
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13. Dashboard – Scenario Comparison
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14. 14
Water Interventions Dashboard
• Distribution Mains

15. ASKING THE RIGHT QUESTIONS
Electricity North West – Phil McFarlane
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16. 16
Introducing Electricity North West
4.9 million
23 Terawatt
hours
2.4 million
£12 billion of network assets
56 000 km of network l 96 bulk supply substations
363 primary substations l 33 000 transformers

17. Risk Matrices
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18. Electricity North West
• Began a journey 12 months ago to understand &
implement prescriptive analytics
• Started with a pilot looking at cross asset optimisation
across 4 asset classes
• Objectives of the pilot were to understand:
– Expected benefits of prescriptive analytics for a DNO
– Different optimisation techniques
– Benefits of refurbishment options versus replacement across
different asset types
– Savings that can be found compared to the current approach
– Run different investment planning ‘what if’ scenarios
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19. Asking the right questions
Sample questions asked during the pilot:
1. Maintain current risk at least total cost. (Baseline scenario)
2. What is the optimal plan with a 5% reduction in expenditure?
3. What is the optimal plan with a risk reduction of 10%:
1. By asset category?
2. Across multiple asset classes?
4. What is the best risk score with an annual budget cap?
Constraints considered – budget, resource and skill availability
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20. Dashboards
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21. Group Workshop
• What would the most useful ‘what if’ questions be for
your business?
• Do you have the data and processes in place to look at
implementing analytics?
• Why?
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22. Making Asset Management Active – in Summary
• Benefits - why use Analytics?
• Overview of Analytics in Asset Management
• What is required?
• Dashboards, Reports & Visuals
• View from the industry
– Electricity North West’s journey
– ‘What if’ scenario modelling’
Questions?
April Hutchen - a.hutchen@seamsltd.com
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