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Making Asset Management Active
with Analytics
1
April Hutchen a.hutchen@seamsltd.com
Phil McFarlane – Electricity North West
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
2
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
3
IAM Asset Management Anatomy
4
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
5
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
6
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
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.
8
Analytics & Optimisation Process
9
Analytics & Optimisation Process
Understanding & Presenting Information using
Dashboards, Reports & Visual Tools
11
Sample Strategic Dashboard – Risk Matrix
12
Dashboard – Scenario Comparison
13
14
Water Interventions Dashboard
• Distribution Mains
ASKING THE RIGHT QUESTIONS
Electricity North West – Phil McFarlane
15
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
Risk Matrices
17
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
18
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
19
Dashboards
20
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?
21
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
22

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Iam active asset management 2016

  • 1. Making Asset Management Active with Analytics 1 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 2
  • 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 3
  • 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 5
  • 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 6
  • 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. 8
  • 11. Understanding & Presenting Information using Dashboards, Reports & Visual Tools 11
  • 12. Sample Strategic Dashboard – Risk Matrix 12
  • 13. Dashboard – Scenario Comparison 13
  • 15. ASKING THE RIGHT QUESTIONS Electricity North West – Phil McFarlane 15
  • 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
  • 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 18
  • 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 19
  • 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? 21
  • 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 22

Editor's Notes

  1. Pilot is mainly Capital Investment Decision Making. But (as you will see from Key Findings) it touched on Data Management, Supply Chain Management, etc.
  2. If no client speaker, then a couple of Case Studies???
  3. Regulated electricity distributor Distribute > 23TWh of electricity annually To 5 million people at 2.4 million premises At 99.99% reliability Using an £11G network; 56 000 km of network 96 bulk supply substations 363 primary substations 33 000 transformers