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Business Analytics Blog

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Learn to Love Your Assets by Hugh Harford, Gráinne McDonagh and Nigel Lewis

Improving existing operations to reduce risk, increase margins and yield competitive advantage is more important in the current market than ever – and we believe that analytics can provide the answer. This week Capgemini’s Business Analytics team are releasing a daily blog on some of the key use cases of Operational Analytics – today’s topic is Asset Management.

A news story from Reuters in March 2015 detailed the number of incidents across the US and Canadian rail network of Canadian National Rail (CN Rail). The article showed that there has been a spike in accidents since 2012, including some very serious incidents. Also during March there was a flood of stories about mains water pipeline bursts that were causing disruption in many parts of England. There was a flood surrounding a hospital in Redcar, Teeside; 1400 homes were without water and the A494 closed near Llanferres, North Wales; Melton Mowbray in Leicestershire suffered two mains bursts within 48 hours, closing schools, roads and cutting off most of the town.



Although these incidents are not necessarily fully representative, the question arises: why are they happening with more frequency?

What we are able to learn from these will inform our view of how heavy industry and utilities will be managed in the future?

Rail networks, water companies, oil platforms from the North Sea and across the world, electricity generators and distributors from Costa Rica to the US and Europe, port terminals across Europe and globally all face a similar set of challenges. And they are using asset management to deal with these challenges.

Finding common ground

I’d bet those working in these respective industries would say their challenges are very different from each other. In many ways they are, but there is a clear commonality. Firstly, the asset base used by all these organisations is expensive to look after, and it is old – often life-expired. The lifetime of these assets can be longer than human lifespan, and therefore they were designed and installed in different decades before. Furthermore, it is not unusual that assets are dispersed across a significant geographic region.

The challenge of funding is growing

There is a notable gap in infrastructure investment. You will find many people talking about this, including the UK government in their National Infrastructure Plan, despite a total investment pipeline of £466bn and 2,500 projects since 2010 - see diagram below details. So we have expensive, ageing assets, without the funding to replace them.

To add to this, we expect more. As the population and economy inexorably grow the assets strain to perform as we expect. Add to this the interests of governments and shareholders and you begin to get the picture.

Failures of railway networks, water mains, or electricity supplies are often headline news as they cause a huge range of disruption. Behind these asset failures, there are the inefficiencies of a system that cannot accurately predict failures, as with both CN Rail and UK water networks. If you read the news articles about the CN Rail accident rates, the company doesn’t seem to have a firm grip on why the accident rate has changed, despite the significant spikes in accident rates from in 2005.



To return to my original question – can analytics be used to find out why these accidents happen? CN Rail are now using analytics to look at trends.

For asset-intensive organisations around the globe, there is huge value in better prediction of where best to invest limited resources. These days, service is increasingly the focus; service interruption is no longer acceptable. Under this sort of pressure, Mark Carne of Network Rail has the right idea. He feels there “should be better use of data to identify ways of improving the [rail] industry.” In other words: those in asset-intensive organisations need to learn to love their assets. This means listening to them, gathering what useful data they can and seeking to understand the assets via analytics. By loving your assets, listening and understanding, you can make better decisions. This is crucial because understanding how best to invest takes some thinking, as those who have implemented asset management know. These assets can have lifetimes of many decades, how best to spend this year’s budget, or invest in 5 or 15 years is not obvious when considering the whole lifecycle cost. What impact does an investment next year have, or what is the impact of not making the same investment until, say, 2019?

Where and when to invest

Some investments are obvious: asset failures must be dealt with despite the heightened expense. Where there is a significant and disparate asset base it is more difficult to decide where to invest. If you had an aging fleet of buses, say, how would you work out which to maintain, refurbish or replace, and when would be best to do so for each one? For ageing €3m cranes in a port terminal, how would you show they should be kept on rather than replaced? For a water network company there are so many possibilities, what would the optimised programme look like?

Our sensitivity analysis work for UK water utilities is useful too, to identify how much flexibility there in the plan. These challenges demand a responsive organisation, and the right insights from the right information.

Standardising approach

Over the last 15 years the new discipline of asset management has developed, and there is a clear methodology to deal with these challenges. The Institute of Asset Management (IAM) now shows rapid grow in corporate and individual membership. For an introduction download the Anatomy of Asset Management – you can register with the IAM for free. I have been Editor of the IAM’s membership magazine Assets since 2012, and since then there has been huge uptake of this strategic approach, globally and from all types of asset-intensive industry. Now there is an international standard of Asset Management: ISO 55000 2014.


The idea that asset management doesn’t apply is a perennial favourite. But so often this notion is wrong. If you have a reliance on physical assets, the principles of asset management apply. Asset management can help solve the combination of difficult and widespread issues mentioned here. And these challenges are not going away.

I will briefly highlight some of the key tenets to applying Asset Management successfully. The performance of the assets is crucial. How is system performance understood, and how does current performance reflect the capability of the asset portfolio? To understand this, an integrated dataset about the assets and their output is needed. Getting to grips with the data will likely require visualisation techniques. The award-winning Network Rail LADS project is a good example of great data visualisation, where many datasets, presented together, facilitate decision-makers to make more informed choices.



Establishing the criticality of the assets within your portfolio is another important step. How can investments be prioritised without clarity about the extent that each asset is important to your organisation and customers? Criticality should cover multiple facets, and criticality is a key component of the risk-based approach that is central to asset management. Using a single unit or currency is vital to allow comparison across the diversity of your assets. Here is one of the central tenets of asset management thinking. Love your assets, and learn how to forecast how they behave over their whole lifecycle, the costs, usage and performance at each stage. This approach requires a multi-disciplinary input to gather all the information; you will need input from across your organisation.

Modelling and forecasting across the whole asset base is important so you can understand the systematic effects, as with our asset investment planning work for electricity generator and transmitters. Each model forecasts the effect investment will make to asset condition. Modelling the system effects using all the individual models allows a planning regime to move towards optimised investment.

What are the benefits

Let’s get to outcomes, what is all this effort for? One important outcome from asset management is financial benefit. Others include performance improvements, risk reductions and safety improvements. These can be available at the same time, as in our electricity generator and transmitter, water utilities and rail network asset management work. At the core of these projects is a risk-based optimisation analytics approach that is the beginning of the continuous improvement cycle, where insights drive updates to strategies and policies. If inputs from across the business are used, and decisions are transparent, this can incubate a real change to the way of working as people see their inputs driving change.

Some caution is needed; this is a substantial change programme. Senior leadership needs to think in the long term. The new way of working will not drop into place overnight, and leadership needs to back the new strategies and nascent processes until they are fully in place. Asset management competence (see below) must drive capability into the business, so staff know how they each contribute to the overall effort, and this new model must be enabled with the right technology. Breaking down the traditional organisational silos unlocks the inefficiencies, but organisational power structures often get in the way.



Quick wins can and must be delivered early to encourage the programme. Getting away from a heavily reactive mode is difficult, and I expect this is partially the cause of the UK water network’s and Canadian National Rail’s slow response to better management of their asset portfolio.

Learning to love your assets

This all begins to show that a new operating model is needed, allowing a genuine change to be made. Renaming all the divisions to include asset management in the title, as is seen regularly, does not begin to get at the genuine change to business as usual. That said, with the right approach, your assets will feel loved, and better understanding allows prediction of how they will behave. Wouldn’t that be a relief!

If you would like to know more about Asset Management, our Operational Analytics offer or where Capgemini has delivered this capability before – please feel free to contact one of the authors.

About the author

Nigel Lewis
Nigel Lewis
Nigel leads the Capgemini Consulting’s 35 strong Business Analytics team, which delivers analytical, operational and strategic modelling solutions to clients. He has 18 years consultancy experience as well as 8 years experience in the UK gas industry. Nigel has successfully managed complex projects in both the public and private sector, including capacity modelling, simulating supply chain operations, strategic business modelling to support future policy decisions, and implementing complex demand forecasting systems. Nigel is currently focussing on the development of Capgemini’s customer analytics and analytics advisory services.

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