Effective Infrastructure Asset Management

A holistic approach to transformation

Russell Pell, Radek Svoboda, Rick Eagar, Peter Ondko, Frank Kirschnick

Ensuring that physical assets are available to deliver required It would be easy to as-
services in a cost-effective and timely fashion is a big issue for sume that after decades
of development and
industry. Assets managed across the European Union are worth
refinement, infrastruc-
some €48 trillion, and investments of €1.9 trillion and maintenance ture asset management
expenses of €1.0 trillion are required annually to keep them going. practices and approach-
Given these numbers, one might be forgiven for thinking that after es would now all be
fairly straightforward
decades of development and refinement, asset management prac-
and well-established.
 72/73

Picture by OJO Images / iStockphoto

tices and approaches would now all be fairly straightforward and However, many compa-
well-established. However, this is not the case at all. For example, nies are realizing that in
the face of mushrooming
in a recent benchmarking study we found that some of the world’s
asset replacement costs
leading infrastructure companies are still struggling to implement and increasing demands
even basic predictive maintenance techniques effectively. Many are for reliability and capacity,
facing mushrooming costs to maintain and replace aging assets, a radically different
approach is needed. In
whilst demands for reliability and capacity are constantly increas-
this article the authors
ing. All this means that many infrastructure companies are starting explore the challenges
to realize that they can no longer manage assets in the same way being faced by infra-
– a radically different approach is needed. In this article we explore structure companies in
transforming their asset
the challenges being faced by infrastructure companies in trans-
management efforts
forming their asset management processes, and set out some and set out some best
best practices to help transform operations. practices to successfully
make the change.
The challenges facing infrastructure companies

The principles and methodologies for effective asset management

are well established and enshrined in commonly accepted stan-
dards such as PAS55 and ISO 55000. However, not all industries
have reached the same level of maturity in their approach to man-
aging their assets. Whilst sectors such as aviation, chemicals, man-
ufacturing and nuclear power are quite sophisticated in their asset
management approaches and technologies, other infrastructure
sectors such as rail, road, oil & gas and water are often less so.

There are some good reasons for this. Asset management is

generally more difficult when assets are distributed over large dis-
tances with differing origins, ages and operating conditions. Also,
many infrastructure systems are publicly owned and regulated, and
historically have not been subject to the same commercial pres-
sures for optimization as, say, a manufacturing plant.

In recent years there has been growing pressure on infrastructure

organizations to significantly improve their asset management
performance. This is due to a range of factors, such as the need
for increasing capacity due to economic growth and urbanization,
the need to replace high-cost, aging assets in developed econo-
mies, shrinking public sector budgets, and ever-higher demands
from customers for infrastructure service quality and reliability. In
addition, rapid technological innovation in areas such as big data
analytics, robotics, automation and sensors, is opening up new
possibilities that transform the way assets are managed.

However, today we see that many infrastructure organizations –

even the best-performing ones – are struggling to achieve the scale
of transformation needed to respond to these growing pressures.
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Where infrastructure companies are struggling

We see a number of common problems that infrastructure compa-

nies experience, for example:

• Many companies do not yet have a fully-integrated approach

to demand forecasting, demand management and asset
planning. This makes it difficult to establish asset manage-
ment strategies that will optimize across new asset builds and
extensions, existing asset replacements or enhancements, and
maintenance or rehabilitation regimes.

• Second, most companies have some type of asset information

system for planning and work-order management, but often
this is not yet integrated into a single architecture, and actual
real-time condition data may not be included in the system. The
resulting lack of accessible information at the right time, in the
right place, is a major barrier to efficiency improvement.

• Third, although whole-life costing is usually in place (i.e. eval-

uating total costs over the lifetime of the asset), in practice it is
often poorly applied because of grey areas around key assump-
tions and fragmented responsibilities internally. Connected with
this is an approach to value management, which, whilst recog-
nizing “value engineering” (i.e. optimizing designs on the basis
of analysis of the value they provide), seldom leads to signifi-
cant design changes with major cost or performance benefits
due to a “stick with what we know” mentality.

• Fourth, implementation of optimization techniques such as con-

dition-based monitoring and predictive maintenance often
gets stuck at the pilot stage. This is because of the time and
level of effort needed to analyze and interpret huge volumes of
condition data, its uncertain economic benefits, and the com-
plexity and cost of full rollout.
• Finally, many infrastructure companies have a strong focus on
high operational reliability, which leads to a risk-averse culture
with respect to new and emerging technologies. Many compa-
nies have few, if any, dedicated resources for new technology
development and introduction, which means they tend to
stick with what they know.

So what should infrastructure organizations do to overcome these

problems?

Using a holistic approach to achieve transformation

Our recent asset management benchmarking study showed that

the most common underlying weakness in companies was a
failure to address asset management in a sufficiently holistic
way. Companies were often working on the pieces of the puzzle,
especially in terms of predictive maintenance technology trials, but
had failed to put them together in a way that would achieve a real
impact.

The companies that have been most successful in transformation

are those that have taken a holistic approach that tackles these
underlying weaknesses head on. This approach comprises five
building blocks: Requirements, Systems, Principles, Methods, and
Organization & Culture, as shown in Table 2.

1. Requirements: Integrated strategic asset management

planning

The ability to form a consistent, properly evidenced, and integrat-

ed picture of likely demand on assets, especially in the medium
to long term, is essential to enable optimized asset management
plans to be developed. In many organizations this is difficult
because of absent or separate “siloed” processes for short-term
demand assessment, long-term demand forecasting, asset en-
hancement planning, and current asset degradation modelling and
maintenance planning. Key steps to address this issue include:
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1 Requirements
Needs, strategy and planning

Build/
replace
4 Methods
3 Principles
Table 2 Holistic
Technology &
Value innovation approach to asset
Dispose Asset Operate
engineering
lifecycle management management
Whole life Optimized transformation
costing maintenance
Source: Arthur D. Little
approaches
Maintain

2 Systems
Asset information management

5 Organization & culture

• Setting up a consolidated demand register to capture the

range of past, current and future needs on the assets, including,
for example, customer needs, operational needs and strategic/
corporate needs.

• Re-engineering the strategic asset planning process to analyze

consolidated demand needs as well as current asset conditions
and degradation forecasts, and to develop integrated short- and
long-term asset replacement and management strategies.

• Leveraging new technologies and approaches to improve

demand intelligence, such as new big data analytical methods,
new ways of monitoring, modelling, and predicting customer
behaviors, and new trend intelligence and forecasting tools.

As one example of the value of demand management, the Fuel

Efficient Traffic Signal Management program implemented through-
out the State of California optimized traffic signal timing by enhanc-
ing data collection, system monitoring and automated control. This
led to improvements in overall system utilization and a cost-benefit
ratio of 1:17. This was achieved by reductions of 14 percent in
delays, 8 percent in fuel consumption, 13 percent in stops, and 8
percent in travel time, all without requiring significant investment in
existing infrastructure.

2. Systems: Adequate asset information management

Having accessible and suitably-interpreted asset information is a

critical enabler for the entire asset management effort, in order to
support the planning cycles appropriate to that asset type. To man-
age disruption, this could mean very short-term, or even real-time,
data. Despite its importance, many companies do not recognize
the strategic value of asset information. Information system issues
are often complex and IT-based solutions may be costly, meaning
that companies are reluctant to make the necessary investment.
There is usually a wide variety of implementation paths available,
but the most successful approaches tend to focus on three things:

• Getting the fundamentals in place. Making sure that the basic

information for all key assets is actually available to support key
asset management processes and performance analysis. Ideally
there should be a commonly agreed suite of technical, opera-
tional and condition information, in a fit-for-purpose data struc-
ture to enable rapid development of builds to the information.

• Leveraging the information. Once key data is available and

accessible in a coherent structure, it needs to be used to create
efficiencies. This means new processes, maintenance strate-
gies, ways of working, and competencies. Creation of reliable
asset degradation models is one of the key means by which
good-quality asset-level data on operational history and condi-
tions can be used for maintenance optimization.

• Information integration. With key data available and support-

ing new ways of working, there is an opportunity to further
integrate asset information. This usually involves finding ways to
better integrate with enterprise solutions and other applications
within a connected portfolio.
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As with any information system, it is often valuable to stagger

the development, so in effect the deployment of change is
happening across different asset groups at different stages at the
same time, and quick wins can be delivered through well-facilitat-
ed pilots. The focus should be on how new ways of working by
engineers and technicians will deliver the benefits of improved
asset information availability.

Advances in digital technology and solution development

methods mean that the development of asset information man-
agement is no longer a binary choice between simple solutions
based on limited technology investment, or highly complex
approaches requiring substantial investment. In fact, we see
companies adopting three levels of approach here:

– MVP (Minimum Viable Product) – low-tech options, with multi-

ple manual workarounds
– Pragmatic approach – digital “fit-for-purpose” often incorporat-
ing agile development
– Enterprise-level solutions based on fully integrated systems
requiring high levels of investment

Choosing the right approach can greatly reduce investment costs

without compromising on functionality. With the increasing use
of agile development techniques, organizations are now seeing
that technology can be developed in certain areas within rapid
timescales, not necessarily related to the long-term asset life-
cycles which tend to characterize the traditional mindset of the
asset manager.

3. Principles: Consistent whole-life costing and

value management

The concept of optimizing whole-life costs (TOTEX) as opposed

to managing CAPEX and OPEX separately has been around for
many years. High initial acquisition costs may provide assets
with higher reliability, better performance and lower maintenance
costs, whilst low acquisition costs can generate higher OPEX
costs in the future. Many companies still only pay lip-service to
the concept and do not apply it effectively and consistently. Com-
mon reasons for this include, split budget responsibilities between
OPEX and CAPEX; short-term financial constraints which favor
CAPEX reduction over TOTEX; and different assumptions about
asset lifetimes, cost allocations, depreciation curves, and the
economic value of benefits across different parts of the company,
which undermine the credibility of the approach. Often organiza-
tions struggle to effectively prioritize their asset-related budgets or
portfolios, because of difficulties in comparing different projects
in the portfolio on a common basis. This is sometimes due to
attempting to apply highly detailed project parameters for compar-
ison, when in reality a more holistic approach would better achieve
what is needed. Key success factors for companies in applying an
effective whole-life costing approach include:

• Embedding a whole-life view into all aspects of the asset

lifecycle: Adoption of a genuine, shared, long-term view on
asset lifetime cost and performance, supported by top manage-
ment, is an essential starting point. The whole-life approach is
applicable in all stages of the asset life cycle, including Design,
Operate, Maintain and Dispose. It should be applied to suit the
needs of the organization as a whole, which may be different to
the needs of planning or managing a specific project.

• Agreeing common definitions and assumptions: Having clar-

ity across different functions, departments, business units and
regions around key definitions and assumptions is essential to
underpin the credibility of the TOTEX approach. This can some-
times be quite difficult, given the varying lifetimes of different
asset classes, cost allocation complexities, and the challenge of
monetizing certain performance benefits.

Value management is also a key part of the picture in terms of op-

timization and achieving cost efficiencies. Like whole-life costing,
value engineering has been around for many years but is still poorly
implemented by many companies. Typical problems include risk
aversion when considering alternative design technologies, lack of
in-house capabilities to assess options and impact, and reliance on
design contractors to conduct “value engineering” studies too late
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in the cycle, when the basic design concept has already been fro-
zen. Key success factors for effective value management include:

• A focus on innovation and “optioneering”: avoid the auto-

matic assumption of like-for-like asset replacement, and change
the policy of using only well-established technologies or de-
signs. Manage risks rather than avoid them. This is especially
important for assets with long lifecycles, when many new op-
tions may be available, and crucially, knowledge of prior design
assumptions may have been lost in the course of time.

• Multi-disciplinary, function-based thinking: Good-value

management starts by considering what the function (or set of
functions) is that the asset needs to deliver. Asset owners and
managers should work with multi-disciplinary teams including
project managers, operators, designers, estimators, contractors
and commercial staff, based on a structured process. Too often,
operators or asset owners rely on their contractors, instead of
taking the lead to ensure that they are getting exactly what they
need in a cost-effective way.

• Timing: Strategic value-based thinking for assets should start

very early on, certainly around the time concept design starts.
Having a layered approach, whereby high-level direction can
be set early, and then focusing on specific aspects or areas in
more detail later on, can help to ensure that the complexities of
specific projects are considered appropriately.

These principles deliver major benefits. For example, in Germany,

transmission grid operators have started to prioritize more system-
atically their capital investments for grid/sub-station operations and
onshore/offshore grid connection projects using effective whole-life
approaches. In Denmark, analysis of policy options has reduced the
costs of road maintenance by 10 to 20 percent, whilst reducing the
maintenance backlog by 70 percent.
4. Methods: Predictive maintenance and technology
& innovation management

Whilst of course, there are many methods and approaches that

need to be applied for effective asset management, there are
two methods which have a big potential impact by addressing the
typical weaknesses mentioned above as part of a holistic approach:
predictive maintenance (PdM) and technology & innovation man-
agement (TIM).

PdM is a powerful tool for optimization because it enables:

• Reduced maintenance costs by optimizing maintenance sched-

ules, based on the prognosis of future asset conditions.

• Improved system reliability and minimized disruptions through

better failure modeling and prediction.

• Reduced downtime through better maintenance planning and

execution, based on foresight rather than history.

• Extended asset life through better intelligence on asset condi-

tions and management of asset degradation.

As mentioned above, there has been tremendous innovation in

technologies relevant for PdM in recent years (see Box 1), with the
potential for game-changing impact.
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Box 1: Technological innovation in maintenance: From predictive to “prognostic”

Technological innovation in maintenance covers many fields, including condition-moni-

toring technologies, remote control and automatic tools, workforce management, and
analytics and big data solutions.

New condition-monitoring technologies enable precise targeting of maintenance and

repair activities to assets with signs of deterioration, for example:

• Surveying cars equipped with high-resolution cameras, laser systems and other sen-
sors are increasingly used to monitor remote asset condition and quality. Techniques
using drones and robots have huge potential.

• New types of condition data have been discovered. In the case of rotating equip-
ment, examples includes stress waves, filter debris, and stator vane acoustics (indi-
cating blade cracks) for gas combustion turbines.

• New types of sensors have been developed for new and established data types,
such as wireless, self-energized vibration sensors for upstream oil & gas applica-
tions, online/inline oil particle counters for wind turbines, and wayside laser sensors
for railway applications.

Condition monitoring combined with predictive analytics and big data has given rise
to “prognostic” maintenance, (i.e. building a comprehensive prognosis of future asset
condition, as opposed to simply comparing the current condition with a predicted ref-
erence state). This is now possible on a much larger scale, as highly affordable ways of
transferring, archiving and processing data in large volumes have emerged, with cloud
computing and storage now finding their way into industrial asset management. Predic-
tive and prognostic maintenance is increasingly being adopted in more dispersed asset
bases, such as transmission networks and high-speed railways. Adding high-quality, yet
low-cost, mobile communication devices such as smartphones or tablets enables almost
complete digitalization of workforce management, leading to substantial reductions in
scheduling efforts and improved utilization of field workers in operation and maintenance.

With “Industry 4.0”, the “Industrial Internet” and the “Internet of Things” (IoT), new
analytical solutions – including prognostic solutions – from other industries such as
finance, consumer goods and healthcare are now entering the realm of industrial asset
management. Grounded in big data and decades of analytical refinement in highly com-
petitive markets, best-practice solutions from these sectors may prove inherently more
powerful than the old-fashioned analytical approaches used for PdM. Robust stochastic
process models, in particular, integrate and utilize the available condition data volumes
without requiring asset-failure rates or lifecycle statistics, formerly mandated by legacy
techniques such as Weibull fitting and Cox regression.
Organizations need to ensure that asset failure/degradation mod-
els are developed and validated, possibly in consortiums or joint
ventures with industry research institutes. This will allow them to
gauge where best to apply PdM as part of a balanced maintenance
approach that includes preventive and reactive methods. Once
suitable asset information systems are in place (see 2 above), it is
possible to “mainstream” PdM methods into maintenance pro-
cesses. In combination with innovative mobile workforce solutions,
remote-monitoring techniques and automatic/robotic inspection
and repair technologies, significant benefits can be achieved. For
example, Xcel Energy, a major US electricity and natural gas com-
pany, implemented a digitalized, integrated solution for workforce
planning and asset management, which included mobile function-
ality. The solution provided a clear, accurate, and timely data matrix
that allowed overall optimization of major business processes,
yielding an 87 percent reduction in scheduling effort, 17 percent
reduction in maintenance and inspection effort, and 47 percent
improvement in construction crew productivity.

In order to be able to successfully apply the new technologies that

are being developed around asset management, robust tech-
nology and innovation management approaches are needed,
combined with suitable resourcing. However, many companies do
not yet have these approaches in place in the arena of asset man-
agement. Key elements include:

• Systematic monitoring and evaluation of emerging technolo-

gies, always considering their compatibility with existing assets.

• Adopting partnering approaches with developers, large sup-

pliers and other innovation players to influence the course of
technological innovation, co-develop solutions to meet internal
needs, and build new internal capabilities and competences.

• Proper piloting of field technologies with practical lessons

embedded during full roll-out.

Without these approaches, asset managers remain in reactive

mode with regard to new technologies, and true integration into
new and existing assets is difficult.
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5. Organization and culture: Dealing with the root causes

The root causes of failure to achieve expected benefits from new

asset management technologies, processes and approaches
can often be traced back to fundamental issues around “people”
and how the organization behaves. This relates especially to how
responsibilities for different aspects of asset performance are de-
fined, and where costs and benefits are allocated. Getting this right
is perhaps the most essential part of any holistic approach:

• Organizing around asset management: Having the right

organization structure and governance to enable teams and
individuals to deliver world-class asset management is key.
Asset management cuts across traditional company functions
such as Engineering, Projects, Operations, Maintenance, Safety
and even Customer Service. Accountability for asset perfor-
mance is often split between these functions. Allocating clear
accountability for asset lifetime performance within the existing
structure is one way forward. A multi-functional governance
approach, such as a cross-functional steering group or commit-
tee, can help to make balanced asset management decisions.
In some situations, placing asset management in a more central
position within the organization is the optimal answer.

• Philosophy and culture: Whole-life and whole-system think-

ing is often difficult to promulgate in the face of short-term
corporate priorities, and pressures on departments, units and
individuals to deliver against specific targets. Companies need
to actively promote the right values and behaviors to support a
holistic approach to asset management. This means leading by
example, and reinforcing this with carefully selected incentives
and key performance indicators that promote long-term goals
and whole-system benefits. Early delivery of beneficial change
is one important aspect. The use of rapid action teams, deliver-
ing substantive change in a specific area or asset class, is one
proven technique for the advancements of new process man-
agement.
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Insights for the executive

Infrastructure asset management companies need to do things
differently to respond to the demands of today and tomorrow. The
key to successfully making the change is to take a holistic approach
that tackles fundamental barriers around Requirements, Systems,
Principles, Methods, and Organization & Culture.

With these building blocks all in place, infrastructure organizations

should be able to achieve the transformation they need in a sus-
tainable way. Those that continue to approach asset management
in a “siloed” manner, expecting new technologies alone to make
the difference, are unlikely to succeed.
Picture by Daniel Ingold / Cultura / gettyimages

Russell Pell
is a Partner in the London office of Arthur D. Little and a member of the Oper-
ations Management Practice.

Radek Svoboda
is a Manager in the Prague office of Arthur D. Little and a member of the
Energy & Utilities Practice.

Rick Eagar
is a Partner in the London office of Arthur D. Little and global head of the
Technology & Innovation Management Practice.

Peter Ondko
is a Manager in the Prague office of Arthur D. Little and a member of the
Operations Management Practice.

Frank Kirschnick
is Chief Technology Officer of Cassantec, a provider of prognostic solutions
for industrial asset management.