PERFORMANCE EVALUATION FRAMEWORK FOR IT/IS

BASED ASSET MANAGEMENT

Abrar Haider

School of Computer and Information science, University of South Australia,

Mawson Lakes, Adelaide, SA 5095, Australia

Andy Koronios

School of Computer and Information science, University of South Australia,

Mawson Lakes, Adelaide, SA 5095, Australia

Keywords: Asset Management, Asset Maintenance, Asset Lifecycle Management.

Abstract: Engineering assets managing businesses use a variety of information and communication technologies for

process efficiency, control, and management. Nevertheless, key to all these is the effective measurement of

the IT/IS utilisation for existing process such that the underperforming areas are highlighted, and corrective

actions are taken to achieve optimal use of IS/IT. There are a variety of performance measurement

mechanisms available that stimulate improvement efforts, in so doing helping businesses to translate

perceived business strategy into action. However, these approaches are mostly aimed at high level

evaluation of an organisation’s performance; whereas the stochastic nature and ever expanding scope of

asset management processes demands asset managers to have a comprehensive view of asset lifecycle and

the interacting business areas. This paper proposes an evaluation framework for IT/IS based asset

management in an engineering enterprise. The paper firstly seeks to present a critique of the asset

management paradigm. It then discusses available performance measurement mechanisms and develops a

case for the constituents of an effective asset management measurement framework that provides detailed

indicators for controls actions required to achieve optimal process efficiency through the use of IT/IS. The

paper, then, presents an integrated asset performance measurement framework that not only is derived from

business strategy, but informs strategy formulation through a closed loop learning encompassing entire asset

management lifecycle.

1 INTRODUCTION

Business and engineering disciplines are facing

continuous change, facilitated by factors such as

advancements in technology, deregulation, and

environmental concerns. Amidst these adjustments in

the operating environment, it has become imperative

for business to have some sort performance

measurement system in place to measure the growth

and progress of the business, so as to rationalize

investments and to measure if their existing

technological, process, and procedural initiatives

conform to business strategy. This has particular

relevance for the high risk and capital intensive

businesses, such as engineering enterprises (see for

example Liyanage and Kumar 2000). More than ever

these businesses are concerned about the usefulness

of the business infrastructure that they put in place to

produce products and services, and at its heart lies the

measurement of the effectiveness of their production

or manufacturing ‘assets’. This concern is not just

limited to the businesses operating and owning these

assets, but is also shared by the regulatory authorities

(such as, environmental protection agencies). Asset is

the physical component of a manufacturing,

production or service facility, which has value,

enables services to be provided, and has an economic

life of greater than twelve months (IIM 2003), such

as manufacturing plants, railway engines and

carriages, aircrafts, water pumps, and oil and gas rigs.

Accordingly, management of these assets represents a

set of disciplines, methods, procedures and tools to

optimise the whole life business impact of costs,

performance and risk exposures associated with the

availability, efficiency, quality, longevity and

regulatory/safety/environmental compliance of a

355

Haider A. and Koronios A. (2006).

PERFORMANCE EVALUATION FRAMEWORK FOR IT/IS BASED ASSET MANAGEMENT.

In Proceedings of the Eighth International Conference on Enterprise Information Systems - ISAS, pages 355-365

DOI: 10.5220/0002449503550365

 SciTePress

company’s assets (Woodhouse 2001). However,

trends like convergence of technologies is making

assets easier to operate on one hand, and on the other

are making their management versatile due to the

multifaceted maintenance demands of various

technologies used in the assets. Nonetheless,

traditionally manufacturing/production assets have

not been given requisite attention on the strategic

agenda of manufacturing or production businesses;

with more emphasis been given to factors like what to

produce and how much to produce. Consequently, the

available performance measurement systems either

tend to overlook assets altogether, or when they do

allow provisions for assets performance

measurement, it provides a unilateral view mainly

concerned with their throughput rather than providing

a multilateral view that covers their output as well as

the impact of their operation on other business areas

and their design, maintenance, and retirement and

reinvestment demands. Furthermore, classical

measurement systems generally have a financial

measurement orientation (Kaplan and Norton 1996;

Sveiby 1997), and do not give enough consideration

to other important factors like technological maturity,

skill base, and process efficiency.

This research paper investigates the role of

information technologies, particularly information

systems in enabling asset management processes. It

takes an asset lifecycle perspective and proposes a

performance measurement framework for asset

management, which assists engineering enterprises

to evaluate the effectiveness of their assets in

operation as well as the impact of their operation on

related business areas and overall business direction.

The paper suggests a seven perspectives framework,

which has IT/IS at its core, such that it ties asset

management processes together to create a chain of

value added perspectives that translate into business

competitiveness.

2 IT AND ASSET MANAGEMENT

The past decade has seen significant activity in

business enabling technologies, which among others

also spans manufacturing and production systems,

production philosophies, and processes. Impact of

these technologies has intensified competition,

mainly because technology provides businesses with

the opportunities of competing on even grounds,

regardless of their size. However, at the same time

technology has also facilitated a shift towards

continuous renewal of products and services at

regular intervals, which consequently is forcing

businesses to innovate and update their offerings with

added value and features regularly. This shortening of

product lifecycles and continuous updating of

products demands enhanced asset operation capacity,

which means assets also have to be upgraded

continuously. Nevertheless, if engineering enterprises

are to take optimum advantage of manufacturing

technologies, their implementation should also

consider the resources, structures and processes that

may be impacted by technology adoption. These four

areas are operational processes, operational

structures, information systems, and human

resources. Information systems, in particular, have

the most significant bearing factor on operational

performance. It is mainly due to the fact that

engineering enterprises mature technologically along

the continuum of standalone technologies to

integrated systems, and in so doing aid the maturity

of processes, skills, and business intelligence.

Information, however, is the fuel of this maturity

process and its magnitude and quality demand also

increases along the same scale of maturity.

Information technologies, which in themselves are an

important constituent of manufacturing technologies,

and information systems, hold the key to continuous

improvement and competitiveness of manufacturing

businesses (Lawrence 1999).

Koc and Lee (2003) summarise the changes in

manufacturing paradigm over the last two decades

and suggest that it is fast moving towards a wireless

environment, or an ‘e-intelligent’ environment

(Figure 1). The authors argue that the manufacturing

paradigm is fast moving towards an environment of

continuous and seamless flow of information, aimed

at real time access to all the stakeholders of a

business process to increase the overall business

efficiency, responsiveness, and agility. This,

however, means a shift that is not just outwardly

innovative, as in terms of product innovation, but is

also inwardly creative and aimed at process re-

engineering and innovation in asset design,

operation and support. Lee (2003) terms this shift as

the “5Ps,” namely predictability, producibility,

productivity, pollution prevention, and performance.

Focus of these 5Ps is on the effectiveness of assets

on the manufacturing floor in terms of continuous

availability, efficiency, and output, as well as on the

expectations of stakeholders in terms of compliance

with regulatory and environmental legislations. In

manufacturing and production environments that are

riddled with continuous change, stability in

manufacturing and quality processes has long been

advocated (see for example, Warnecke and Hueser

1994), as disruptions and disturbances in production

ICEIS 2006 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION

356

1980 1990 2000

2010

Product Focus 3Cs (Chips, Computers,

Communications) &

Intelligent Mechatronics

Products that think

link

Products that Learn,

Grow, Reconfigure,

& Sustain

Manufacturing Focus Factory Automation

(Flexibility)

Business Automation

(Agility)

e-factory & e-

Automation

Innovation Microelectronics &

Computing

Embedded Intelligence

& Smart Netware

E-intelligence

Systems

Figure 1: Evolution in Product Innovation and Manufacturing Source (Koc and Lee 2003).

Table 1: Asset Lifecycle Management Perspective Source (Moubray 2003).

Functions

Description

Functional specifications

Decide what each asset must do to make the manufacturing processes value added

Design specifications

Decide the configuration of the asset in order to meet functional specifications

Acquisition & Deployment

Acquire and deploy the assets

Maintenance

Sustain and where necessary replenish the assets in such a way that they continue to

make the required contribution to the value-adding process

Scorekeeping

Identify key performance indicators that show how well the assets are making their

required contribution to the value adding process

Disposal

Dispose off assets when they do not fulfil the required functions or are not needed

Compliance

Monitor and ensure compliance with regulations governing the use of the assets

or manufacturing have a devastating effect on

revenues as well as customer relationship (Almgren

1999). Engineering enterprises, therefore, need to

take stock of the effectiveness of their assets and

manufacturing process, such that it highlights the

underperforming areas and provides them with a

roadmap for implementation of information systems

in ways that complement business strategy. This

scorekeeping, however, requires a comprehensive

approach that takes a holistic view of the way asset

are operated; their lifecycle demands are addressed

and resources are allocated to keep them in running

condition; their lifecycle decisions are made; and

information is collected, processed, and

communicated within the organisation and with the

business partners.

3 IT AND ASSET MANAGEMENT

Asset management entails design and

commissioning of assets, operation and

simultaneous addressing of maintenance needs

arising from the operations of assets, and consequent

decision support for asset renewal or

decommissioning. Table 1 below further breaks

down these stages and presents a description of the

activities associated with each stage of an asset

lifecycle management.

Increased business automation along with the

continuously changing operating conditions makes

asset management increasingly intricate and

multifarious as it increases their vulnerability by

exposing them to disruptions and interruptions of

various kinds. For example, a typical water pump

station in Australia is located away from major

infrastructure and has considerable length of pipe

line that brings water from the source to the

destination. In this situation, assets are deployed

over an area of various kilometres; however, the

demand for water supply is continuous for twenty

four hours a day, seven days a week. Although, the

station may have some kind of a early warning or

process control and condition monitoring system

installed, such as Supervisory Control and Data

Acquisition (SCADA), maintenance labour at the

water stations and along the pipeline is generally

limited and spares inventory is generally not held at

each station. Therefore, it is imperative to

continuously monitor asset operation (which in this

case constitutes equipment on the water station as

well as the pipeline) in order to sense asset failures

as soon as possible and preferably in their

development stage. However, early fault detection is

not of much use if it is not backed up with the ready

availability of spares and maintenance expertise.

Therefore, the expectations placed on water station

by its stakeholders are not just of continuous

availability of operational assets, but also of the

efficiency and reliability of support processes.

Elimination and control of production irregularities

and disturbances is, therefore, necessary for

production and service provision, agile

manufacturing, and customer satisfaction. However,

PERFORMANCE EVALUATION FRAMEWORK FOR IT/IS BASED ASSET MANAGEMENT

357

as businesses are beginning to recognise the

importance of these turbulences, weaknesses of

traditional approaches to asset equipment are

coming to forefront (Lawrence 1999).

Bamber et al (1999) posit that traditionally asset

management processes, such as maintenance have

been considered as support functions, and are termed

as non-productive and a non core processes that add

little value to the business. This is largely due to lack

of acknowledgement of the direct connection

between maintenance and profitability (Jonsson

1999). Most organisations adopt a traditional

technology-centred approach to design and

implementation of new assets, where technical

aspects command most resources and are considered

first in the planning and design stage. Human and

organisational factors are only considered relatively

late in the process, and sometimes only after the

system is operational (Konradt et al 1998). Al-Najjar

(1996) suggests that most businesses do not have a

significant control of costs incurred by planned or

unplanned stoppages and quality problems. Generally

tactical and operational decision made by managers

have a short term focus, for example, asset

procurement decisions are based on acquisition cost

only and maintenance requirements are totally

ignored, whereas, a significant amount of the annual

operational costs are attributed to maintenance costs.

Consequently engineering enterprises struggle to,

utilise their assets effectively and profile its lifecycle

demands; implement cost effective maintenance

strategies that best suit the business; develop lifecycle

management competencies; plan an effective exit

strategy for assets rendered obsolete through

technology refresh or through end of need; and

provide a credible charge-back system to allocate

maintenance costs to the business lines and thus

ensure that everyone is involved in avoiding

redundancy and wastage of efforts (Haider and

Koronios 2005). This highlights the need for a

comprehensive performance measurement system

that not only provides insights into the effectiveness

of the asset operation, but also quantifies impact of its

operation on other business areas so as to provide a

lifecycle perspective of asset utilisation to asset

managers. Such a performance measurement system

entails that performance measurement should have a

multifaceted but integrated focus. It should include

all the facets of an asset lifecycle as well as critical

factors such as, technology, process efficiency, risk

assessment, competencies, and organisational

learning; and how these factors contribute to overall

business strategy.

4 PERFORMANCE AUDIT

There have been numerous business improvement

methodologies developed and implemented by

businesses of all sorts. These methodologies

represent a blend theory and practice, which each

having its own way of performance measurement

that is largely dependent upon the focus of the

methodology. Some of the leading initiatives in this

regard include organisational learning,

Benchmarking, total quality management, learning

organisation, Six Sigma, European Foundation for

Quality Management Business Excellence Model

(EFQM), business process re-engineering,

knowledge management, and balanced scorecard.

These methodologies constitute the basis of the most

of performance measurement and management

initiatives tailored by businesses to meet their needs.

Consequently, engineering enterprises have adopted

these methodologies in a variety of ways and aimed

at different business areas and processes, such as for

manufacturing planning and control (Kochhar et al.

1996), product development process (O'Donnel and

Duffy, 2002), human resources development (Kelly

and Gennard 2001; Gibb 2002) service or facility

management (Wilson 2000).

Businesses have particularly been interested in

measuring the performance of their information

systems, in order to rationalise investment and to find

triggers for further improvement. An interesting

aspect of these methodologies is the fact that they are

either high level performance measurements or are

aiming at the functional level. Remenyi et al (2000)

summarise the methodologies developed for

assessing the performance of Information systems,

and suggest that their focus has been on strategic

match analysis and evaluation; value chain

assessment (organisation and industry); relative

competitive performance; proportion of management

vision achieved; work-study assessment; economic

assessment - I/O analysis; financial cost benefit

analysis; user attitudes; user utility assessment; value

added analysis; return on management, and multi-

objective, multi-criteria methods.

Although research has paved the way for major

developments in the filed of business improvement,

yet it is interesting to note that asset performance

measurement has been largely limited to physical

inspection of plant and equipment for its health

assessment. However, existing research provides the

essential stepping stones for further research into

performance measurement for asset management.

From the discussion so far seven characterises of a

performance measurement mechanism are formulated

ICEIS 2006 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION

358

and are validated by the research on performance

measurement systems. These characteristics entail

that an appropriate performance measurement system

for asset management should:

a. Focus on business processes as well as the

structures that deliver value (Neely and Adams,

2001);

b. Integrate different aspects of asset management,

such that they constitute a chain for business

competitiveness (Suwignjo et al. 2000; Neely et

al. 1996);

c. balance the needs of various stakeholders, such

as business partners or third party service

providers, customers, employees, regulatory

agencies, and society at large (Kaplan and

Norton 1996; Neely and Adams 2001);

d. information driven such that it provides inputs

to strategy re-calibration rather than being

steered by the business strategy (Bititci 2000;

Bititci et al 2005; Neely and Adams 2001);

e. Conform to business objectives (Kaplan and

Norton 2000; Bititci 2000);

f. Aim at competency development and business

intelligence infrastructure development to create

and sustain value for asset management

processes (Kaplan and Norton 2000; Neely and

Adams 2001); and

g. Provide financial (Kaplan and Norton 2000) as

well as non financial assessments (Neely and

Adams 2001).

5 IS/IT BASED ASSET

MANAGEMENT EVALUATION

From the discussion above, two characteristics stand

out. First, there has to be a strategic fit between the

structure of asset management processes and the

supporting infrastructure, and second, the technology

should provide for the functional integration between

various asset management processes. Table 2, below,

provides the theoretical underpinnings for a seven

perspectives framework that were identified from the

literature review. IT/IS are seen here as the focal

point around which asset management and support

processes are organised. It provides two fundamental

purposes, first it provides the strategic fit between

business structure and infrastructure, and second it

provides for the functional integration. This way,

IT/IS facilitate a closed loop asset lifecycle

management framework (see figure 2).

Table 2: Asset Management Performance Measurement Perspectives.

Perspective Description References

Design and Planning Planning, design, and improvements of assets

and manufacturing processes according to

stakeholders’ expectations and products and

services demand.

Feigenbaum (1991); Flynn et al. (1994);

Yamashina (2000); Zhang et al. (2000); IIM

(2002); Jonsson and Mattsson (2003); Raouf

(2004); Fernando and de Carvalho (2005);

Productivity Ensuring smooth asset performance, including

mitigation of risks posed to assets; their

operating environment

Suzuki (1994); Bever (2000), Woodhouse

(2001), IIM (2002); Raouf (2004); Mathew

(2004); Seth and Tripathi (2005)

Support Financial and non financial resources support

for asset lifecycle support including

maintenance management, spare supply chain

management, and related processes.

Blanchard (1997); Yamashina (2000); Raouf

(2004); IIM (2002); Moubray (2000);

Moubray (2003); Zutshi and Sohal (2005);

Oke (2005)

Stakeholders Ensuring stakeholders collaboration and

integration to achieve higher levels of asset

management through enhanced work design,

process efficiency, and compliance to

regulatory and environmental regulations.

Crosby (1979); Liyanage and Kumar (2000);

Tsang and Chan; (2000); Santos (2000);

Raouf (2004); Zutshi and Sohal (2005); Bititci

et al (2005); Seth and Tripathi (2005)

Organisational

Learning

Profiling asset management and managing

lifecycle knowledge for better understanding

of improvements in asset design, operation,

maintenance, reinvestment, and compliance.

Ramamurthy (1995); Hipkin (2001); IIM

(2002); Marquez et al (2004); Johansen and

Riis (2005)

Competitiveness Strategic directions to strengthen business

performance and competitive position with

effective asset management.

Yamashina (2000); Dangayach and

Deshmukh (2001); Rudberg (2002); IIM

(2002); Schroeder et al (1995); Raouf (2004);

Zutshi and Sohal (2005)

Information

Systems/Information

Technology

Appropriateness of information systems/

information technology to provide value

added support to asset management

Al-Najjar (1996); Blanchard (1997); Bever

(2000); Moubray (2000);Duffuaa et al (2001);

Cassady et al (2001); IIM 2002); Mathew

(2004); Fernando and de Carvalho (2005)

PERFORMANCE EVALUATION FRAMEWORK FOR IT/IS BASED ASSET MANAGEMENT

359

Each perspective and the rationale behind it are

explained below, along with their impact on other

perspectives.

Competitiveness Perspective

In engineering enterprises strategy is often built

around two principles competitive concerns and

decision concerns. Competitive concerns set the gaols

of manufacturing, whereas decision concerns deal

with the way these goals are to be met (Rudberg

2002). This perspective deals with both these

principles. As shown in figure 2, this perceptive

provides strategic underpinnings to asset management

in anti-clock direction thereby setting gaols, and as

the end point of the anti-clock cycle gets feedback

from the asset management processes for better

decision support and asset lifecycle management.

These decisions entail the choice of assets, their

demand management, and business arrangements to

ensure smooth manufacturing or service provision.

Business arrangement illustrates the optimum ways

of doing business, such as the choice of business

partners, outsourcing of asset management functions,

capacity scheduling, and service provision to third

parties (Dangayach and Deshmukh 2001).

Design Perspective

A usual manufacturing cycle starts with specification

of the products and services that the business aspires

to offer its customers in conformance with its

business strategy. This specification illustrates the

types of assets and processes that the business needs

to put in place to produce services and products. It is

also known as the demands specification of assets.

This is of vital importance in a manufacturing cycle

as well as in the asset management lifecycle. It is,

therefore, critical to have an integrated understanding

of factors such as, the characteristics of the

environment that the business operates in; design,

configuration management, and workload of each

asset; maintenance demands of each asset;

availability of asset maintenance support; and the

business process that enable manufacturing as well as

asset management. Any mismatch between what the

market demands, manufacturing process design, and

planning has a detrimental effect on the overall

performance of the business (Schroeder et al 1995).

For example, consider two different types of assets,

one operates on fixed number of hours over a period

of time, and the other operates on as needed basis that

can be many times over the same time. In order to

keep both these assets in running condition, both

assets have some maintenance demands that entail to

have a stock of spares. Usually there are two methods

used in businesses, re-order point and material

requirements planning, where both deal with how

much and when to place an order for a specific item.

However, re-order point requires an even demand

that suits assets that operate in stable conditions,

whereas material requirements planning better suits

complex and demand dependent environments with

erratic demand. Similar differences can be identified

for capacity planning and other manufacturing floor

control methods (see for example, Vollmann et al

1997). Planning choices at this stage drives asset

behaviour, therefore it is important to assess if right

choices have been made to ensure availability.

Furthermore, this assessment also explains variations

in output levels, and possible causes of

manufacturing, production, or service provision

disturbances.

Productivity Perspective

Productivity of an asset is directly related to the

minimising of production or service provision

disturbances. A production or service provision

disturbance is an unplanned or undesirable function

or failure of an asset (Kuivanen, 1996). It can be

classified as asset downtime, speed or operation, and

quality losses. It is important to note that disturbances

do not only occur due to a mechanical or electrical

fault, they can also occur due to some process and

procedural issues. Disturbances occur in one of the

three ways, as suggested by El-Haram (1995):

a. When an asset become inoperable suddenly, and

can no longer perform its required operations;

b. When an asset cannot fulfil some or all of its

operations at the same performance standard as

originally specified; or

c. When an asset gradually deteriorates to an

unsatisfactory level of performance or

condition, and its continued operation is unsafe,

uneconomical or aesthetically unacceptable.

Businesses use different methods to assess the

reliability of their assets operation, just like there are

many ways that can impact asset productivity and

case disturbances. According to one study, more than

one third of the production disturbances were caused

by design errors (Jarvinen et. al. 1996). In complex

manufacturing environments where there is range of

assets employed, production or service disturbances

in one asset can cause detrimental issues for other

assets. For example, due to a mechanical fault the

output of an asset is feeding substandard input to the

next asset, idleness of an asset as it runs out of raw

material, or hazard to other assets due to total asset

failure such as nuclear radiations, and fire. Here,

productivity assessment of an asset entails deviating

ICEIS 2006 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION

360

away the convention practice of just condition

monitoring of an asset and process control through

the use of sensors and process control systems. Its

scope is extended to include operational requirements

compliance, asset operation in the planned

environment, as well as the mechanical behaviour of

the asset. Matson and McFarlane (1999) propose the

concept of production responsiveness with refers to

achieving goals of asset operation in wake of

supplier, internal and customer disturbances.

Therefore, support processes like asset maintenance

need to take a holistic approach by taking care

resource availability for myriad of factors that cause

production or service provision disturbances.

Support Perspective

Operational support for assets means failure detection

as well as support for maintenance execution. This

support is not just limited to availability of resources,

such as spares, equipment, and human resources, but

it also includes factors such as employee training and

skills development. Failure root cause detection is

itself is a daunting task, as explained earlier a failure

condition can have its foundations in different

process, procedural, and mechanical reasons.

Maintenance approaches differ form industry to

industry, depending upon the type of assets that the

business utilises. However, there are three major

approaches to maintenance (Niebel 1996):

a. Failure-driven maintenance;

b. Time-based maintenance;

c. Condition-based maintenance.

Though the crux of maintenance approaches is the

same as the ones described above, however different

industries utilise different techniques to select the

cost effective strategies that best suit their operations

and nature of assets. In this quest oil, defence and

aviation industries have been the forerunners, as they

have introduced strategies such as reliability centred

maintenance (RCM), failure modes and effects

analysis (FMEA), availability, reliability and

maintainability analysis (ARM), level of repair

analysis (LORA), and whole life costing (WLC)

(Blanchard et al. 1995). These approaches fall under

the umbrella of integrated logistics support (ILS) that

deals with the delivering outputs at an affordable cost

throughout a project life cycle (Jones 1995). ILS is an

engineering and management tool, which ensures that

the project economically meets performance

requirements such as reliability, durability, quality,

maintainability, and availability throughout its life

cycle (Green 1991).

Maintenance, however, influences many areas of the

business, such as asset availability in supporting just

in time principles (Nakajima 1988), relationship

between technology and operations (Willmott 1997),

product quality (Moubray 2000), and achieving and

sustaining a safe workplace and environment (Zutshi

and Sohal (2005). This perspective is the most

powerful perspective of asset lifecycle management,

as it not only assesses risks posed due to asset

operation, but also quantifies these risks by providing

indications on spending for asset lifecycle support.

These assessments also provide lifecycle support

decision support, such as tradeoffs between asset

maintenance and renewal, changes to asset design,

level of employee expertise in operating assets.

Strategic Control

Operational Control

Management Control

How well do the

existing ICTs aid in

production design

and planning?

Design and Configuration

Management

How well do the existing ICTs

manage financial and non financial

resources to provide Asset Life

Cycle Support?

Integrated Resource

Management

Capacity Scheduling

and Asset Demand

Management

Disturbance Management

Asset Health Management

Support

Training and Awareness

Operational Risk

Management

Operational Quality

Management

Competencies Development

Organisational

Responsiveness

Asset Workload

Definition

How well do the existing

ICTs ensure optimum asset

operation?

Asset Health

Monitoring and .

Process Control .

Business Value Chain

Integration

How well do the existing ICTs enhance

profitability and competitiveness of

Asset Managing Businesses?

Asset Need and

Requirements

. .

Definition

How well do the existing ICTs

integrate stakeholders in Asset

Management processes?

Collaboration and

Communication

How well do the

existing ICTs

manage Asset

Management

Knowledge and

learnings?

Business Intelligence

Management

Knowledge Sharing

Support

Innovation and Changes in Asset Design;

Lifecycle Processes; products; work design;

and Services

Information System s/

Information Technology

Perspective

Measures

Goals

Design Perspective

Measures

Goals

Competitiveness

Perspective

Measures

Goals

Support

Perspective

Measures

Goals

Productivity

Perspective

Measures

Goals

Stakeholders

Perspective

MeasuresGoals

Learning

Perspective

Measures

Goals

Figure 2: IS/IT based Asset Management Evaluation Framework.

PERFORMANCE EVALUATION FRAMEWORK FOR IT/IS BASED ASSET MANAGEMENT

361

Stakeholders Perspective

Asset performance, among other factors discussed

above, also depends on the skills and expertise of

asset operators and knowledge of asset operation,

asset failure trends, and procedures (Ramamurthy

1995). A common tend among engineering

enterprises is the outsourcing of core activities such

as maintenance. This trend is quite common among

for complex assets, such as aircrafts, and oil and gas

rigs. In these circumstances neither the asset owning

business, and nor the asset maintaining business has a

complete understanding of asset behaviour, which

obviously impacts asset lifecycle decision support.

This perspective assesses the level of integration

between the business stakeholders, such as

employees, business partners, customers, and

regulatory agencies like environmental and

government organisations. The idea here is to share

knowledge in order to enhance the efficiency and

competencies of the overall business, which

subsequently provide quality of operations.

Learning Perspective

Contemporary engineering enterprises take an

adaptive learning view. Senge (1990) argues that, for

continuous improvement adaptive learning generative

learning (Argyris 1977) as opposed to adaptive

learning should be adopted. Adaptive learning has a

short term focus and aims at solving the immediate

problems faced by the business; whereas generative

learning has a long term focus and instead of looking

at immediate issues it looks at long terms strategic

issues. Here, the learning perspective illustrates

assessing the way engineering business preserve the

knowledge that it creates in previous perspectives,

and using the same for providing triggers for change

to recalibrate its competitive strategy in terms asset

lifecycle management. These triggers are aimed at

changing asset design, processes, and business

architecture and infrastructure, whereby the objective

is to induce flexibility in over all business execution

and creativity in the processes of asset lifecycle

management.

Appendix 1 provides the details of the asset

management processes that should be assessed under

each perspective. It examines the purpose of each

process, i.e. primary or secondary, and assigns it to

the appropriate dimension of asset performance

criteria of efficiency, effectiveness, availability,

compliance, and reliability as suggested by

Woodhouse (2001) and IIM (2002). Information

systems consist of hardware components, software

applications, communications networks and facilities,

and information that is captured, exchanged,

processed, and stored to enable business operations.

Therefore, in order to assess the effectiveness of

IS/IT for each process four dimensions, namely,

people, information, applications, and technology are

selected, to be measured on a scale of 1 to 5. This

information could be collected though surveys and

with the help of Analytic Hierarchy Process (AHP)

(Saaty 1990) and Multi-Attribute Utility Theory

(MAUT) (Goicoechea et al. 1982) it could be

aggregated to provide performance measurements,

thereby providing an overall IT/IS performance

measurement for asset lifecycle management.

6 CONCLUSION

This research provides the basis for further research

into comparative analysis of IT/IS based asset

management for industrial and infrastructure assets

to be conducted through the Cooperative Research

Centre for Integrated Engineering Asset

Management (CIEAM). This paper has proposed

and theocratically demonstrated an approach for

linking asset management to strategic

competitiveness of a manufacturing business

through processes measurement and control. It has

particularly emphasised the use of IT/IS for

integration between competitive environment and

resource capabilities, competencies, and capabilities.

It has also shown how asset managing businesses

could benefit by taking a lifecycle perspective of

asset management, such that assets are treated as

business enablers rather than just production or

service provision enablers.

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APPENDIX 1

Processes Asset Performance

Criteria

IS/IT Resources

Efficiency

Effectiveness

Availability

Compliance

Reliability

Skills

Applications

Hardware

Information

Planning and Design Perspective

Asset Operation/Service Standards Definition

Asset Design and Configuration Management

Production Scheduling

Performance Perspective

Operational Requirements Compliance

Asset Performance Monitoring

Asset Condition Monitoring

Hazard Identification

Asset Depreciation and Deterioration Trending

Support Perspective

Asset Failure Prediction and Maintenance Planning

Asset Failure Root Cause Analysis

Asset Maintenance Workflow Execution

Asset Lifecycle Support Resources Management

Asset Lifecycle Budgeting and Cost Benefit Analysis

Operational Risk Assessment

Asset Treatment Options and Tradeoffs

Materials Management

Stakeholders Perspective

Third Party Services Management

Asset Operator Training and Education

Environmental and OH&S Compliance

Stakeholder Advise, Assistance, and Collaboration

Contract Management

Organisational Learning Perspective

Lifecycle Evaluation and Recommendations

Asset Lifecycle Cost Planning and Expenditure

Asset Lifecycle Knowledge Management

Asset Register Management

Project Management

Asset Performance Reporting

Competitiveness Perspective

Strategic Asset Management Planning

Strategic Business Audit

Business Partner Integration

Technology Perspective

Strategic IT/IS Planning

Information Acquisition, Integration and Storage

Technology Direction Assessment

Appropriateness of Technology to AM Processes

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