Sustainable performance of industrial assets: the role of PAS 55-1&2 and human factors

Abstract

Asset-intensive organisations are under rising pressure from their stakeholders to realise the optimum level of exploiting assets to achieve a balanced and sustainable performance (SP) over their life cycle. However, industrial organisational structures delineated along traditional disciplines fail to provide an asset-centric focus. Accomplishing SP in an asset-intensive organisation depends on the ability of the human authority in an organisational hierarchy to maintain different asset operations align with sustainable considerations. The level of physical assets' integrity in a particular industrial setting depends on the personnel ability for acquisition, exploitation (includes design and operation), maintenance, modification and disposal of critical assets and properties within the limits of universally accepted norms. Thus, human factor (HF) is a central measure to evaluate the ‘integrity’ of physical assets in asset management as the ‘integrity’ is a characteristic that human beings can have. The publically available specification (PAS) which is published by British Standards Institution (BSI) provides specification (PAS-1) and guidelines (PAS-2) for managing integrity of physical assets towards SP. This manuscript demonstrates the role of PAS 5-1&2 and HFs achieving SP. It also proposes a framework and its implementation methodology to mitigate unwanted events due to human errors leading to organisational weaknesses.

Keywords:

• human factors
• asset management
• sustainable performance
• PAS 55-1&2
• asset integrity

1. Introduction

The term ‘sustainable performance’ (SP) with regard to organisational change is defined in various ways, as sustainability cannot be defined for a single corporation (organisation) (Elkington 1998). For instance, if an operator company such as BP had not concerned about allocating adequate investment on maintenance of their sub-contracting physical assets, then an engineering contractor company such as Transocean compelled to operate their drilling rigs without performing adequate maintenance leading to catastrophic incidents such as the 2010 oil spill in the Gulf of Mexico (CCR 2011). Hence, it is a collective agreement via discussions among several organisations to conclude how to operate the physical assets in a sustainable manner without compromising the ability of the future generations with regard to societal, environmental and economic aspects (Ratnayake, Samarakoon, and Gudmestad 2011). However, in the context of industrial asset operations, the term SP does not mean sustaining the production of a particular product indefinitely (Arscott 2003; Roca and Searcy 2012). For instance, sustaining the hydrocarbon era is basically a matter of time frame, as it is a process of mining a non-renewable resource. Furthermore, SP in the oil and gas (O&G) sector is not intended to mean sustaining the production of O&G indefinitely; instead, it is to mean meeting the needs of the global society with O&G and related products at a reasonable cost, safely and with minimal impact on the environment until an alternate energy source is available (Lorek and Fuchs 2013). In general, SP is realised when the industrial asset exploitation levels ‘meets the needs of the present generation without compromising the ability of the future generations to meet their own needs’ (WCED 1987). For instance, if the catastrophic accident in the Piper Alpha production and process facility in the North Sea (1988) was prevented (i.e. by mitigating overexploitation and usage of immature maintenance procedures, where both the factors are related to human factor (HF) in terms of expertise, decision-making, awareness, competence and so on, where lack of these would be reflected as a loss of asset integrity (AI) in terms of a failure or violation of universally accepted norm), it could have been avoided the significant damage to human lives, environment and economy whilst such prevention could have been beneficial for the next generations (Ratnayake 2009). This argument has been further reinforced by the environmental, societal and economic damage caused due to the 2010 oil spill in the Gulf of Mexico. The oil spill caused loss of many human lives, destruction of natural resources and change in life pattern of the society within the proximity of the accident due to the unsustainable habits of the present generation (Ratnayake, Samarakoon, and Gudmestad 2011).

Alternatively, Don Huberts, CEO Shell Hydrogen, remarked: ‘The Stone Age did not end because we ran out of stones’ (Hargroves and Smith 2005). The meaning here is that the hydrocarbon era might well end when a suitable replacement for hydrocarbons (e.g. hydrogen, bio-fuel and so on) appears rather than when the hydrocarbons are depleted. Hence, it is paramount to ensure that the O&G production and process assets are operated in a balanced way during the transition period, taking into consideration equally economic prosperity, environment quality and societal justice (Lorek and Fuchs 2013). The aforementioned consideration has also been coined as ‘triple bottom line’ (TBL) which focuses organisations not just on the economic value they add but also on the environmental and societal value they add – and destroy (Elkington 1997).

The concept of TBL provides a ladder to reach SP, at its narrowest is used as a framework for measuring and reporting organisational performance against economic, societal and environmental parameters, whereas at its broadest is used to capture the whole set of values, issues and processes that organisation must address in order to minimise any harm resulting from their activities and to create economic, societal and environmental values. This involves being clear about the organisation's purpose and taking into consideration the needs of all the organisation's stakeholders – shareholders, customers, employees, business partners, governments, local communities and the public (Elkington 1997). Although asset performance is conventionally evaluated based on financial returns, the practice and research evidence reveal that such evaluations are somewhat inaccurate. For instance, sole reliance upon financial evaluation methods is sub-optimal in determining the performance of industrial assets (Ratnayake 2009; Kaplan and Norton 2000). Hence, the successful implementation of an asset management (AM) system requires a holistic, systematic, systemic, risk-based, optimal and sustainable view of how assets are planned and exploited from the inception of an idea to design (commission, operation, maintenance, modification, life extension) and decommission (BSI PAS 55-2 2004).

AM has also been defined in a range of different contexts. These include transport (FHA 1999; McElroy 1999), construction (Vanier 2001), electricity (Morton 1999), chemical engineering (Chopey and Fisher-Rosemount 1999) and irrigation (Malano, Chien, and Turrell 1999). Federal Highways Authority in the USA developed an AM primer to guide thinking and activities in this area which was an early and systematic attempt to understand the critical elements of AM (FHA 1999). Vanier (2001) revealed that seamless data integration, a standardisation framework and life cycle analysis are some of the challenges for AM. Apart from that, Reed and Defillipi (1990) discussed complex interactions of skills and resources, physical asset specificity and the way these assets are managed. However, Tsang (2002) revealed human dimensions as a key issue for the successful management of engineering assets (see also Ratnayake and Markeset 2011a; Ratnayake 2012). For instance, the greatest danger lies in the shortfall of human capital educated to adapt to the more sophisticated needs of modern AM (Woodhouse 2001). Although the techniques and know-how already exist, it requires those to be adapted to produce the systems needed for effective AM (Woodhouse 2001). In this context, the HF makes the weak link in the chain as the role of the AM includes translation of ideas, making an interface between business objectives and engineering reality, effecting economic outcomes from physical assets in a complex environment of changing technologies and ideas, dealing with numerous regulations and differing social values (Woodhouse 2001). Hence, the aforementioned holistic views of AM reflect the general movement in engineering circles to emphasise the importance of it rather than just asset maintenance. This enables to focus on the bigger picture of life cycle asset assessment, including strategy, risk measurement, safety and environment and HFs. In the UK, a Publicly Available Specification (PAS) has been released by the BSI, embodying the same principles of life cycle analysis, systematic risk assessment and sustainability (PAS 55-1&2 2004).

The accidents that have happened since the late 1980s (e.g. Piper Alpha 1988) up until now (e.g. BP Macondo spill 2010) as well as organisational weaknesses (e.g. continuation of environmental and societal damage due to oil spills in Niger delta) leading to human error in decisions made by industrial experts (e.g. Brent Spar) have evidenced that to date the TBL concept to reach SP has not been adequately translated into actions at the plant level of asset operations. However, the PAS provides specification and guidelines which support to achieve top to bottom, bottom to top and middle-aligned approach to meet the SP (BSI PAS 55-2 2004; Ratnayake and Markeset 2010c). Basically, PAS 55-1 provides specifications for the optimised management of physical infrastructure assets, whilst PAS 55-2 provides guidelines for the application of PAS 55-1 (BSI PAS 55-2 2004; BSI PAS 55-1 2004). The specifications and guidelines explain how to reduce uncertainties about asset behaviour, future requirements, performance values, costs and risks. Furthermore, they help to systematise an organisation into groups of functional specialism in such a way that departments are set up to design/build the assets (‘engineering’), deploy them (‘operations’ and ‘production’) and care for them (‘maintenance’). However, the specifications and guidelines provided in PAS 1&2 are prescriptive only to the extent that they define what have to be done, not how they are to be carried out. Hence, it is vital that an organisation selects the necessary tools to align its assets with its assessed needs. For instance, the strategic performance management approaches, such as ‘Balanced Scorecard (BSC)’ and ‘strategy maps’, address how managers can keep track of the execution of activities by the personnel within their control and monitor the consequences arising from their actions (Kaplan and Norton 2000). Implementation of any of the aforementioned depends on HFs [i.e. physical or cognitive properties (or social behaviours) of individuals which are specific to humans and influence functioning of technological systems as well as human–environment equilibriums] of the associated asset-intensive organisation.

This manuscript provides a framework to perform gap analysis for mitigating human errors and its implementation based on the specification stated in PAS 55-1&2 for reaching SP of industrial assets.

2. Need for sustainable asset performance

By the end of the twenty-first century, it is observed unprecedented changes in corporate strategy and management towards sustainable thinking as a result of the emergence of sustainability as corporate strategy, and making sustainability an integral part of an organisation's business strategy in order to obtain the bottom-line benefits (Enquist, Edvardsson, and Petros 2007; Epstein 2008). Hence, achieving SP in an asset-intensive organisation via TBL concerns has gained an increased prominence among industrial organisations and their stakeholders around the world (Lorek and Fuchs 2013). These concerns gained momentum in the 1980s and 2000s as a result of public outrage over some very serious, societally (people), environmentally (planet) and economically (profit) damaging accidents such as Flixborough (1974), Tenerife (1977), Bhopal (1984), Chernobyl (1986), North Sea Piper Alpha (1988), Exxon Valdez (1989), Texas City BP refinery explosion (2005), Montara spill (2009) and Macondo spill (2010). Aftermath incident reports reveal that most of these accidents caused due to a technical failure that roots back to lack in management of change (organisational weakness) and HFs (e.g. task demands, individual capabilities, work environment and human nature) in the workplace.

The loss of human lives, environmental degradation and economic deficits due to the catastrophic accidents increased the response by industry to the avalanche of regulation and public concern to revitalise the performance assessment and management systems available at the plant level of asset operations (Ratnayake, Samarakoon, and Gudmestad 2011; Arscott 2003). From the AM point of view, it is evident that some accidents are due to the overexploitation of physical assets without paying enough attention to inspection, maintenance and/or modifications (CCR 2011). From the environmental point of view, they are also due to pollution as a result of uncontrolled releases, resource scarcity, as well as global warming. Apart from that the reliance on growth, innovation and technological solutions builds a locked-in situation in an asset-intensive organisation, hindering an effective targeting of sustainability challenges without contributing to them (Lorek and Fuchs 2013; Tukker 2008). This is further exacerbated in O&G sector as by its very unsustainable nature.

Recent reported incidents reveal how asset-intensive organisations are unsustainable in connection with the level of assets exploitation. For instance, ‘the Deepwater Horizon had never been to dry dock for shore-based repairs in the nine years since it had been built’ and ‘lack of time in dry dock may have resulted in a lapse in BOP certification’. The aforementioned and other associated factors caused the Deepwater Horizon to suffer a major incident in the Gulf of Mexico (CCR 2011). As a result, goodwill of leading O&G operator company BP has been destroyed significantly, and there was loss of human lives, high-level environmental degradation and societal burden to the people living within the proximity. Aftermath investigations reveal that ‘the Deepwater Horizon did not go to dry dock because Transocean insisted on being paid its daily rate during repairs’ (CCR 2011). This illustrates how an asset-intensive organisation can commit to the over-exploitation of assets and lead to loss of whole assets due to a lack of sustainable and balanced performance.

Not only has the accidents due to unsustainable exploitation of physical assets but also Shell provided evidence on weaknesses of human and organisational performance (in terms of decision-making) alignment with sustainable lines can destroy goodwill and increase stakeholder pressure against a company. In 1995, Shell was embroiled in a public dispute over the decommissioning and disposal of the Brent Spar which was a redundant oil storage installation in the North Sea. As a result of that, the company management had to withdraw their decision and it has been remarked that ‘Brent Spar was damaging to our reputation: despite the support of independent scientists for our proposals, we did not win public acceptance. We recognized that we needed to change our approach – not just to offshore decommissioning in the UK, but to how we conduct our operations everywhere’ (Shell 1995). In addition, Shell Nigeria continues to operate well below internationally recognised standards to prevent and control pipeline oil spills (Steiner 2008). Moreover, continuous oil spills in the Niger Delta (e.g. where Shell is responsible for about 50% of petroleum production) reveal (Steiner 2008) how oil companies are operating in an unsustainable manner when they get the opportunity, whilst not employing the best available technology and practices that they use elsewhere in the world. Hence, it is vital that asset-intensive organisations measure their performance and report if they are deploying their assets in a sustainable manner. Hence, not only the accidents but also non-sustainable decision-making should be mitigated by effective assessment of industrial performance in relation to the sustainability dimensions (Tahir and Darton 2010).

3. AI: HF and SP

Within the context of maintaining corporate responsibilities continuum, SP reflects a target of corporate conformance, certifying, compliance and reporting with given standards to corporate performance in relation to stakeholder expectations (Bhimani and Soonawalla 2005; Schaltegger and Wagner 2006; Johnson 2007; Epstein 2008). Buchanan et al. (2005) consider SP as a range of work methods, goal attainment and process of development. SP also requires the transformation of mindset and commitment of the leadership and organisational performance to include key stakeholder demands (Laszlo 2003; Waddock and Bodwell 2007). In general, management SP holistically is challenging as it requires a sound management framework that integrates environmental and societal performance with economic business performance (Johnson 2007; Schaltegger and Wagner 2006; Epstein and Roy 2003). As the SP requires adherence to external standards and a shift in mindset, the responsibility lies on human hands (and associated HFs) along the organisational hierarchy.

In the context of AM, SP is assured when the AI is maintained at an anticipated level. In this manuscript, AI is defined as ‘the ability of physical asset(s) to perform their required function effectively and efficiently for generating return on investment at an anticipated level whilst safeguarding society and environment’. de Jong, Marx, and de Vos (2009) revealed the significance of human involvement in asset operations as ‘it is important that interactions between people, representing the stakeholders, be managed and carefully coordinated to avoid degradation of the overall asset integrity’. In practice, the concept of integrity is mostly understood as a characteristic that only human beings can have (Taylor 1981), whereas the concept of integrity emerges in industrial practices based on the nature of the particular industry it belongs to (Ratnayake and Markeset 2011b). For instance, BP defines integrity management (IM) as ‘the application of qualified standards, by competent people, using appropriate processes and procedures throughout the plant life cycle, from design through decommissioning’ (BP 2004). In the O&G industry, the AI is said to be assured when maintaining the pressure-containing envelope or, in simple terms, keeping hydrocarbons inside the pipes and vessels. Also, the NORSOK D-010 (2004) standard describes O&G production well integrity as ‘the application of technical, operational and organisational solutions to reduce risk of uncontrolled release of formation fluids throughout the life cycle of the well’. However, the operationalisation of integrity at different levels of an organisation remains vague, although management gurus such as Stephen Covey, Peter Drucker and Manfred Kets de Vries treat it as the quality of management (Van Maurik 2001). Figure 1 illustrates the role of human performance in the context of AI.

Figure 1 Role of human performance (factors) in the context of AI.

Although the term ‘integrity’ has been extensively used within different asset scenarios (e.g. pipeline integrity, structural integrity, well integrity and maintenance integrity), the preservation of the integrity at an anticipated level has roots back to competence and awareness of individuals those who are working within those disciplines. In this context, the level of impact of the change and/or relaxation of procedures and standards, lack of change management, change in inherent operation and environmental conditions, etc. on AI depend on the competence and awareness of industrial experts those who are responsible for different tasks. For instance, with ageing piping components' wall thicknesses are reduced due to erosion and/or corrosion. However, the required absolute minimum wall thicknesses requirement becomes lesser for preserving piping components integrity as the O&G production well pressure also inherently going down over the time, which necessitates right human judgments based on the calculations. Hence, AI is mostly dependent on human performance. Figure 2 illustrates possible AI scenarios that shall come across over the operational life of an industrial asset (Ratnayake 2012, 2010; Oliver 2002).

Figure 2 Possible scenarios of AI.

DOE Standard (2009) reveals that 80% of unwanted events in industry are due to human errors and only about 20% are due equipment failures. It also reveals that among them 70% of human errors are due to organisational weaknesses and only about 30% are due to individual mistakes. Hence (see Figure 3) more than half (56%) of unwanted events are due to organisational weaknesses leading to human errors, a quarter (24%) of unwanted events are due to individual mistakes leading to human errors and only less than a quarter (20%) of unwanted events are due to equipment failures.

Figure 3 The contribution of organisational weaknesses (leading to human errors), individual mistakes and equipment failures to unwanted events.

Hence, it is vital to mitigate organisation weaknesses that shall lead to human performance. Furthermore, a survey carried out during the offshore safety summit 2012 also revealed that the most important aspects of offshore safety are HFs in safety and company culture and leadership (OSS 2012). Figure 4 illustrates the results of the survey.

Figure 4 A survey results: most important aspect of offshore safety.

In addition to that a research study claims that although the immediate causes of major incidents frequently involve ‘human error’ of operators or maintenance personnel, the reasons that these errors occurred in the first place were the responsibility of those more senior in the organisation (Collins and Keeley 2003; Anderson 2004). This reveals another fact that human errors that caused due to organisational weaknesses also have roots back to human performance, as organisational policies and strategies are derived by senior-level personnel in an organisation. Therefore, it is apparent that focusing efforts on reducing organisational weaknesses leading to human errors can increase SP of an asset-intensive organisation. For instance, Figure 5 illustrates the factors that influence human performance.

Figure 5 Factors that influence human performance.

Although the challenge is pertaining to top or bottom level of an asset-intensive organisation, HF plays a significant role in aligning physical asset performance with reference to benchmarking specifications and/or guidelines (Ratnayake and Markeset 2010a, 2011a). Therefore, it is logical to interpret the role of human assets in the context of managing physical assets' integrity as indicated in Figure 6, concerning the connection between other critical kinds of assets (BSI PAS 55-2 2004).

Figure 6 Role of human asset and other critical kinds of assets in the context of managing integrity of physical assets.

Table 1 summarises the five categories of asset types and gives examples as specified in BSI PAS 55-1 (2004).

Table 1 Critical elements of assets and examples.

Asset category	Examples
Physical assets	Natural resources, infrastructure, machinery, plant, equipment, buildings and IT systems
Human assets	Leadership, management, workforce, skills, knowledge and experience
Financial assets	Cash, investments, equity and credit rating
Information assets	Data and information
Intangible assets	Reputation, customer and staff impression, public image/relations, brand value, licenses, patents, trademarks, copyrights and culture

Table 2 illustrates the corresponding interrelationships of assets which shall bridge the gaps between current and sustainable asset performance (de Jong, Marx, and de Vos 2009; Ratnayake 2010).

Table 2 Interrelationships of assets each other.

Intersection	Example cases for interconnecting relationships with physical assets
Financial versus physical	Life cycle costs, capital investment criteria, operating costs, depreciation and taxes
Intangible versus physical	Reputation, image, morale, level of societal and environmental compliance
Information versus physical	Condition monitoring data, data about level of degradation, status of current performance, maintenance records and backlog information
Human versus financial, intangible information and physical	Technical skills, personnel abilities, work ethics and leadership

The aforementioned discussion reveals why human intelligence and their performance cannot be replaced with innovative technologies, technological systems or sub-systems (Koch 2002) and should effectively be managed to assure the AI. Hence, in this manuscript asset integrity management (AIM) is defined as ‘preservation of asset integrity at an anticipated level’. Figure 7 illustrates the role of AIM and how AM, PAS 55-1&2 and sustainable and balanced asset performance have been linked to each other (Ratnayake 2009).

Figure 7 AM for SP.

The Offshore Division of the Health and Safety Executive (HSE) published a report of its 3-year inspection initiative known as Key Programme 3 (KP3). This was a comprehensive appraisal of AIM of offshore installations on the UK Continental Shelf and revealed significant issues regarding the maintenance of safety-critical systems used in major accident hazard control in the industry. The KP3 report stated that the influence of the engineering function had declined to a worrying level as a result of technical authorities being under pressure, often reacting to immediate operational problems rather than taking a strategic view to provide expertise and judgement on key operational engineering issues (KP3 2007) and ‘senior management in the industry had failed to adequately monitor the status of asset integrity’ (KP3 2007). Therefore, it is vital to carry out continuous asset performance analysis and AIM to reach SP (NORSOK N006 2009).

In this context, AI (see, Figure 8) is split into three to realise the overall picture, i.e. design integrity (DI): ‘assurance that facilities are designed in accordance with governing standards and meet specified operating requirements’; operational integrity (OI): ‘appropriate knowledge, experience, manning, competence and decision-making data to operate the plant as intended throughout its life cycle’ and technical integrity (TI): ‘appropriate work processes for inspection and maintenance systems and data management to keep the operations available’ (de Jong, Marx, and de Vos 2009).

Figure 8 AI in terms of DI, OI and TI.

In terms of AI, the AM system controls appropriate work processes for the acquisition, exploitation (includes design and operation), maintenance, modification and disposal of critical assets and properties. The AIM plays the role of preservation of AI at an anticipated level with the help of personnel who are responsible for different levels of asset exploitation. The role of PAS 55 as well as AI, AIM and AM is illustrated in Figure 9.

Figure 9 Role of PAS 55 1&2 as well as AM, AIM and AI.

The ability of physical assets to perform their required function depends on to what extent the responsible personnel in an organisation has adopted benchmarking practices. Hence, in order to manage industrial assets, it is vital to assess the gaps between current practices and benchmarking practices. This manuscript utilises specifications and guidelines provided in PAS 55-1&2 for the optimised management of physical infrastructure assets. Basically, they provide a minimum requirement for achieving SP. Figure 10 highlights the PAS 55 elements which align the performance of an asset-intensive organisation with mandatory SP demanded by its stakeholders (e.g. government, shareholders, customers, activists and surrounding society).

Figure 10 PAS 55 structure.

Almost all the elements are related to AI and alternatively human performance-related aspects within different disciplines along an organisational hierarchy in an asset-intensive industrial organisation. Hence, it is vital to assess to what extent (i.e. the gap between current status and what is demanded by benchmarking practices) these elements have been utilised by the particular asset-intensive organisation. Also, such analysis would reveal gap between the talents available to deliver the specifications and guidelines provided in the PASS 55 and the typical training or education required for the personnel involved with asset operations (BSI PAS 55-1 2004; Ratnayake and Markeset 2010a, 2010b, 2011a; Ratnayake 2012).

4. Gap analysis in relation to PAS 55-1&2

Behn (2005) stated that ‘if you're not measuring, you're not managing’. Thus, for managing the assets in a sustainable manner, it is vital to measure their performance. Managing assets in a sustainable manner or reaching SP in an asset-intensive organisation is something that can be achieved via properly directed human performance based on their experience, awareness, competence, decision-making power, etc. and providing necessary training. In order to measure asset performance, a gap analysis procedure is proposed which enables to measure the gaps between the current status of human performance and the PAS 55 specifications and guidelines. The degree of the gaps would reveal the level of AI. In this context, in order to get an overall picture about the asset performance, such an analysis is suggested to perform in terms of DI, OI and TI requirements of the particular organisation. Figure 11 illustrates a framework for such gap analysis process.

Figure 11 A framework for measurement of asset performance: gap analysis.

Basically, depending on the asset-intensive organisation, the focus of gap analysis might be different. For instance, the focus of an operator company would be its final product and the consequences in relation to the production process. On the contrary, engineering service provider or contractor company involved with fabrication and manufacturing required for physical assets would be providing consultancy services (e.g. operation, maintenance, modification and life extension) and performing inspection, maintenance and modifications, etc. However, human performance is central to any kind of the asset-intensive organisation. This manuscript considers twenty-five elements which have been highlighted by PAS 55 to illustrate the possible gap analysis process (see Table 3).

Table 3 Elements of PAS 55 for finding gaps.

PAS 55	Section	PAS 55	Section
4.1.0	General requirements	4.4.2	Training, awareness and competence
4.2.0	AM policy and strategy	4.4.3	Consultation and communication
4.2.1	AM policy	4.4.4	Documentation
4.2.2	AM strategy	4.4.5	Document and information control
4.3.0	AM information, risk assessment and planning	4.4.6	Operational control
4.3.1	AM information systems	4.4.7	Emergency preparedness and response
4.3.2	Risk identification assessment and control	4.5.0	Checking and corrective action
4.3.3	Legal, regulatory and statutory	4.5.1	Performance and condition monitoring
4.3.4	AM objectives	4.5.2	Failures, incidents, non-conformance and actions
4.3.5	AM performance and condition targets	4.5.3	Records and record management
4.3.6	AM plans	4.5.4	Audit
4.4.0	Implementation and operation	4.6.0	Management review and continual improvement
4.4.1	Structure, authority and responsibility

To perform the gap analysis, one-to-one interviews can be carried out with a cross section of middle to executive management. The interviews are designed with a selection of options to evaluate the current status of the asset-intensive organisation against a scale of ‘innocence to excellence’. Examples shall be used to help the candidate to agree to the current status of the asset-intensive organisation against the twenty-five elements of AM as set out in PAS 55. Figure 12 illustrates a sample model of questionnaire that can be used to carry out the gap analysis (Eskom 2007).

Figure 12 A sample model of questionnaire.

By carrying out the gap analysis based on the aforementioned approach (see Figure 12), the current status of human performance in relation to physical assets is possible to summarise as illustrated in Figure 13. Thus, depending on the severity of the gaps in between the current and the intended performance (see, Figure 13), the asset managers can start mitigating them as appropriately to meet with SP levels.

Figure 13 Sample distribution of PAS 55 score.

This kind of analysis also allows the consistency of AM performance across the asset-intensive organisation – comparing results across departments and geographically different regions. The aforementioned approach is validated via a case study done in a power transmission company, and the reliability of the method is assured (Eskom 2007). The aforementioned kind of analysis enables recognizing to what extent the same organisation follows benchmarking practices. This enables to distinguish SP between when it is an obligation, i.e. merely to get an extension of licence to operate (e.g. Shell operations in the North Sea and Norwegian Continental Shelf), and when it is not an obligation (e.g. oil spills in Niger delta – Shell is responsible for about 50% of petroleum production). Figure 14 summarises the process of performing gap analysis.

Figure 14 Identifying the benefits and assessing them against the investments required to realise improvements.

The phases 2 and 3 in Figure 14 illustrate the process for identifying the benefits and assessing them against the investments required to realise improvements.

5. Conclusion

The application of AIM has evolved; its focus and usage has varied considerably, not only between different industries but also between organisations (and different geographical locations) within the same industry. The method suggested in this manuscript provides means to assess gaps between current performance and standard requirements (e.g. PAS 55-1&2) of an asset-intensive organisation. This enables to mitigate organisation weaknesses that can lead to human errors. Alternatively, such an approach would sustain abilities of asset performance providing sufficient return on investments without endangering HSSE.

However, different asset-intensive organisations should adapt specifications and guidelines specified in PAS 55-1&2 according to their needs. As human performance dominates as they cannot be replaced with the so-called latest technologies, technological systems or sub-systems, it is vital to manage the change efficiently and effectively. For instance, a research carried out by the Ethics Resource Center revealed that 29% of the employees questioned feel under pressure from their manager to compromise their own ethical standards in line with the company's objectives (Kaptein 1999). The methodology suggested in this manuscript provides means to mitigate aforementioned by sticking to universally accepted guidelines and specifications. It also enables assessing current performance and assigning the right personnel in the right place to carry out the right job to achieve SP.

In addition, it is the author's experience that some of the engineering contractor/operator companies are not concerned about sending the right personnel along the ladder based on their skills and qualifications. Instead, they are being isolated in the same kind of discipline. This leads them to change company just to get the next promotion, which reduces the organisation's AI as a result of brain drain. For instance, it takes a transition period to bring new recruits to the required level of performance. This is another challenge for asset-intensive organisations to maintain the specified integrity levels of their assets during such transition periods.

Future research should be carried out to analyse how to prioritise optimal improvement plans for earning return on investments without damaging natural environment (e.g. reduction of CO₂ emissions, spill outs and leakages) and assuring health and safety (e.g. process safety and personnel safety).