transfer of knowledge from service phase case study

8/10/2019 Transfer of Knowledge From Service Phase Case Study

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Research in Engineering Design

ISSN 0934-9839

Volume 23

Number 2

Res Eng Design (2012) 23:125-139

DOI 10.1007/s00163-011-0118-5

Transfer of knowledge from the servicehase: a case study from the oil industry

G. Vianello & Saeema Ahmed


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O R I G I N A L P A P E R

Transfer of knowledge from the service phase: a case studyfrom the oil industry

G. Vianello Saeema Ahmed

Received: 11 November 2009/ Revised: 20 June 2011 / Accepted: 28 July 2011/ Published online: 21 August 2011

Springer-Verlag London Limited 2011

Abstract This paper aims to investigate the knowledge

generated during the later phases of the life cycle of acomplex customised product and understand how this

knowledge is transferred between projects and between

different user groups. A series of four identical rigs for

offshore drilling was selected as a case study, and the

transfer of knowledge between the first two rigs was

explored through two sets of interviews with the rig

operators and the project management team. The expected

knowledge transfer strategies that emerged from the first

set of interviews were analysed and compared with the

actual transfer mechanisms identified in the second set of

interviews, and similarities and differences were investi-

gated. It was found that the transfer of knowledge primarily

occurred within the individual phases of the products life

cycle, and there was poor transfer across the different

phases.

Keywords Product life cycle management Design

knowledge management Information management

Service One-off machinery and oil industry

1 Introduction

The general trend, when designing a product, is to consider

issues related to the different phases of its life cycle in

order to improve its behaviour during operation. Hence, the

identification of the knowledge generated throughout a

products life cycle and its feedback to engineeringdesigners plays an important role in product development.

Variant design industries have begun to understand the

importance of service knowledge as they move towards

selling a product service system (PSS): for example, in the

aerospace industry, power by hour rather than an engine is

sold. Even in industries which have not moved towards a

PSS, the knowledge of how a product behaves in service is

still relevant, e.g. in the case of user-driven innovation for

consumer products. The adoption of a knowledge man-

agement system coordinated at an organisational level is

imperative in order to support the sharing and reuse of

knowledge from the different phases of product life cycle

in a systematic manner. Studies in the management field

indicated that a sound management of internal knowledge

is a key factor for the competitiveness of a company

(Zander and Kogut 1995). However, knowledge manage-

ment strategies do not always lead to the desired result,

particularly when they address knowledge from different

sources and phases of the life cycle of the product. Inte-

grating different perspectives and taking into account the

interests of the variety of users is necessary to ensure a

coherent and satisfactory organisation of engineering

knowledge (Ahmed 2005). Additionally, a knowledge

management strategy should cover the entire life cycle of a

product and facilitate the retrieval and reuse of information

whilst avoiding overloading the users with unnecessary

information.

In the case of the research presented here, the focus is

upon a complex business-to-business industry, specifically

the design of oil drilling systems and rigs. The choice of

this case study was motivated by the characteristics of the

industry. The drilling systems are specific for each rig, and

redesign or adaptation of equipment and assembly is

G. Vianello S. Ahmed (&)

Department of Management Engineering,

Section of Engineering Design and Product Development,

Technical University of Denmark, Building 426,

Produktionstorvet, 2800 Lyngby, Denmark

e-mail: [email protected]

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DOI 10.1007/s00163-011-0118-5


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required from one rig to the next. Hence, the transfer of

knowledge and experience between rigs is essential, whilst

reusing a design (as may be possible in the case of variant

industries) is not always an option. Designing the drilling

system without flaws the first time is crucial as the testing

phase is limited compared to variant industries and the cost

of downtime of a rig in operation is in the range of hun-

dreds of thousands of USD per day. Hence, a systematictransfer of knowledge from previous rigs to engineering

designers involved in the development of new rigs is cru-

cial to avoid recurrent problems.

2 Literature review

2.1 Knowledge management

In the last decades, it has been widely recognised that a

firms competitive advantage depends more than anything

on its knowledge and the way it is able to manage it (Alaviand Leidner 2001; Zack 1999). This view suggests that

knowledge is the most strategically significant resource of

a firm, as what firms do better than individuals is the

sharing and transfer of the knowledge between members of

the organisation (Prusak 1997). According to this per-

spective, knowledge-based resources are usually difficult to

imitate and socially complex; hence, the knowledge and

capabilities available within a firm are the major determi-

nants to achieve competitive advantage and superior

performance.

Grounded on these premises, research on knowledge

management has focused upon improving the exploitation

of knowledge in the context of organisations, to achieve

enhanced performance, increased value, competitive

advantage and return on investment. Managing knowledge

involves taking into consideration both individual and

collective knowledge and developing strategies through the

analysis of the context, i.e. the organisation where

knowledge needs to be exploited, and the identification the

content, i.e. the knowledge that needs to be reused (Kogut

and Zander1992).

The first step when approaching knowledge and its

management is defining what knowledge is. A widely

adopted framework is the one proposed by Polanyi, based

upon the distinction between explicit and tacit knowledge:

explicit knowledge can be captured and distributed, whilst

tacit knowledge is related to the personal skills or experi-

ence of an individual and is more difficult to disseminate

(Polanyi1966).

This distinction between tacit and explicit knowledge is

fundamental for the analysis of the phenomenon of

knowledge creation and transfer, as the creation of new

knowledge is based on a continuous process of interactions

between explicit and tacit knowledge (Nonaka 1991). The

combination of the two categories occurs through four

conversion patterns, described by Nonaka (1991) in the

SECI (socialisation, externalisation, combination, inter-

nalisation) model. According to this model, the patterns of

knowledge conversion are as follows:

From tacit to tacit: through socialisation;

From tacit to explicit: through externalisation;

From explicit to explicit: through combination;

From explicit to tacit: through internalisation (that

represent the traditional notion of learning).

Three of the four types of knowledge conversionso-

cialisation, combination and internalisationare described

in organisational theory. Socialisation is connected with

theories of organisational culture, combination is rooted in

information processing and internalisation is associated

with organisational learning. By contrast, the concept of

externalisation has been covered by literature on cognition

from the individual point of view, but has not beenextensively investigated in organisations. Research on

cognition has also defined knowledge in relation to other

forms of cognition, such as information and experience.

One such example is the definition of the DIKW (data,

information, knowledge and wisdom) pyramid, showed in

Fig.1, which represents the different entities in a hierarchy

from the lower level, represented by data, to the higher

level, embodied in wisdom (Rowley2007; Ackoff1989).

However, the distinction between data, information,

knowledge and wisdom is not always clear as it is depen-

dent on the knowledge and experience of the person

involved (Ahmed2000); for this reason, a more pragmatic

approach towards knowledge has been proposed by Von

Krogh et al. (2001). They introduced the concept of a

knowledge domain, consisting of the set of relevant

data, information, articulated and tacit knowledge in rela-

tion to a particular subject. The term knowledge, as used

in this paper, is in line with the concept of knowledge

domain proposed by VonKrogh and Nonaka and includes

both explicit and tacit elements, whilst information is

used interchangeably with codified knowledge (i.e.

knowledge that has been made explicit).

Fig. 1 DIKW hierarchy

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Knowledge management can be approached from two

different perspectives, depending on whether the attention

is focused upon tacit knowledge (behavioural approach) or

explicit knowledge (technocratic approach) (Earl 2001;

Easterby-Smith and Prieto 2008). The behavioural

approach focuses on the behaviours of individuals and on

social relations and cultural factors that influence the

transfer of organisational knowledge and is frequentlyrelated to the structure of an organisation. The technocratic

approach focuses on the information systems which are

designed to manage knowledge, for instance IT infra-

structures, applications, databases and technical proce-

dures. Some research suggests that these two approaches

represent two complementary views as both share an

interest in knowledge for the benefit of the organisation

(Pan and Scarbrough1999); however, other authors suggest

that a clear selection of the approach to follow, depending

the characteristics of the organisation in question, is nec-

essary in order to develop a successful knowledge man-

agement strategy that supports the transfer and reuse of acompanys internal knowledge (Hansen et al. 1999). The

range of knowledge management strategies that are derived

from these two approaches extend from strategies focused

on personalisation (from the behavioural approach), which

aim to support the sharing of information within the

organisation by building personal networks amongst

employees (Wenger2000), to codification strategies (from

the technocratic approach) which try to solve issues con-

nected with knowledge management through information

and communication technologies (McMahon et al. 2004).

The selection of the appropriate strategy is influenced by

the type of organisation and product.

Argote et al. proposed a framework based upon

empirical evidence that aims to cover these different

approaches towards knowledge transfer in organisations

(Argote and Ingram 2000). They identified three basic

elements for transferring knowledge at the organisational

level: tools, tasks and members. The three elements

themselves and the networks formed by their combination

are identified as reservoirs of the organisations knowl-

edge. Tools represent the technological elements within

the organisation; tasks represent the goal and purpose,

whilst members are the individuals who form the resour-

ces of the organisation.

The framework suggests that knowledge transfer can

occur through two distinct mechanisms, as follows:

Moving a knowledge reservoir into a different context,

e.g. adopting a software tool, which is already in use in

one department, in other parts of the organisation.

Modifying a reservoir at the recipient side, e.g.

enhancing the knowledge of employees through a

training programme.

To have a positive impact on organisational perfor-

mance, the networks formed by the three basic elements of

the reservoirs must be compatible with other networks

within the organisation where knowledge is expected to be

reused.

This framework not only covers both codification and

personalisation approaches towards knowledge transfer but

also explains the difficulties in transferring knowledgeacross disciplines, as in this type of knowledge transfer, the

environment where knowledge was generated is not always

compatible with the environment where knowledge is

meant to be reused. Hence, the transfer of knowledge

across disciplines requires more complex mechanisms than

the transfer of knowledge within a homogeneous group.

According to the framework for managing knowledge

across boundaries proposed by Carlile (2004), when a

pragmatic boundary is present, that is when the parties

have different interests, knowledge needs to be translated

according to the needs of the receiver in order to be suc-

cessfully shared. Bechkys research is in line with Carlilesand describes the importance of a local work context that

acts as boundary object in order to build a common

understanding, shared within an organisation, that enables

the communication and transfer of knowledge across dis-

ciplines (Bechky2003).

Despite the difficulties that might represent a barrier for

transferring knowledge across disciplines, organisations

should try to facilitate this type of knowledge transfer as

dissimilarity is a condition for learning and a variety of

points of views support exploration of new solutions and

facilitate innovation (March1991).

2.2 Knowledge management in engineering

In the engineering field, companies employ knowledge

management systems to capture, structure and organise

their growing amount of internal knowledge in order to

facilitate its retrieval and reuse, especially during the

development process. For example, in the case of variant

design, up to 70% of information is reused from previous

solutions (Khadilkar and Stauffer 1996). Furthermore, the

current trends in the career paths reduce the probability of

an engineer having a lengthy career within a single com-

pany. This limits the build-up and reuse of personal

expertise across projects and motivates companies to

implement new approaches to facilitate the learning pro-

cess and the reuse of past experience. Empirical studies

have showed that novices have difficulties in formulating

questions and defining what they are looking for, hence

highlighting their need for support in searching for

knowledge (Ahmed et al. 2003). Wimalasiri et al. (2008)

described how the problem of building appropriate skills in

novice engineering designers is a main concern for the oil

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industry as poor competences and diverging work pressures

posed a barrier to the development of effective design

solutions.

Interest in knowledge management by the engineering

design community has recently increased, as the focus of

engineering design has moved from the product itself to a

broader approach embracing the different phases of its life

cycle and a new set of methods and tools, enabling thetransfer of knowledge throughout the life cycle, has

become necessary. This shift is motivated by a growing

awareness that the value of a product is related to its

behaviour during operation and by the market moving its

interest towards services and product service systems. One

consequence is the need for companies to implement

knowledge management systems that cover the entire life

cycle of their products and facilitate the reuse of infor-

mation from products already in operation during the

development of new products. Although current progresses

in managing information include the use of metadata to

facilitate the retrieval of documentation available inknowledge repositories, research is still needed in order to

understand how to efficiently capture and retrieve infor-

mation, especially with regard to information generated in

the later phases of a products life cycle (Ding et al. 2008).

In relation to the DIKM hierarchy described earlier,

most of the research from the engineering field has

addressed the topic of knowledge management at the data

and information levels (Giess et al. 2008; Jagtap 2008).

This approach is aligned with the technocratic approach

and results in developing knowledge-based engineering

systems to support the management of codified information

(Earl2001). In this context, knowledge transfer is still seen

in terms of information flow and can be evaluated by

monitoring the use of shared files and folders (Tribelsky

and Sacks2010).

However, a new awareness that the development and

implementation of IT solutions is not always the best

strategy to support knowledge management has recently

characterised the engineering domain. Researchers in

knowledge management from engineering have started

investigating how to develop knowledge management

strategies that go beyond the deployment of IT tools and

take into consideration factors such as the type of infor-

mation that engineering designers would like to have

access to (Bracewell et al. 2004). A number of studies have

recently been conducted in the engineering field to under-

stand the characteristics of the knowledge generated in the

service phase and how this can be reused to support

engineering designers during the design of similar products

(Jagtap et al. 2007; Wong et al. 2008). The reuse of

knowledge from service during the design phase is par-

ticularly critical as life cycle knowledge is generated over a

long period of time by people with different interests and

experiences; in addition, knowledge gathered from opera-

tions and service is more difficult to capture in comparison

with design knowledge due to its dynamic nature and the

absence of planned reviews when it is validated and

structured. Furthermore, the way this knowledge could be

utilised during the design process is not always clear at the

time when knowledge is generated and captured into

documentation.Jagtap et als (2007) research investigated the informa-

tion generated during the service phase from a design

perspective through a case study conducted within the

aerospace industry. They identified maintenance and fail-

ure data, reliability, service instructions and life cycle costs

as the knowledge from service that is most relevant for

engineering designers. The same research found that the

distributed nature of service information, spanning across

different repositories, was a barrier for retrieval of infor-

mation and for achieving a systematic reuse of service

information by engineering designers.

Another study, also carried out within the aerospacedomain, developed a proposal for organising service

knowledge and incorporating it into the design phase based

upon service-oriented architecture (Wong et al. 2008) and

resulted in the definition of an ontology to integrate dif-

ferent knowledge repositories.

This literature review shows that various studies agree

on the importance of knowledge management, both from

engineering and business perspectives. However, the

investigation into the topic in an engineering context is

mostly limited to the information level and tends to

exclude the analysis of personalisation strategies and

transfer mechanisms. A broader understanding of the

phenomenon of knowledge transfer in relation to technical

knowledge is required, in order to develop a knowledge

management system suitable for the needs of designers and

technical personnel involved throughout a products life

cycle. This paper aims to close this gap investigating the

expected and actual transfer of knowledge in an engi-

neering context and analysing which are the features that

should characterise a knowledge management system tar-

geting the reuse of knowledge from the operational phase.

3 Aims

The purpose of this paper is to investigate the knowledge

generated during the later phases of the life cycle of

complex customised products, namely during installation,

commissioning and operation, in order to understand how

this knowledge is transferred across products.

The study was based on the assumption that knowledge

is transferred and reused differently within a product,

throughout its life cycle, and across products. The research

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project presented in this paper aimed to verify the

assumption made and investigated the transfer mechanisms

that are adopted in an industrial context through a case

study from the oil industry. The selected case study,

described in detail in Sect. 4, focused upon the transfer of

knowledge within and across customised products and

between different user groups, in order to understand to

what extent knowledge in customised industries can beshared across products despite their customised nature.

Moreover, the mechanisms for transferring knowledge

have been investigated.

From a research perspective, this study aims to con-

tribute to research in engineering knowledge management

by identifying the characteristics of the knowledge that is

relevant to reuse within a products life cycle and across

customised products. On the other hand, the findings from

the case study aim to support the development of a

knowledge management strategy in industry by identifying

the dimensions in which it is valuable to reuse knowledge

from the life cycle of customised products and the mostsuitable mechanisms that can be used to support knowledge

transfer.

4 Research methods

4.1 Case selection and data collection

A case study approach was selected as the most suitable

method for the research project, as the project aimed to

investigate knowledge transfer in industry (Yin1994). The

case selected was a series of oil rigs for offshore drilling;

this choice was motivated by the fact that the reuse of

knowledge generated in the later phases of a rigs life cycle

is crucial for the oil industry, where a successful knowl-

edge management strategy results in avoiding recurrent

issues and facilitating the transfer of operational experience

across rigs. However, the customised nature of the oil rigs

makes the reuse of knowledge particularly challenging.

The drilling contractor that collaborated on this project

is the owner of a fleet of offshore oil rigs that are rented to

oil companies. Each rig has specific characteristics that

make it suitable for operating in well-defined conditions,

since its design takes into account the drilling environment

(water depth and location) and the features of the reservoir

(size, temperature, pressure, etc.) where the rig is expected

to be operating. The drilling contractor considered the

reuse of knowledge generated in the later phases of a rigs

life cycle crucial for its business, as the high costs of

downtime and maintenance, together with strict regula-

tions, make it imperative to avoid recurrent issues and

facilitate the transfer of operational experience across rigs.

Additionally, the performances of a rig in operation impact

its value on the market.

The selected case study consisted of a series of oil rigs

that needed to be completed with a 6-month delay between

each rig. These rigs, from a construction point of view,

were to be considered copies, as the intention of the drilling

contractor was to reuse design and the experience from

installation and commissioning of the first rig in the sub-sequent rigs. The series of rigs in question included four

rigs, however the research project specifically focused on

the first two rigs of the series, that were the object of two

sets of interviews: (1) the first set of interviews was con-

ducted at the end of the commissioning phase of the first

rig, whilst it was entering into operation and the other rigs

were under construction; (2) the second set of interviews

was conducted 6 months later at the end of the commis-

sioning phase of the second rig.

The first set of interviews investigated how knowledge

transfer was expected to occur across the series of four rigs,

whilst the second set of interviews investigated the actualtransfer and reuse of the knowledge generated on the first

rig.

A total of eighteen interviews were carried out in the

two rigs. The participants represented both the project

management team and the operating crews, see Table 1.

The interviews were semistructured with questions related

to knowledge required during commissioning and service

and questions related to transfer of knowledge within and

across departments.

Not all participants were asked all the questions, as only

certain groups of questions were relevant for some of the

interviewees. All interviews lasted between 15 and 45 min

and were audio-recorded.

4.2 Data analysis

The interviews were transcribed, divided into 2,400 seg-

ments representing meaningful instances and coded by two

coders, using a predetermined coding scheme. An inter-

coder-reliability check was conducted to understand to

what extent subjective factors connected to a coders per-

sonal perception of the content of the interviews could

influence the application of the coding scheme. The dis-

agreement between coders was calculated through Cohens

kappa test, and kappa was found to be 0.9 in a scale from 0

Table 1 Participants interviewed

Rig 1 Rig 2

Department Project

team

Operation Project

team

Operation

No of participants 4 4 4 6

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to 1, where 1 represents the total agreement. This kappa

level was deemed to be acceptable. All disagreements were

checked and an agreement reached.

The coding scheme was elicited from literature on

engineering design and knowledge management, particu-

larly on knowledge transfer. The scheme includes two

categories:

Knowledge characteristics,

Knowledge transfer.

Each of the two categories embraces codes and sub-

codes. Subcodes within a code are mutually exclusive. The

codes used to investigate knowledge characteristics were

related to:

The type of knowledgeThe subcodes were based on the

ontology proposed by Ahmed (2005) to classify

engineering knowledge; this was integrated with the

types of knowledge specific of the case that were

elicited through a bottom-up approach. The stage of the knowledge life cycle The subcodes

represented the phases of the knowledge management

process proposed by Wallace et al. (2005).

Multiple aspects of knowledge transfer were investi-

gated in the analysis of the interviews and taken into

consideration when developing the coding scheme. The

codes used were as follows:

Type of captureThis code was based on the distinction

between personalisation and codification strategies

described by Hansen et al. (1999) and McMahon

et al. (2004). Dimensions This code, based on the different dimen-

sions for transferring knowledge, was developed

through a bottom-up approach, since a preliminary

analysis of the interviews suggested that different

patterns for transferring knowledge were followed,

depending on whether the transfer occurred within a

rig, across similar rigs part of the same project, or

across projects.

Initiation mechanisms This code aimed to investigate

whether the knowledge was made available by the

sender (pushed), required by the received (pulled), or

transferred through other mechanisms, e.g. formal and

informal meetings. These codes were derived from

McMahon et al. (2004).

An overview of the categories and the codes, together

with their definitions, is shown in Table 2, whilst Table3

shows an example of how the coding scheme was applied

to the transcribed interviews. The fragment is part of an

interview with a member of the drilling crew working on

the second rig of the series.

First, the transcripts were analysed to identify the rela-

tionships between the different codes, for instance to under-

stand whether an initiation mechanism could be associated

with a specific dimension of knowledge transfer or a specific

type of knowledge. A further analysis was subsequently con-ducted to investigate in more detail the inferences regarding

knowledge transfer that emerged from the first study.

5 Results

Three dimensions of knowledge transfer have been elicited

from the interviews with operators and project managers,

as illustrated in Fig. 2:

Within a rig In this case, the transfer of knowledge is

related to the progress of that rig, its life cycle and

operation and takes place through handover, records,talk amongst colleagues, etc.

Across rigs part of the same project(i.e. that share the

same design). In this case, knowledge from the first rig

is reused in the next ones of the same series through

moving the crews from one rig to another, transfer of

change records, reuse of procedures, etc.

Table 2 Coding scheme

Categories Codes (subcodes) Definition Literature

Knowledge characteristics Type (product, process, issues,

etc.)

What the knowledge is about Ahmed (2005), integrated

through a bottom-up

approachStage (capture, retrieve/reuse,

transfer)

Phase of the knowledge life cycle Wallace et al. (2005)

Knowledge transfer Type of capture (personal,

codified)

Transfer through structured ways or

relying on human factors

Hansen et al. (1999);

McMahon et al. (2004)

Dimensions (across projects,

across rigs, within rig)

Transfer within a rig, across rigs part

of the same project or across

projects

Defined from the interviews

through a bottom-up

approach

Initiation mechanism (push/pull/

fixed)

Transfer pulled by the receiver,

pushed by the sender or initiated by

fixed means

McMahon et al. (2004)

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Across projects In this case, knowledge is gathered

through lessons learnt, personal knowledge and main-

tenance records and is reused in subsequent projects

(i.e. a different series of rigs).

The identification of the three distinct dimensions in

which knowledge was transferred led to reformulating the

scope of the research project. The assumption that initially

motivated the research project was that knowledge was

Table 3 Example of coded interview, extract from an interview with a rig operator

Text Missing Wanted Object Type of

capture

Dimension Mechanism

Q: Do you have contact with people covering your position in the

previous rig?

A: Yes

Q: When do you contact them?A: Thats via mail. We are forwarding the things of any kind of interest Personal Across

rigs

Push

Q: Do you contact the first rig if there is a problem or do you contact

them to ask how they have done things?

A: We have given up with the official way of lessons learnt. It is not

working efficiently. The problem with these lessons learnt and crew

comments is that people see that nothing have been done or anything

() Now we just do it our way and then its because I know them

personally and Ive been working with those guys on the first rig for

years. This is how we do it this is how we have done our piping system

Issues,

changes

Personal Across

rigs

A: Then of course in the official drawing and documentation in our SAP

system. Everything should be documented in the drawing and I need to

make the drawing change request, so that I file whatever I do on

drawings. But we have given up on we really want to be so good onthe next rigs . I have plenty of work and much of this comes from

give a hint or give a call something. We should be used to a more

structured way of implementing changes but unfortunately its not the

real world. I was so nave to believe in that at the beginning but

Issues,

changes

Codified Push

Q: Were you involved in the lessons learnt in the last rig?

A: Not really, there is this readiness team who is supposed to catch up

everything but its somehow down the line between readiness,

operation and project. The communication is too bad. Ive seen some

mails but I dont know who decides what is necessary or what is a good

idea for us and what is just something that that Rig1 considers a good

idea. Most of the changes that I have made here maybe the next rig

dont consider them very beneficent. Unfortunately there is some

anarchy into it but I believe thats unavoidable thats how the things

are

True Issues,

changes

Codified Across

projects

Q: What is the procedure? If you want to get a product improvement

A: There is really no procedure True Procedure Codified

Across

Rigs

Across

Rigs

Within RigAcross Projects

Rigs part of a

different

project

RIG X

RIG Y

RIG 1

RIG 2

RIG 3

RIG 4

Series of rigs

part of the

project

investigated

Rigs wherethe interviews

were

conducted

Within RigFig. 2 The interviews

conducted on the first and the

second rigs part of a series of

four rigs sharing the same

design suggested that

knowledge was transferred in

three dimensions: within a rig,

across rigs part of the sameseries and across projects

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transferred and reused differently within a product

throughout its life cycle (i.e. an oil rig) and across products

(i.e. across oil rigs); however, the interviews indicated a

clear difference in how knowledge was transferred: (1)

across similar rigs that are part of the same project (across

rigs) and; (2) across rigs from different projects (across

projects).

This distinction is interesting as the dimensions in whichknowledge is transferred are expected to influence the

types of knowledge that is relevant to transfer and how

knowledge needs to be structured and retrieved.

The knowledge from the later phases of a products life

cycle is strictly connected to the specific context when it is

generated. Consequently, when documentation from ser-

vice is expected to be reused in different circumstances,

e.g. across rigs or projects, a translation process needs to be

included at some point of the knowledge management

process in order to turn available information into static

knowledge that is easier to relate to different contexts.

The three dimensions described here were integratedinto the predetermined coding scheme and considered in

relation to knowledge transfer during the analysis of the

interviews. The results from the analysis of the interviews

are reported in the following sections.

5.1 Types of knowledge

The types of knowledge were investigated in relation to the

dimensions of knowledge transfer for which they were

relevant, see Table4. Knowledge transferred in any

dimension was mainly related toproject(including lessons

learnt, comments from the crew and the client, status,

outstanding tasks, project documentation) followed by

knowledge on changes, issues and improvements. Project

knowledge is dynamic and hence characterised by the need

to be continuously updated to reflect its development over

time. When transfer is expected to take place through

codification strategies, this type of knowledge needs to be

translated into static knowledge in order to be applicable

beyond the original context, i.e. reused across projects.

The reuse of knowledge from a rigs life cycle across

rigs (that are part of the same series), together with the

reuse of the rigs design and financial advantages, was the

main motivation for the company to build a series of four

rigs instead of a single one. Instances describing the reuse

of knowledge across rigs from the interviews on the first rigof the series did not refer to any specific type of knowl-

edge. From the interviews on the second rig, it emerged

that the knowledge of relevance across the rigs was related

to project, changes and issues, and knowledge about

operations. Additionally, the investigation into the actual

situation through the interviews on the second rig showed

that these types of knowledge were not specifically

addressed to any one dimension, e.g. knowledge of a pro-

ject can be used both within a rig and across rigs, or

changes leading to improvements can be implemented both

in other rigs of the series and in other projects. This makes

the organisation of the documentation more difficult todefine, as the possibilities for multiple reuse should be

reflected in the document.

5.2 Knowledge transfer

5.2.1 Dimensions of knowledge transfer: within rig,

across rigs, across projects

The interviews were then analysed in respect to the three

dimensions of knowledge transfer. In the majority of

instances, the transfer was limited to across rigs within the

same series or within a rig, with instances of transfer

across projects (from one series of rigs to another) being

less than 20% of the total (see Table5). The instances

coded against not specified described information and

knowledge that could be used in multiple dimensions, e.g.

both within a rig and across rigs. However, the distribution

of the number of instances on knowledge transfer across

Table 4 Types of knowledge against the dimensions of knowledge transfer

Within rig Across rigs Across projects Not specified Total

Rig1 Rig2 Rig1 Rig2 Rig1 Rig2 Rig1 Rig2 Rig1 Rig2

Product 2 2 2 1 2 2 0 0 6 5

Changes and issues 2 4 19 16 2 0 0 4 23 24

Project 2 8 10 23 7 5 1 15 20 51

Organisation 0 0 0 1 0 0 0 0 0 1

Operation and service 9 1 2 9 1 2 1 0 13 12

Procedures 0 2 0 2 0 1 0 0 0 5

Not classified 5 1 28 1 4 0 1 0 38 2

Total 20 18 61 53 16 10 3 19 100 100

The values are percentages, calculated against the total number of instances for each rig

132 Res Eng Design (2012) 23:125139

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the three dimensions is not particularly relevant for the

research as the questions primarily investigated the transfer

across rigs; hence, the higher number of these instances

reflected the nature of these questions.

From the second rig of the series, it emerged that 19% of

the instances described information addressed to multiple

dimensions. This implies that whilst the expected situation

was well defined, the actual management of information

defined less clearly how the information needed to be used.

This discrepancy between the data from the two sets of

interviews with regard to the undefined context of knowl-edge transfer, shown in Table5, suggests that the expected

knowledge flow that was described during the interviews

on the first rig did not take place in practice.

5.2.2 Initiation mechanisms and transfer strategies

The motivation for knowledge transfer was analysed by

investigating the initiation mechanisms, specifically whe-

ther knowledge was pulled, that is the transfer was driven

by a request for information from the receiver that actively

searched for it, or pushed, when the sender makes infor-

mation available before a specific need for it has arisen. A

third transfer mechanism was also identified: planned

transferdue to fixed meetings or standard reports, i.e. when

there is no specific need or request, but an organised pro-

cess to share knowledge is in place. Similar trends emerged

from the two sets of interviews. Table 6 shows that less

than 15% of the total instances on the transfer of knowl-

edge described transfer due to a planned procedure, i.e. a

planned meeting or a report. In both the rigs, around a

quarter of the transfer was pulled, whilst the majority ofcases (50%) were cases of pushing knowledge, with the

sender passing on knowledge without the receiver actively

requesting this knowledge. All the examples of planned

knowledge transfer were related to either the status of the

project within the current rig or lessons learnt which may

be relevant to the next three rigs. Other mechanisms that

initiated knowledge transfer included moving personnel

and symmetric unplanned sharing.

Pairing the analysis of the initiation mechanisms with

the adopted transfer strategies, codification and personali-

sation, provides a further understanding of the current

knowledge transfer process and therefore helps define therequirements for a knowledge management strategy that

answers the needs of practitioners. Pushing information

emerged to be the main initiation mechanism and occurred

though codified channels; however, information captured

into documentation and pushed into the repositories is not

necessarily reused at the receiver side. Whereas the

knowledge that is pulled, i.e. requested or actively sought,

identifies that there is a need for this knowledge and it is of

interest for the receiver.

Table7 provides an overview of how knowledge was

expected to be captured (from interviews on Rig 1) and was

actually captured (from interviews on Rig 2) in the three

dimensions, within rig, across rigs and across projects.

Table 5 Dimensions for knowledge transfer

Dimension of knowledge transfer Rig 1% Rig 2%

Across projects 16 10

Across rigs 60 53

Within rig 20 18

Not specified 3 19

Table 6 Initiation mechanisms for knowledge transfer that emerged from the two rigs where the interviews were conducted

Knowledge transfer Push Pull Planned Other Total

Rig1 Rig2 Rig1 Rig2 Rig1 Rig2 Rig1 Rig2 Rig1 Rig2

No of instances 31 58 18 25 7 15 6 15 62 113

Percentage 50 51 29 22 11 13 10 13 100 100


Table 7 Knowledge transfer strategies for the two rigs

Codification Personalisation Others Total

Rig1 Rig2 Rig1 Rig2 Rig1 Rig2 Rig1 Rig2

Within rig 12 4 6 4 3 2 21 10

Across rigs 28 16 15 35 17 3 60 54

Across projects 4 12 9 5 4 1 17 18

Others 0 13 0 5 2 1 2 19

Total 44 45 30 49 26 7 100 100


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This influences the transfer mechanisms that should be

adopted to support the process. Codification strategies can

be used to transfer only explicit knowledge, whist per-

sonalisation strategies are suitable for transferring also tacit

knowledge. Explicit knowledge that was transferred

through codification was available at the company in the

form of documents such as manuals, lessons learnt reports

and change reports, whilst tacit knowledge included directexperience of the personnel. The latter, together with

explicit knowledge that was not captured into documenta-

tion (e.g. knowledge acquired through communication

amongst colleagues, through meetings or personal net-

work), was transferred through personalisation strategies.

Table7 shows that 26% of instances from the first rig

that described the transfer of knowledge did not specify the

strategy that should have been adopted; this was particu-

larly evident for transfer across similar rigs. Additionally,

the first set of interviews indicated that knowledge transfer

across rigs was expected to occur through codification,

whilst data from Rig 2 showed the predominance of per-sonalisation. The interviews from Rig 1 indicated that

codification was expected to support knowledge transfer

within rig, whilst personal knowledge was more likely to

facilitate the transfer of knowledge across projects. How-

ever, the picture drawn from Rig 2 was different, codifi-

cation supported transfer across projects and was not

particularly utilised within a rigs life cycle. The distribu-

tion of the number of instances on knowledge transfer

across the three dimensions is not particularly relevant for

the research as the questions primarily investigated the

transfer across rigs; hence, the higher number of these

instances reflected the nature of these questions.

Differences emerged between expected and actual

knowledge transfer in relation to the dimensions (within

rig, across rigs and across projects) in which the transfer

took place and the strategy adopted. The picture that

emerged from the first set of interviews was quite defined

with respect to the context in which the knowledge shouldbe reused, i.e.across rigs, whilst the strategy was not clear.

Moving from the expected to the actual situation, the

strategies to adopt became more delineated; however, the

context in which the knowledge needed to be transferred

became more confused, since it was relevant in multiple

dimensions.

After having highlighted the main areas of interest

through the study described above, the characteristics of

knowledge transfer in the three dimensions were further

investigated through a more detailed analysis of the text of

the interviews. This analysis confirmed the connection

between the dimensions of knowledge transfer (within rig,across rigs or across projects) and the transfer mecha-

nisms. The results are described below and summarised in

Table8.

5.2.3 Knowledge transfer within a rig

Both the sets of interviews showed similar results regarding

the dimensions of knowledge transfer, whilst the methods

to transfer knowledge were somehow different. Moving

from the first to the second rig, the importance of training

Table 8 Knowledge transfer in the different dimensions in relation to the phase of the life cycle and the knowledge object

Within rig Across rigs Across projects

Design (Not investigated) Personalisation: same design and project

management teams (project, issues)

Personalisation: design and

project managers with long

history within the company

(project)

Codification: transfer of design solutions

(project, issues)

Codification: lessons learnt and

project documentation from

previous projects (project)

Installation and

commissioning

Personalisation: personal communication,

following construction (project, issues,product)

Personalisation: knowledge of other rigs

captured at the yard (issues, project,product)

Personalisation: personal

experience and communication(projects, product)

Codification: status reports, crew comments,

punch list, updated drawings, handover

procedures (project, issues, product)

Codification: reports from lessons learnt

meetings, crew comments, testing

procedures (project, issues, procedures)

Codification: commissioning

procedures, certificates

(product, procedures)

Operation Personalisation: training on new machines,

presence of operators during yard stay

(project, product)

Personalisation: experience and

communication (product, issues,

operation)

Personalisation: personal

experience and communication

(product, operation)

Codification: training, workshops,

procedures, manuals (procedures,

product)

Codification: record of comments from

the crew (issues)

Codification: safety alerts (issues)

134 Res Eng Design (2012) 23:125139

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on the equipment through simulation was reduced as the

knowledge of the drilling system was facilitated by drilling

operators visiting the first rig. Additionally, the methods

adopted for transferring knowledge were influenced by the

experience of the individuals. Novice and trainees tended

to rely upon IT systems and the company procedures,

whilst more experienced personnel tended to adopt less

formal and more proactive ways of transferring knowledge,for example by following the rig before they had any active

involvement.

5.2.4 Knowledge transfer across rigs (within a series)

Knowledge transfer mechanisms across rigs, which were

part of the same project, were influenced by the phase of

the life cycle in which the transfer occurred. These are

described below.

5.2.4.1 Design phase This phase was common for all the

rigs of the series and completed by a single design teamthat approached the four rigs as part of the same project.

Design solutions were transferred from one rig to the next

without changes.

5.2.4.2 Installation and commissioning This phase took

place at the same shipyard for all the four rigs with

6-month delays between the rigs, hence facilitating the

exchange of information due to physical proximity and the

transfer of personnel across rigs. In the installation phase,

knowledge was transferred across rigs through different

channels, for instance:

Support teams were based at the yard to coordinate the

transfer of knowledge across rigs and facilitate the

handover from design to operation.

Personal contact occurred between the different crews

due to the proximity of the rigs.

Crews were moved across rigs in order to provide

support in critical phases.

Documentation on issues arising during installation and

commissioning was transferred from the first rig to the

next.

Lessons learnt programs were set up both internally,

after 90 days of operation, and externally with thirdparties, at a later date.

Workshops were organised to transfer start up problems

to next rigs.

Comments from the crew and the client were captured,

evaluated by the project manager and transferred across

rigs if considered relevant.

The two sets of interviews showed differences in the

expected transfer mechanisms and in the actual ones.

Particularly, knowledge transfer was expected to take place

through lessons learnt meetings and moving the operational

crew from the first to the second rig; however, this did not

take place. Transfer occurred through personalisation due

to the physical proximity of the rigs that facilitated infor-

mal communication between crews and as a result of the

temporary allocation of the crew assigned on the second rig

to the first one. This temporary allocation of the crews had

the objective to provide support in critical stages and at thesame time allow the crew to gain further experience on the

equipment.

During installation and commissioning, time and cost

constraints limited the implementation of improvements

and changes across rigs. This resulted in rig personnel

being sceptical towards planned procedures for transferring

knowledge across rigs and preferring to postpone inter-

ventions that did not involve safety issues to the operation

phase.

5.2.4.3 Operation The rigs operated in different areas,

hence resulting in a reduction in the knowledge transferacross the two rigs, particularly through personalisation.

No evidence of operational experience pushed through

codification mechanisms across rigs emerged from the

interviews.

Operational experience was gained by the drilling crew

of the second rig by visiting the first rig whilst in

operation.

Communication across rigs was based on personal

initiative.

No systematic transfer of operational experience across

rigs or to engineering designers occurred. No transfer of operational procedures was observed.

Although the drilling systems were identical, personnel

from the second rig preferred to write their own

procedures rather than reuse those from the first rig.

The separation between the different phases was mir-

rored in the knowledge transfer program organised by the

company; separate lessons learnt meetings were set up at

the end of each phase until the end of the warranty period.

When knowledge transfer across rigs occurred, it took

place amongst people involved in the same phase of the life

cycle and usually covering the same role in different rigs.

No initiatives were planned in order to capture the

knowledge generated throughout a rigs life cycle once the

warranty period was concluded, as after the end of this

period information from service could not be used for any

formal claim against the suppliers.

5.2.5 Knowledge transfer across projects

The transfer of knowledge across projects could take place

in two directions, each of these are discussed below:

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Capture of knowledge with the purpose to reuse it in

future projects;

Reuse of knowledge from past projects.

A high portion of the knowledge generated from a rig

was expected to be reused in future projects, as the design

of the rigs was not meant to be changed between the first

and the other rigs or the series, with the exclusion ofchanges that needed to be implemented to correct faults

compromising safety on board. However, this knowledge

was part of the standard project documentation, and no

effort was made to structure it in a way to facilitate its

retrieval and reuse in the future.

The knowledge that was reused from past projects dur-

ing the development of the analysed series of rigs was

personal experience, particularly of members of the design

and the project management team. Experience of the

operators was not used during the design of new rigs. As a

result, issues regarding reliability, maintenance and oper-

ation were common to the current and the previous projectsand, as in the case of the transfer of knowledge across rigs,

transfer was more likely to occur through personalisation

mechanisms and to be confined to people involved in the

same phase of the life cycle.

Table8 summarises the main findings described here

and couples each phase of the rig life cycle and each

dimension of knowledge transfer with the relevant types of

knowledge. Differences emerged between the knowledge

that is significant in operation compared to that which is

relevant during design and commissioning. After a rig

enters into operation, project information is no longer rel-

evant, whilst information about past operational processesis more relevant for reuse, particularly to create operational

procedures to share within the series of rigs.

6 Discussion and implications

The findings from the analysis of the case study are of

interest for both industry and academia. The implications

of the research for these two domains are discussed in the

following sections.

6.1 Industry: implementation of knowledgemanagement strategies

The case study described in this paper investigated

knowledge transfer in an engineering context, particularly

in complex customised products as oil rigs.

Two sets of interviews were carried out. The first set

indicated that the transfer of knowledge across similar rigs

was expected to take place following a codified approach;

however, the subsequent set of interviews showed that the

actual flow of information across rigs tended to follow

personal channels. Various factors can explain the dis-

crepancies between expected and actual transfer mecha-

nisms; some of them are strictly related to the specific case,

e.g. the limited time between the deliveries of the rigs that

narrowed the possibility of implementing changes from

one rig to the next, whilst others are of general relevance

for industry, particularly:

Knowledge management strategies were not addressed

to the specific dimensions for knowledge transfer, for

example the same type of documentation was expected

to be used both to track the progressions of the

construction of a rig and to notify changes to future

rigs. Hence, practitioners could not distinguish between

documents that were relevant only in the short-term and

other addressing a longer-term perspective.

Knowledge generated in the later phases of a rigs life

cycle, particularly from operation, was still embedded

into people as no specific strategy was adopted tocapture knowledge from these phases. Hence, this

knowledge was difficult to transfer and reuse.

Changes to the design were implemented across rigs

solely if motivated by safety issues: this limited the

benefits of the transfer of knowledge within the project

and reduced the motivation of personnel to follow the

procedure for capturinginformation on possible improve-

ments. This suggested the difficulty in motivating the

personnel to record issues that are of a longer-term

benefit, i.e. to be implemented in the next generation of

products, where they may not necessarily see the benefits.

Specific tools were adopted for capturing knowledgefrom each phase of the life cycle, making it difficult to

obtain an exhaustive overview of a project through

documentation. This resulted in people referring back

to lessons learnt by memory (if they had been directly

involved in their definition) and not looking for

information available in knowledge repositories.

An explicit description of the purpose of each knowl-

edge management tool aiming to support the transfer of

knowledge at the different phases of the product life cycle

would resolve ambiguity and help capture neglected types

of knowledge. For instance, the companys knowledge

transfer strategy did not include operational knowledge.

This may be explained by the difficulties in managing

knowledge about operational processes; the available

knowledge was linked to the products and knowledge

repositories were not designed to effectively capture pro-

cess knowledge. Improvement in managing process

knowledge would lead to various advantages, such as:

The transfer of process knowledge (e.g. on how to

operate the drilling equipment, perform maintenance or

136 Res Eng Design (2012) 23:125139

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trouble shooting) can be implemented at any phase of

the rig life cycle without requiring a high budget,

contrary to the implementation of other types of

knowledge. The costs related to the implementation

of changes to a product, for example, increase in a

factor of about 10 at each stage of the life cycle (Carter

and Baker1992).

Mapping process knowledge could lead to the optimi-sation of the process itself with advantages in terms of

both time and costs.

The current situation emerging from the interviews

showed that operational procedures were determined by the

personnel on the rig and differed across rigs. The definition

of operational procedures that are standardised at organi-

sational level could reduce the time requested to define

procedures for each rig and at the same time lead to the

development of a shared operational practice within the

organisation.

The case study illustrated in this paper represents acustomised industry that was attempting to reuse design

and service knowledge across rigs to achieve advantages

that include the following: (1) reducing design costs (and

reducing costs in general), (2) detecting faults in the first

rig and correcting them in the subsequent ones and (3)

improving operational practices by sending personnel with

experience from one rig onboard the others. The transfer of

knowledge across rigs of the same series was analysed and

compared to the transfer within the life cycle of one rig and

to the transfer across rigs with different characteristics. The

study identified the limitations of the current knowledge

management strategy, e.g. lack of definition of the contextwhen knowledge is expected to be reused, and proposed the

factors that should be taken into account whilst designing a

strategy aiming to systematically transfer knowledge in the

different dimensions.

6.2 Research: knowledge from later phases of the life

cycle

This research focused upon knowledge from the later

phases of product life cycle, i.e. installation, commission-

ing and operation. This knowledge differs from knowledge

generated during the design phase due to its dynamic nat-

ure and strict connection to the context in which it is

generated. These characteristics pose a barrier to both the

capture and the reuse of life cycle knowledge due to dif-

ficulties in following its development over time and sepa-

rating the knowledge of general value from the contingent

knowledge that is relevant only in that one specific case.

Knowledge about processes, e.g. how to operate the

equipment, perform maintenance or detect a failure and its

cause, is particularly important in the latter phases of a

products life cycle. This type of knowledge has many

characteristics in common with the knowledge associated

with the design process (Wallace et al. 2005). Both design

and operational activities can be seen as decision-making

processes starting with the knowledge of the task to fulfil

and resulting in a solution generated by using available

knowledge and personal expertise.

Both design and operation would benefit from the reuseof process knowledge as it supports for the decision-mak-

ing process by identifying the steps to undertake and how

to tackle tasks; however, difficulties in embedding process

knowledge into IT systems represent a barrier for its reuse

(Wallace et al. 2005).

To facilitate the systematic reuse of knowledge from the

later phases of the life cycle in different contexts, two

strategies could be adopted. The first strategy regards

translating dynamic knowledge from installation and

operation into more static forms, e.g. systematically linking

the processes to their effects on products and making the

knowledge of broader interest i.e. relevant beyond thecontext in which it was originally generated (Fig. 3). This

strategy would support the reuse of codified information

from the later phases of the life cycle during the develop-

ment of the next generation of products and ensure engi-

neering designers could readily access the knowledge.

The second possible strategy focuses upon understand-

ing which transfer mechanisms are suitable to transfer

knowledge from the later phases of product life cycle

across projects at the same phase, e.g. transfer service

knowledge both across rigs and across projects. The choice

between personalisation and codification strategies is

influenced by the characteristics of the knowledge to be

transferred, the type of organisation and the business.

This study showed that transfer of knowledge from

installation and commissioning does not always occur

according to the planned strategies, specifically knowledge

that is supposed to be transferred through codification

strategies was transferred through personalisation. Mecha-

nisms commonly used to capture knowledge in the design

phase, e.g. project reviews in correspondence to the gates

of the development process, were expected to be extended

throughout the life cycle of the rig, but the difficulties in

implementing changes due to cost and time constraints

undermined the reuse of this knowledge across rigs part of

the same series. This elicits the need for further

PHASES: Installation,

Commissioning, Operation

KNOWLEDGE: Project,

Changes, Issues, Processes

PHASE: Design

KNOWLEDGE:

Product

Translation

Fig. 3 Translation process

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understanding of how to design a knowledge management

system suitable for the specific context where it has to be

applied.

The research presented in this paper suggests that the

mechanisms used for transferring knowledge and the types

of knowledge that are relevant to be transferred are influ-

enced by the dimensions in which knowledge is trans-

ferred; however, these findings derive from a single casestudy. Conducting further research in industries with dif-

ferent characteristics is required to verify whether the

findings presented in this paper are valid in other contexts.

7 Conclusions

This paper explored the transfer of knowledge in complex

customised equipment through a case study of a series of

four oil rigs for offshore drilling and focused specifically

upon the knowledge generated in the later phases of the

rigs life cycle.Two sets of interviews were carried out during the

installation and commissioning phase of the first and sec-

ond rigs of the series. The expected knowledge transfer

mechanisms from the interviews on the first rig and the

actual situation emerging from the second rig were

investigated.

The comparison between the actual transfer of knowl-

edge and the expected situation that the flow of knowledge

towards the different dimensions (within rig, across rigs,

across project) was less clear that expected. The finding

that almost 20% of the coded instances were addressed to

multiple dimensions indicates ambiguity on when captured

knowledge is meant to be reused.

The transfer of knowledge primarily occurred within

anyone phase, e.g. within design, installation or operation,

with very poor transfer of knowledge across phases, par-

ticularly when codification mechanisms were involved.

Additionally, a number of knowledge repositories were set

up with the aim to capture the companys internal knowl-

edge, resulting in information stored in different forms and

scattered throughout various repositories. These difficulties

in retrieving and reusing information resulted in personal-

isation strategies still being the most used and effective

way to transfer knowledge.

The attempts to support the transfer of knowledge

appeared to neglect knowledge generated during the

operation of the rig, particularly after the conclusion of the

warranty period. The reuse of operational knowledge was

not only missing during the design phase; also, the opera-

tion phase was characterised by poor communication both

across rigs that were part of the same project and across

projects. The result was the creation of procedures specific

for each rig, rather than reusing procedures. Knowledge

generated in the operation phase was only captured in a

codified manner in the case of issues, whilst knowledge

related to the products and the operational processes was

transferred through personalisation strategies. This indi-

cates a mismatch between the information made available

and the information actually needed. Hence, successful

codification strategies to support transfer of knowledge

of the product in operation should be related not only toissues but also to the specific product and the operational

processes.

The case study investigated in this paper regarded a

customised industry that was moving towards the produc-

tion of small series of products in order to be able to reuse

the products design and the knowledge generated

throughout its life cycle and achieve financial advantages.

In the case of the development of customised products only

two dimensions are relevant for knowledge transfer: within

the life cycle of the product and across different products.

With the introduction of a series of similar products, the

transfer knowledge can take place in a third dimension, i.e.within similar products of the same series. This suggest the

direction for further research, aiming to understand the link

between each dimension, the type of knowledge to be

transferred and the mechanisms that better support this

transfer in industries with different characteristics.

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