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Examining the Implications of Knowledge Boundaries
for a Large-Scale Agile Transformation Initiative
of a Manufacturing Company
Silvia Orejuela
*
, Glenn Johansson
†
and Damien Motte
‡
Department of Design Sciences, Lund University, P. O. Box 118
Lund, SE-221 00, Sweden
*
silvia.orejuela@design.lth.se
†
glenn.johansson@design.lth.se
‡
damien.motte@design.lth.se
Received 6 October 2023
Revised 5 February 2024
Accepted 11 March 2024
Published 22 May 2024
To stay competitive in today's environment, characterized by changing customer requirements,
digitalization, new technologies, etc., companies must deliver fast and continuous innovation.
Manufacturing companies have therefore started to launch large-scale agile transformation
initiatives. A speci¯city of manufacturing companies is their need for deeply specialized organi-
zational units. Knowledge boundaries resulting from knowledge specialization tend to impact
transformation initiatives.Therefore, this work examinesthe implications of knowledgeboundaries
between organizational units for a large-scale agile transformation initiative of a manufacturing
company. The ¯ndings show that these knowledge boundaries imply a need for knowledge inte-
gration based on °exibility and dynamism as key aspects. A conceptual modelthat illustrates these
aspects during the initial phase of implementation of these transformation initiatives is presented.
Keywords: Agile implementation; organizational transformation; knowledge boundaries;
knowledge integration.
1. Introduction
With changing customer behaviors, increasing digitalization, and the emergence of
new technologies, companies need to deliver innovation quickly and continuously to
stay competitive [Blais (2023); Denning (2019); Reischl et al. (2022)]. To this end,
they launch organizational transformation initiatives, such as the implementation of
Total Quality Management (TQM) [Marion et al. (2022)], Lean [Gudem et al.
(2014); Yordanova (2018)], and Industry 4.0 [Nayernia et al. (2022)]. One initiative
that is gaining interest among companies is large-scale agile transformation because
*
Corresponding author.
This is an Open Access article published by World Scienti¯c Publishing Company. It is distributed under
the terms of the Creative Commons Attribution 4.0 (CC BY) License which permits use, distribution and
reproduction in any medium, provided the original work is properly cited.
OPEN ACCESS
International Journal of Innovation and Technology Management
Vol. 21, No. 5 (2024) 2450039 (25 pages)
#
.
cThe Author(s)
DOI: 10.1142/S0219877024500391
2450039-1
it supports °exibility and quick adjustments in uncertain business environments
[Kasauli et al. (2020); Rigby et al. (2018); Uludağet al. (2019)]. Large-scale
agile transformation refers to the process of reorganizing strategy, structure, people,
technology, tools, processes, etc. to adopt, implement, and use agile frameworks and
practices across an organization [Pawlak (2021); Strode et al. (2022)].
Large-scale agile transformations rely on agile frameworks and practices that
were originally introduced to achieve software development e±ciency and quality.
Due to proven bene¯ts in software development [Digital.ai (2022)], agile frameworks
and practices have begun to be used in manufacturing companies [Edwards et al.
(2019); Ovesen (2012)]. Still, few studies have explored this phenomenon; examples
are the studies on the LEGO Group [Sommer (2019)], Saab Aeronautics [Lindl€
of and
Furuhjelm (2018)] and the multi-case studies conducted by Eklund and Berger
[2017] and Kasauli et al. [2020].
Nevertheless, the development, manufacturing, and delivery of physical products,
which characterize manufacturing companies, involve multiple interdependent
technologies [Eklund and Berger (2017); Walrave et al. (2022)] and di®erent highly
specialized organizational units [Beretta and Smith (2023); Kasauli et al. (2020);
S€
afsten et al. (2014)]. Knowledge boundaries resulting from specialization tend to
impact the implementation of organizational initiatives [Grant (1996)]; therefore,
they may also a®ect the implementation of large-scale agile transformation initia-
tives in manufacturing companies.
While studies that address the software development context have conceptualized
large-scale agile transformation initiatives in terms of the complexity of working
with various knowledge boundaries across actors, technologies, and processes in-
volved [cf. Rolland (2016); Rolland et al. (2016)], the implications of knowledge
boundaries for the implementation of large-scale agile transformation initiatives in
manufacturing companies have been scarcely addressed.
The purpose of this study is therefore to examine the implications of knowledge
boundaries between organizational units in the initial phase of the implementation of
a large-scale agile transformation initiative in a manufacturing company. The study
focuses on the initial phase of the implementation of this initiative because it is
critical to its success [Kotter (1995)].
This exploratory study relies on a single case study of a large-scale agile trans-
formation initiative in a manufacturing company. It focuses on three of its organi-
zational units: Production, Research and Development (R&D), and Information
Technology (IT). The study consists of two steps. In the ¯rst step, the study compares
the di®erent organizational units' knowledge of agile and shows how the di®erences
result in knowledge boundaries. In the second step, the study examines the implica-
tions of knowledge boundaries for the implementation of a large-scale agile trans-
formation initiative. The study shows that the existence of knowledge boundaries
between organizational units implies a need to consider °exibility and dynamism in
the implementation of large-scale agile transformation initiatives. By using the
notions of acting and interacting [cf. Enberg (2007)], the paper presents a conceptual
model that illus trates how °exibility and dynamism are essential a spects to consider in
the initial phase of implementing such initiatives in manufacturing companies.
S. Orejuela, G. Johansson & D. Motte
2450039-2
The remainder of this paper is organized as follows. Section 2the literature on
agile, large-scale agile transformation in manufacturing companies, knowledge
boundaries, and knowledge integration is reviewed. Section 3describes the research
method followed in this study. Section 4presents the ¯ndings about the di®erent
organizational units' knowledge of agile. Section 5discusses the implications of
knowledge boundaries for the implementation of large-scale agile transformation
initiatives. A conceptual model illustrating these implications is then presented.
Section 6concludes this paper by presenting its contributions to the literature and
practice, the limitations of this study, and directions for future research.
2. Literature Background
2.1. Origin and basics of agile
Agile is de¯ned by Agile Alliance [2023] as the ability to create and respond to change
as well as to deal with uncertain environments. In software development, agile is
related to the values and principles expressed in the Agile Software Development
Manifesto [Beck et al. (2001)]. These values and principles are the constituents of a
mindset that provides guidance in a turbulent environment [Agile Alliance (2023)].
Based on these values and principles, several frameworks have been created that
focus on single, small, self-organizing, cross-functional teams (e.g. Scrum, Extreme
Programming, and Dynamic Systems Development Method) [Edwards et al. (2019)].
These frameworks outline practices (e.g. incremental delivery, continuous integration)
that seek to support e±cient and e®ective software development [Beck et al. (2001);
BirgünandÇerkezoğlu (2019); Tura et al. (2017)]. Nevertheless, attention is now
turning to frameworks and practices that support coordination among multiple teams
and are implemented beyond software development. Practitioners, consulting groups,
and researchers o®er large-scale agile frameworks and practices; some examples are the
Scaled Agile Framework (SAFe) [Scaled Agile (2022)], Scrum@Scale [Sutherland and
Scrum Inc (2022)], and Large-Scale Scrum (LeSS) [The LeSS Company (2014)]. Agile
has thus become an umbrella term for several frameworks and practices based on the
values and principles expressed in the Agile Software Development Manifesto.
The bene¯ts of agile software development include better collaboration, better
alignment with business needs, and a better working environment [Digital.ai (2022)].
In search of these bene¯ts, agile frameworks and practices have been applied to gain
improvements in areas beyond software development [Gonzalez (2014); Reischl et al.
(2022); Rigby et al. (2018)]. For instance, in manufacturing companies, agile fra-
meworks and practices are starting to be used for the commercialization of new
technologies [Tura et al. (2017)] or the development of physical products [Drutchas
and Eppinger (2023); Edwards et al. (2019); Eklund and Berger (2017); Lindl€
ofand
Furuhjelm (2018)].
2.2. Large-scale agile transformation in manufacturing companies
With the aim of implementing agile beyond software development or in several
teams, companies launch large-scale agile transformation initiatives. The term
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-3
large-scale agile describes the implementation of agile frameworks and practices in
large teams or in extensive projects involving multiple teams or the use of such
frameworks and practices throughout the organization [Dingsøyr and Moe (2014);
Uludağet al. (2019)]. The term transformation refers to the transition from tradi-
tional ways of working to the use of agile frameworks and practices [Pawlak (2021)].
According to Pawlak [2021], large-scale agile transformations can take the form of
a one-time shift or a gradual shift based on scaling pilots across the organization.
The survey conducted by Schmidt et al. [2019] provides insights into the di®usion
progress of agile implementation in manufacturing companies: while 42% of the
surveyed companies had conducted pilots, only 2.2% had completed the roll-out
throughout the organization.
Large-scale agile transformation in manufacturing companies has been studied
with di®erent purposes and through di®erent research methods, such as surveys and
case studies. For instance, Schmidt et al. [2018] conducted a survey that aimed at
studying the implementation of agile in hardware development.
a
The authors
identi¯ed motivations, actual improvements, and challenges in the applicability of
agile to hardware development. There were 228 respondents to the survey, most of
them working in large manufacturing companies. In a subsequent survey, Schmidt
et al. [2019] studied in°uencing factors, the e®ects of agile on hardware development,
and changes in the perception of agile over the course of an implementation. Survey
responses were received from 187 agile practitioners, most of them in large
manufacturing companies. More recently, Michalides et al. [2023] conducted an
empirical study focused on identifying challenges to large-scale agile in physical
products. The study included data from a survey sent to 128 experienced partici-
pants and a literature review.
Research has also been based on single and multiple case studies. Examples of
single case studies include the study by Sommer [2019] that described the orches-
tration of a large-scale agile transformation in the LEGO Group, a large toy man-
ufacturer. The transformation initiative involved changes in the company's
organizational structure, IT and business interaction, roles and responsibilities, and
budgeting and control. Similarly, Beretta and Smith [2023] presented a longitudinal
study of an agile implementation in a large manufacturing company taking bottom-
up (teams' adaptations of agile frameworks) and top-down (control of agile imple-
mentation using rules, procedures, and processes in how agile should be applied)
approaches in the transformation initiative. Moreover, Lindl€
of and Furuhjelm [2018]
presented a case study from Saab Aeronautics, a large manufacturer in the security
and defense business. The case involved the development of a Saab ¯ghter jet, a
project that involved around 200 engineers in hardware and software development.
The authors found that two factors were important in enabling agile bene¯ts to be
gained in large organizations: allowing focused teamwork and giving teams an
empowered role in planning. Drutchas and Eppinger [2023] also studied the hard-
ware and software development of robots in Ocado Technology, a leading online
a
The terms \hardware development" and \development of physical products" are used interchangeably to
refer to the development of products that bear a physical nature [Schmidt et al. (2019)].
S. Orejuela, G. Johansson & D. Motte
2450039-4
grocery. The authors presented and discussed agile adjustments (i.e. problem-based
decomposition and the use of ad-hoc teams) for the development of mechatronic
products. Another single case study was presented by Uludağet al. [2019], who
studied the adoption and application of LeSS in a large automobile manufacturer.
The authors found that transparency, training, and workshops ease the adoption of
agile and that additional roles and processes facilitate the exchange of shared
knowledge between product teams.
Multiple case studies were conducted by Berger and Eklund [2015] and Kasauli
et al. [2020]. Based on three manufacturing companies in the Nordic Region, Berger
and Eklund [2015] identi¯ed expectations and challenges from scaling agile outside
software development teams. One of the identi¯ed expectations is faster time
to market, while the challenges include in°exible test environments and existing
organizational structures and mindsets. Moreover, based on four manufacturing
companies, Kasauli et al. [2020] studied the challenge of coordinating agile teams
(mainly individual teams but also groups of teams and organizations) in non-agile
contexts. The authors found that the agile teams, with their specialized methods and
practices, get isolated from the non-agile teams and that knowledge sharing needs to
be well managed for an e±cient collaboration. They also presented a catalog of types
of boundary objects (that is, artifacts such as requirements list, plans or other
documents) that facilitate the coordination between the di®erent teams.
Several scholars have a±rmed that large-scale agile transformation is challenging
[Eklund and Berger (2017); Michalides et al. (2023)]. One of the main challenges
relates to the di®erent interpretations or understandings of agile of those involved in
the transformation initiatives. Studies have found that this challenge a®ects col-
laboration at the interfaces of di®erent organizational units, causing frustration,
hindering teams in their search for the best way of working, and thus jeopardizing
the successful implementation of the transformation initiatives [Beretta and Smith
(2023); Michalides et al. (2023); Uludağet al. (2019)]. Eklund and Berger [2017]
observed that, out of 21 identi¯ed challenges, understanding agile along the value
chain is the third most important in scaling agile in manufacturing companies.
Similarly, Michalides et al. [2023] found understanding of agile values and principles
to be one of the challenges in large-scale agile in the development of physical pro-
ducts and that the existing literature contains few studies addressing this challenge.
Beretta and Smith [2023] observed that granting teams the freedom to implement
agile frameworks on their own results in variations in agile understanding because
teams' legacy models and ways of working in°uence their understandings of agile.
Schmidt et al. [2018] identi¯ed that, because of the immaturity of the application of
agile in physical product development, it is subject to di®erent understandings
according to whom is questioned. Moreover, Schmidt et al. [2019] found that there is
a high chance that there will be di®erent understandings of agile among practitioners
when it is scaled in manufacturing companies.
Moreover, the literature addressing large-scale agile transformation in manufactur-
ing companies suggests that establishing agile values and principles is a proper starting
point for the implementation of these transformation initiatives. Berger and Eklund
[2015] found that changing the overall mindset in the organization should be the ¯rst
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-5
step toward scaling agile outside of software development teams. Similarly, Sommer
[2019] suggested that implementing agile practices without changing mindsets and
behaviors should be avoided. The author claimed that in implementing agile processes
and tools without changing behaviors and mindsets, organizations end up \doing Agile
without being Agile" (p. 28, emphasis in original), in other words, a shallow transfor-
mation initiative.
Furthermore, authors of studies of large-scale agile transformation in manufactur-
ing companies assert that transformation initiatives are unique, and therefore there
is no \textbook" implementation of them. Instead, these initiatives must be adapted
to ¯t the context of each organization [Beretta and Smith (2023); Drutchas and
Eppinger (2023); Lindl€
of and Furuhjelm (2018); Sommer (2019); Uludağet al. (2019)].
Still, the literature documenting experiences of large-scale agile transformations in
manufacturing companies is scarce. Studies that explore the experiences of other
manufacturing companies can provide further insights into the phenomenon and serve
as inspiration for companies striving for large-scale agile transformation [Drutchas and
Eppinger (2023); Lindl€
of and Furuhjelm (2018); Sommer (2019); Uludağet al. (2019)].
2.3. Knowledge boundaries and knowledge integration
Knowledge boundaries are the result of the knowledge specialization that leads to
shared knowledge frames in epistemic communities [Tell (2016)]. Epistemic com-
munities are de¯ned by a shared role orientation and are found, for example, in
organizational units, professions, occupations, and engineering disciplines [Tell
(2016)]. Epistemic communities (also referred to as subsystems by Lawrence and
Lorsch [1967]) develop speci¯c attributes (i.e. cognitive orientations, systems of
meaning, and thought worlds) to meet the requirements of their sub-environments
[Dougherty (1992); Lawrence and Lorsch (1967)]. As a result, epistemic communities
focus on di®erent aspects of knowledge and ¯lter, interpret, and understand the same
information in di®erent ways, leading to knowledge boundaries that limit how far
they can gain a comprehensive understanding of issues [Dougherty (1992)].
Authors such as Tell [2016] and Carlile [2004] have described di®erent types of
knowledge boundaries. Tell [2016] introduced ¯ve types of knowledge boundaries,
namely, individual, domain-speci¯c, task-oriented, temporal, and spatial. Individual
knowledge boundaries are characterized by the tacit knowledge elements that
individuals use to make sense of the world. Domain-speci¯c knowledge boundaries
refer to the knowledge that results from experiential learning through interactions
within an epistemic community. Task-oriented knowledge boundaries refer to the
organization and task execution capabilities of an epistemic community. Spatial
knowledge boundaries result from local context and conditions, including language,
culture, and traditions. Finally, temporal knowledge boundaries result from the time
and sequence in which knowledge is applied.
Carlile [2004] presented a framework that includes three types of knowledge
boundaries: syntactic, semantic, and pragmatic. Syntactic boundaries arise when the
common lexicon is insu±cient to share and assess knowledge across epistemic
communities; semantic boundaries arise when novel circumstances or knowledge
S. Orejuela, G. Johansson & D. Motte
2450039-6
generate di®erent interpretations or meanings across epistemic communities; and
pragmatic boundaries arise when novel circumstances or knowledge generate dif-
ferent interests across epistemic communities, thus creating the need for negotiation
to share and assess knowledge across them. The framework supports an iterative
approach to developing, sharing, and assessing knowledge between epistemic com-
munities [Carlile (2004)].
Knowledge boundaries pose a critical challenge for organizations [Carlile (2002)],
as they create a need for knowledge integration across boundaries [Kasauli et al.
(2020); Tell (2016)]. Knowledge integration is de¯ned by Huang [2000] as \an on-
going collective process of constructing, articulating and rede¯ning shared belief
through the social interaction of organisational members" (p. 15). As knowledge
constitutes a strategically important resource of companies, knowledge integration is
emphasized as an essential capability of an organization [Grant (1996)]. Therefore,
the importance of knowledge integration to an organization's competitiveness is
widely recognized [Huang and Newell (2003); Tell (2016)].
Acknowledging the importance of knowledge integration in an organization,
several authors have proposed di®erent integration mechanisms. Examples are an
organizational structure that facilitates the sharing of codes and narratives and
minimizes the need for communication between di®erent subsystems [Grant (1996);
Huang and Newell (2003)]; the development, maintenance, and nurturing of social
capital [Huang and Newell (2003)]; formal (e.g. participatory decision-making) and
informal (e.g. informal communication) integrative practices [Patnayakuni et al.
(2007)]; shared knowledge and sophisticated signaling systems developed by orga-
nizational members [Grant (1996)]; fostering generative learning through the con-
tinuous evaluation of initiatives [Huang and Newell (2003)]; interdisciplinary
accountability for activities [Dougherty (1992)]; the codi¯cation of knowledge into
explicit rules, standard procedures, visual or verbal representations, etc., that em-
body the knowledge of multiple specialists [Grant (1996); Kasauli et al. (2020);
Majchrzak et al. (2012); Tell (2016)]; boundary objects, such as prototypes or
drawings [Carlile (2004); Kasauli et al. (2020); Tell (2016)]; and organizational
routines that include sequential patterns of interaction, working arrangements, etc.
that minimize the need for knowledge communication [Grant (1996); Kasauli et al.
(2020); Tell (2016)]. Tell [2016] proposed 15 integration mechanisms including
analogy (e.g. comparisons between the base and target knowledge domains), en-
rolment (e.g. hiring or recruiting people from di®erent knowledge domains), social-
ization (e.g. mimicking behaviors), and dialogue (e.g. using communication
platforms). Finally, Huang and Newell [2003] found that knowledge integration is
facilitated by prior experience of organization-wide initiatives (e.g. the implemen-
tation of TQM or a common IT platform).
These integration mechanisms are considered holistically in the iterative model of
knowledge integration proposed by Enberg [2007]. The model is based on notions of
interacting, which evolves around collective activities, for example, collective sense-
making sessions and problem-solving meetings, and acting, which draws on instances
of individual work, such as individual and idiosyncratic routines. As a result of
interacting-acting iterations, members can establish a representation of the whole
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-7
that guides them in their instances of individual work. The interacting notion could
be related to Carlile's [2004] iterative approach mentioned earlier.
Among the reviewed studies on large-scale agile transformations in manufactur-
ing companies, only Kasauli et al. [2020] addressed the challenge of coordination and
collaboration in such a context, exploring knowledge boundaries between co-existing
agile and non-agile teams and proposing boundary objects as integration mechan-
isms. However, the authors' study focused on a mixed environment (with some
teams having adopted agile frameworks and practices and others continuing with
legacy Stage-Gate or Waterfall models) while this study addresses the implications
of knowledge boundaries in the initial phase of implementation of a transformation
process of organizational units moving from the use of legacy models to the use of
agile frameworks and practices.
The literature on large-scale agile transformations in manufacturing companies
shows that one of the main challenges relates to di®erent interpretations or under-
standings of agile among those involved in the transformation initiatives. Despite its
relevance, this phenomenon remains underexplored. For this study, knowledge
boundaries and knowledge integration are used as a theoretical lens for the explo-
ration of large-scale agile transformation initiatives in manufacturing companies. On
the one hand, knowledge boundaries serve to conceptualize di®erences in organiza-
tional units' knowledge about agile; on the other hand, knowledge integration helps
to examine and deal with the implications of knowledge boundaries for these
transformation initiatives.
3. Research Method
3.1. Study design and empirical setting
A single case study was chosen as the study design because limited insights exist
about the implications of knowledge boundaries between organizational units in
large-scale agile transformation initiatives in manufacturing companies. Such a
study design allows for an in-depth examination of the phenomenon through an
exhaustive and comprehensive analysis of a single setting, thus yielding detailed
insights [Eisenhardt (1989); Eisenhardt and Graebner (2007); Siggelkow (2007);
Voss et al. (2002); Yin (2018)]. Single case studies have been used in other studies [cf.
Beretta and Smith (2023); Drutchas and Eppinger (2023); Lindl€
of and Furuhjelm
(2018); Sommer (2019); Uludağet al. (2019)], but none of these studies has specif-
ically addressed the implications of knowledge boundaries between organizational
units in large-scale agile transformation initiatives.
The case context is a typical large manufacturing company organized based on
a hierarchical organizational structure with several organizational units, each of
which works in a specialized knowledge domain (Production, R&D, IT, Marketing,
Sales, etc.). It has approximately 8,000 employees located in more than 100 countries
and has centers in the Americas, Europe, and Asia. It develops, manufactures,
and delivers physical products with associated services to a variety of industrial
segments, including oil and gas, automotive, aerospace, medical, and energy.
S. Orejuela, G. Johansson & D. Motte
2450039-8
A summary of the company's pro¯le description is presented in Table 1. Its extensive
investment in R&D and manufacturing technologies, together with its expertise,
allows the company to be a frontrunner in innovation, introducing several products
to the market each year.
As presented in Table 2, the case itself is a large-scale agile transformation ini-
tiative. It was selected based on a theoretical sampling logic to extend the existing
literature on large-scale agile transformation initiatives in manufacturing companies
[Eisenhardt (1989); Tsang (2014); Yin (2018)]. The selected case has typical char-
acteristics [Priya (2021); Siggelkow (2007); Yin (2018)] associated with large-scale
agile transformation initiatives: ¯rst, the company's motivation for its implemen-
tation, that is, to improve the collaboration and alignment between the IT and other
organizational units [cf. Barroca et al. (2019); Schmidt et al. (2019); Sommer (2019);
Uludağet al. (2019)]; second, its use of a stepwise approach for the implementation
of the initiative [cf. Beretta and Smith (2023); Brosseau et al. (2019)]; and third, IT's
previous experience of the use of agile frameworks and practices [cf. Schmidt et al.
(2019)].
The company has traditionally worked with Stage-Gate or Waterfall models and
practices. Nevertheless, to adapt to the rapid pace of change and increasing digi-
talization, the company's top management decided to launch a large-scale agile
transformation initiative. It was decided that the IT organizational unit should take
the lead in the transformation initiative, as it already had experience with agile
frameworks and practices. The initiative was intended to be implemented based on a
stepwise approach, one organizational unit at a time. When the study presented in
this paper was conducted, the implementation had started in R&D and was planned
to be extended to other organizational units, including Production. These organi-
zational units, namely, Production, R&D and IT, were considered in the study.
Production and R&D were considered due to their crucial roles in the development
and manufacturing of the products o®ered by the company (Production is the
company's largest organizational unit). IT was considered due to its leadership role
in the transformation initiative and experience of working with agile frameworks and
practices.
Table 1. Company's pro¯le description.
No. organizational units 9
No. employees Approx. 8,000
R&D and manufacturing centers Globally distributed
O®ering Products and services
Customer industrial segments Oil and gas, automotive, aerospace, medical, and energy,
among others
Table 2. Case study design.
Case Large-scale agile transformation initiative
Context Large manufacturing company
Unit of analysis Organizational unit (Production, R&D, and IT)
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-9
3.2. Data collection
Data were collected from two sources: semi-structured interviews and documents.
Interviews are suitable for gaining in-depth insights into individuals' experiences
regarding a phenomenon [Kallio et al. (2016); Yin (2018)]. As large-scale agile
transformation initiatives rely on people's interactions, interviews are an appropriate
data collection technique. Speci¯cally, semi-structured interviews, which provide
°exibility through follow-up questions, were a suitable technique for an in-depth
examination of the implications of knowledge boundaries for large-scale agile
transformation initiatives in manufacturing companies.
In total, 15 interviews were conducted with 16 interviewees involved in the agile
transformation initiative in their respective organizational units. The interviews
were carried out between September 2021 and February 2022. They were conducted
individually, except for one that was conducted jointly at the request of two inter-
viewees. Five of the interviewees represented Production, six represented R&D, and
¯ve represented IT. Interviewees included project managers, functional managers,
senior experts, change leaders, and portfolio managers, all of whom held key roles in
the implementation of the large-scale agile transformation initiative. The interviews
were conducted in English by two researchers. They lasted between 40 and 120 min
(see Table 3). All interviews were conducted via a videoconferencing tool, recorded,
and transcribed. They followed a prede¯ned interview guide that was slightly
adapted depending on the role of the interviewee.
Documents were used as an additional data source to corroborate or supple-
ment information from the interviews. The documents included con¯dential in-
ternal company materials with information about the agile transformation
initiative, organizational structure, organizational roles, management models,
work practices, etc.
Table 3. Overview of the interviews.
ID Organizational unit Interviewees Duration
01 Production Project manager 00:51:31
02 Change leader 00:50:43
03 Portfolio manager 00:58:43
04 Project manager 00:50:36
05 Portfolio manager 00:49:52
06 R&D Functional manager 01:16:21
07 Senior expert 00:55:21
08 Change leader 01:02:16
09 Change leader 02:01:46*
10 Project manager 02:01:46*
11 Senior manager 01:01:49
12 IT Senior manager 01:05:53
13 Functional manager 00:42:44
14 Portfolio manager 01:01:08
15 Consultant 00:40:10
16 Functional manager 00:51:15
Note:Interview conducted with two interviewees by request.
S. Orejuela, G. Johansson & D. Motte
2450039-10
3.3. Data analysis
Data analysis followed the three interactive activity streams proposed by Miles et al.
[2020]: data condensation, data display, and drawing and verifying conclusions. Data
condensation followed the thematic analysis proposed by Braun and Clarke [2006].
The ¯rst step was to identify segments of the transcripts and assign them ¯rst-order
codes, which are words or short phrases containing the interviewees' own terms and
thus foregrounding their voices [Miles et al. (2020)]. The next step was to group these
codes into second-order themes based on their word and content similarity. As the
interviewees sometimes used di®erent words to refer to the same content, documents
were used to corroborate the wording and assign congruent terms to the themes.
Once the second-order themes were created, it was clear that they re°ected the four
components of Scrum, namely, values,teams,events, and artifacts [Schwaber and
Sutherland (2020)]. Therefore, these agile components were used to group the sec-
ond-order themes into aggregate dimensions that represent the knowledge of agile.
The data analysis process was supported by the use of NVivo (version 1.7.1). The
¯nal data analysis followed the structure proposed by Gioia et al. [2013] and is shown
in Fig. 1.
4. Findings
4.1. Agile components
The interviewees described what they considered to be part of agile, and this content
was organized and related to the four agile components according to the process
described in Sec. 3.3. The interviewees' descriptions re°ect their knowledge of agile,
as shown in Fig. 1. Two second-order themes emerged related to the values com-
ponent: individual values and organizational culture. From the descriptions, three
second-order themes were derived and related to the teams component: coordination
between teams, team characteristics, and team roles. Four types of meetings were
identi¯ed, namely, decision meetings, information and learning meetings, planning
meetings, and pulse meetings. All meetings were assigned to the events component.
The last component, artifacts, refers to sets of tools or representations of the team's
work, and for this component the following second-order themes were derived from
the interviewees' descriptions: backlog, main plan, result de¯nition, sprint board,
and subresult.
Table 4shows some examples of how quotes from interviewees led to the ¯rst-
order codes and subsequent second-order themes and the aggregated dimensions.
4.2. Organizational units emphasize di®erent agile components
To contrast the knowledge of agile of the di®erent epistemic communities repre-
sented in the organizational units, a grid heat map was created (see Fig. 2). It depicts
a grid of colored cells containing a variable of interest on two axes. In this study, the
variable of interest was the number of interviewees, and the two axes are second-
order themes and organizational units. Therefore, each cell shows the number of
interviewees representing a particular organizational unit who provided information
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-11
regarding a particular second-order theme. The cells were colored according to their
number the higher the number, the darker the color. The pattern in the colors of
the cells facilitated the identi¯cation of the most common second-order themes and
their associated agile component among interviewees in each organizational unit.
Despite the initially scattered appearance of Fig. 2depicting the organizational
units' knowledge of agile, information can be extracted regarding the diverse em-
phases that organizational units' place on the various agile components.
Interviewees from Production emphasized the agile component events. Each sec-
ond-order theme related to events was mentioned at least once. Moreover, most of the
Fig. 1. Data analysis structure.
S. Orejuela, G. Johansson & D. Motte
2450039-12
interviewees in Production (4 out of 5) emphasized planning meetings as part of their
knowledge of agile. Most of them also emphasized team characteristics; however, the
other two second-order themes related to the agile component teams were not men-
tioned by the interviewees, implying that they did not emphasize this agile component.
For their part, interviewees from R&D were more concerned with events and
artifacts. Most of the second-order themes associated with these agile components
were mentioned by at least two interviewees, except for backlog, which was not
Table 4. Interviewee quotes and grouping examples.
Interviewee quote Data condensation
\Yeah, and a cultural [change], so what I talked
about before, dare to fail and so on, where you
almost get rewarded when trying things out
rather than not trying it." Interviewee 12
First-order code: Dare to fail
Second-order theme: Organizational culture
Aggregate dimension: Values
\This is, I think, the trickiest part, and I think it's
the most important part, to get this coordination
working. You can be super agile in a team, but if
you have dependencies to all the teams, you are
just waiting for them." Interviewee 12
First-order code: Coordination between teams
and requirements
Second-order theme: Coordination between teams
Aggregate dimension: Teams
\It could also a®ect us in a positive way. If you are
involved in the sprints and the planning ...it will
be easier for us to produce, and maybe the cus-
tomer value won't be di®erent." Interviewee 04
First-order code: Sprint-based planning meeting
Second-order theme: Planning meetings
Aggregate dimension: Events
\In the main plan, we have the main results that we
need to achieve during the journey from start
until the end; but then, in between, to get to one
point to the next, we work in sprints, so all the
detailed planning is done before the sprints only."
Interviewee 08
First-order code: Project main plan
Second-order theme: Main plan
Aggregate dimension: Artifacts
Fig. 2. Knowledge of agile among key roles from di®erent organizational units.
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-13
mentioned by any of the interviewees from R&D. Moreover, planning meetings were
mentioned by all the interviewees. Most of these interviewees (4 out of 6) mentioned
main plan and team characteristics as part of their knowledge of agile. Regarding the
latter, the other two second-order themes related to the agile component teams were
not emphasized by the interviewees, implying that this agile component is not
predominant in their knowledge of agile.
Finally, interviewees from IT placed a stronger focus on the agile components
values and teams. All the second-order themes related to these agile components
were mentioned by at least three of these interviewees. Team Characteristics was
mentioned by most interviewees (4 out of 5) from IT. They also mentioned two of the
second-order themes related to the agile component events (i.e. planning meetings
and pulse meetings); however, the other two second-order themes were mentioned by
at most one interviewee, implying that events is not a predominant part of the
knowledge of agile of interviewees from IT. Moreover, they were the only ones that
mentioned backlog and coordination between teams as part of their knowledge of
agile.
5. Discussion
5.1. Knowledge boundaries and large-scale agile transformation
In accordance with the de¯nition of knowledge boundaries presented by Tell [2016],
the ¯ndings indicate that, as the representatives of the studied organizational units
belong to di®erent epistemic communities, they emphasize di®erent agile compo-
nents, which results in knowledge boundaries. That is, as the interviewees represent
di®erent organizational units and consequently di®erent epistemic communities,
they have di®erent work experiences, educational backgrounds, uses of terms and
concepts, organizational goals, etc. [Dougherty (1992); Lawrence and Lorsch (1967);
Tell et al. (2016); Vandevelde and Van Dierdonck (2003)]. As suggested by authors
such as Lawrence and Lorsch [1967] and Dougherty [1992], organizational units live
in di®erent thought worlds and develop speci¯c attributes that help them cope with
their external environments. Therefore, the agile components that they emphasize,
as well as their interpretations of what is essential in agile and what is useful for their
own organizational units, are bound to re°ect the speci¯cities of their epistemic
communities, resulting in knowledge boundaries [Tell et al. (2016)] that limit their
shared knowledge of agile [Dougherty (1992)].
Interviewees representing Production are concerned with planning and schedul-
ing to ensure that the production organization delivers products on time. As a result,
they emphasize events that allow them to be involved early in the product devel-
opment process and thus be aware of changes that could a®ect the production
planning and scheduling. Interviewees representing R&D, for their part, have ex-
perience of traditional ways of working by using Stage-Gate or Waterfall models and
practices and are familiar with various design tools. Their focus on events and
artifacts re°ects these legacy models, practices, and tools. In addition, representa-
tives of both organizational units omit backlog as an artifact. This ¯nding is
S. Orejuela, G. Johansson & D. Motte
2450039-14
consistent with earlier observations by Ovesen [2012] that pointed to challenges in
using backlogs due to di±culties in breaking down physical product development
tasks into smaller items.
On the other hand, the emphasis that representatives of IT placed on values and
teams may re°ect their experience of working with agile. According to the results
presented by Kovynyov et al. [2021], experienced agile practitioners tend to focus on
agile values. Moreover, as IT leads the large-scale agile transformation initiative, the
representatives of IT are the only ones that emphasize coordination between teams.
According to agile frameworks, such as LeSS [The LeSS Company (2014)] and
Scrum@Scale [Sutherland and Scrum Inc (2022)], large-scale agile transformation
can be achieved by scaling and coordinating multiple agile teams.
In line with previous studies, the ¯ndings show that di®erent knowledge of agile
re°ects existing legacy models, such as Stage-Gate or Waterfall [cf. Beretta and
Smith (2023)], and should be considered in large-scale agile transformation initia-
tives [cf. Beretta and Smith (2023); Eklund and Berger (2017); Kasauli et al. (2020);
Schmidt et al. (2019)]. The ¯ndings also con¯rm the observations of Laanti et al.
[2011] showing that prior experiences of agile and non-agile frameworks or models
in°uence practitioners' knowledge of agile.
The level of complexity and novelty that the large-scale agile transformation
brings to the organizational units, the di®erent interpretations and meanings that
the organizational units put on agile components, and the di®erent emphases they
place on the latter entail what is called pragmatic boundaries, following the typology
of Carlile [2004]. As explained in Sec. 2.3, these knowledge boundaries limit a shared
and comprehensive knowledge of agile across the organization [Dougherty (1992)].
Hence, there is a need for negotiation to share and assess knowledge across organi-
zational units, implying a need for knowledge integration across boundaries [Carlile
(2002,2004); Tell (2016)].
5.2. Knowledge boundaries imply knowledge integration in a large-scale
agile transformation based on °exibility and dynamism
As concluded in Sec. 5.1, knowledge integration is essential to deal with knowledge
boundaries between organizational units in large-scale agile transformation initia-
tives. Based on the de¯nition presented by Huang [2000] (see Sec. 2.3), knowledge
integration in the context of a large-scale agile transformation initiative could be
understood as a collective process of constructing, articulating, and rede¯ning shared
knowledge of what agile is and how it should be implemented from the perspective of
di®erent organizational members and their social interactions.
Knowledge integration points to two aspects that need to be considered in the
context of large-scale agile transformation initiatives. The ¯rst refers to the knowl-
edge of the agile components and the way in which the initiative is implemented,
whereas the second refers to the collective processes required to achieve a shared
knowledge of agile in the organization.
Regarding the ¯rst aspect, the literature on large-scale agile transformation
suggests establishing agile values and principles (which refer to the agile component
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-15
values) as a starting point and emphasizing them over other agile components to
avoid a shallow transformation initiative [cf. Eklund and Berger (2017); Sommer
(2019)]. However, it might be challenging to start with agile values and principles
throughout the entire organization because, as described in Sec. 5.1, the agile com-
ponents emphasized by the di®erent organizational units are deeply embedded in the
speci¯cities of each epistemic community. That is, it might be di±cult to establish
agile values in organizational units that focus on the practical aspects of agile unless
those values are in line with the operational situations in which the organizational
units ¯nd themselves. Rather, °exibility, in which a large-scale agile transformation is
embedded in the existing experiences of di®erent organizational units, may be more
constructive. For example, R&D is used to working with various development
models, practices, and tools. For this organizational unit, a large-scale agile trans-
formation initiative could, in accordance with the ¯ndings presented earlier, use
artifacts and events instead of values as a starting point for implementation.
Regarding the second aspect, knowledge integration emphasizes the importance
of a collective process based on the social interaction of organizational members to
achieve shared knowledge in the organization [Huang and Newell (2003)]. Therefore,
dynamism, through which organizational units involved in the implementation of a
large-scale agile transformation initiative interact with each other through inte-
gration mechanisms, is needed. These integration mechanisms include, for example,
socialization, where mimicking behaviors enables the tacit knowledge of agile pos-
sessed by IT to be used in the Production or R&D contexts, or enrolment, where
representatives of IT, who are more experienced with agile, are temporarily assigned
to Production or R&D [Tell (2016)].
5.3. Toward a °exible and dynamic model for large-scale
agile transformations
Drawing upon the implications of knowledge boundaries and the key aspects of
°exibility and dynamism for the implementation of large-scale agile transformation
initiatives, a conceptual model is presented in Fig. 3. The model is inspired by the
notions of acting and interacting proposed by Enberg [2007]. The acting notion,
accounting for the °exibility of the model, refers to the individual work of the
organizational units. Here, organizational units have their own cycles to internalize
the agile components in which agile practices are used to understand the di®erent
agile components and how to apply them. However, it can be problematic if each
organizational unit builds its own knowledge of agile [Beretta and Smith (2023)].
Moreover, a successful large-scale agile transformation initiative also relies on the
interplay and interaction between di®erent organizational units [Rolland (2016)],
so alignment between organizational units must be ensured. Therefore, the model
includes a second notion: interacting. In addition to their internal cycles, organiza-
tional units must engage in a collective process. The interacting notion, accounting
for the dynamism of the model, is based on iterative and reinforcing cycles to build,
articulate, and rede¯ne shared knowledge of agile among organizational units. This
notion encompasses the use of integration mechanisms, such as sharing experiences
S. Orejuela, G. Johansson & D. Motte
2450039-16
from the agile transformation and other previous organization-wide initiatives,
generating learning through joint evaluations of the agile transformation initiative,
creating a common language, nurturing social capital, participatory decision-making
processes, sharing accountability for the agile transformation initiative, using
analogies to explain agile among organizational units, using prototypes or commu-
nication platforms, and mimicking the behaviors of other organizational units (see
Sec. 2.3).
By acknowledging the existence of knowledge boundaries related to agile between
organizational units, this model illustrates the importance of considering °exibility
and dynamism in the initial phase of the implementation of a large-scale agile
transformation initiative. The model implies that organizational units construct
their own knowledge (acting notion) by potentially using di®erent agile components
as starting points and following di®erent paths to internalize the other components.
In parallel, organizational units engage in a collective process of articulating and
rede¯ning shared knowledge of agile among the organizational units involved in the
initiative (interacting notion).
6. Conclusion, Contributions, and Limitations
6.1. Conclusion
The purpose of this study was to examine the implications of knowledge boundaries
between organizational units in the initial phase of the implementation of a large-
scale agile transformation initiative in a manufacturing company. The study shows
that organizational units emphasize di®erent agile components depending on the
Fig. 3. A conceptual model indicating the key aspects of °exibility and dynamism in the initial phase of
implementation of a large-scale agile transformation.
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-17
speci¯cities of their epistemic communities, for example, their contextual require-
ments, work experiences, and organizational goals, which result in knowledge
boundaries that in°uence the implementation of large-scale agile transformation
initiatives. Thus, Production focuses on events, R&D focuses on events and artifacts,
and IT focuses on values and teams. Since knowledge boundaries potentially limit
the formation of a shared knowledge of agile in the organization, acknowledging
these boundaries implies the need for knowledge integration in the implementation
of a large-scale agile transformation [cf. Carlile (2002,2004); Dougherty (1992); Tell
(2016)].
Knowledge integration in the context of large-scale agile transformation initia-
tives points to °exibility and dynamism as key aspects to consider in the imple-
mentation of these transformation initiatives. Flexibility relates to the needs and
unique situations of organizational units and implies that di®erent agile components
can be used as starting points for implementing the transformation initiative.
Dynamism refers to the interactions between organizational units involved in the
large-scale agile transformation initiative. A tailored implementation according to
the organizational units' contexts (the acting notion), coupled with interactions with
other organizational units to increase shared knowledge of agile (the interacting
notion), shows the complexities of implementing a large-scale agile transformation in
a manufacturing company.
6.2. Contributions to the literature and practice
The study makes several contributions to the literature and practice of large-scale
agile transformations in manufacturing companies. Regarding the literature, the
study shows that the existence of knowledge boundaries implies °exibility and dy-
namism in large-scale agile transformation initiatives. On the one hand, °exibility,
that is, self-organization and local adaptations, has been pointed to as a success
factor by authors such as Beretta and Smith [2023]. Flexibility contrasts with the
literature that suggests establishing agile values and principles as a starting point for
large-scale agile transformation initiatives [cf. Berger and Eklund (2015); Sommer
(2019)], as organizational units may have di®erent starting points and take di®erent
paths during the implementation of the transformation initiative. On the other
hand, and in contrast to the ¯ndings presented by Beretta and Smith [2023], who
found that integration is reached through a top-down approach using rules, proce-
dures, and processes, dynamism shows that integration may be achieved through a
collective process, in which involved organizational units articulate and rede¯ne a
shared knowledge of agile through the use of di®erent integration mechanisms.
Moreover, the study contributes by presenting several integration mechanisms
that have not been considered in the literature on large-scale agile transformation
in manufacturing companies, which often explores mechanisms such as coaching,
training, centers of excellence, the creation of new roles, communities of practice, and
the use of objects [cf. Beretta and Smith (2023); Kasauli et al. (2020); Lindl€
of and
Furuhjelm (2018); Sommer (2019); Uludağet al. (2019)]. Other integration
mechanisms include temporarily enrolling people from other organizational units to
S. Orejuela, G. Johansson & D. Motte
2450039-18
explain their context and understanding of agile, sharing accountability for the
transformation initiative among all the involved organizational units, using analo-
gies to explain agile components to other organizational units, and mimicking the
events, artifacts, etc. used by other organizational units.
The conceptual model, which illustrates °exibility and dynamism by the acting
and interacting notions, is a further contribution to large-scale agile transformation
initiatives. The model further supports the existing literature that asserts that large-
scale agile transformations must be adapted to the contextual conditions of each
organization [cf. Beretta and Smith (2023); Drutchas and Eppinger (2023); Lindl€
of
and Furuhjelm (2018); Sommer (2019); Uludağet al. (2019)]. The conceptual model
supports a contingency perspective in large-scale agile transformation initiatives in
manufacturing companies by illustrating an iterative and tailored implementation of
such initiatives.
Regarding contributions to practice, the study raises awareness among practi-
tioners of knowledge boundaries and their implications for the initial phase of
the implementation of large-scale agile transformation initiatives in manufacturing
companies. Manufacturing companies especially those with legacy models, such
as Stage-Gate and Waterfall striving for large-scale agile transformation may
consider actions that support °exibility and dynamism in their transformation
initiatives. On the one hand, actions should be oriented toward internal cycles in
organizational units that allow self-organization according to their contextual con-
ditions; on the other hand, actions should be oriented toward a collective process to
articulate and rede¯ne a shared knowledge of agile in the company. The conceptual
model can support organizations that are initiating their agile transformation
initiatives. Its acting and interacting notions provide insights into the importance of
the balance between what is carried out within an organizational unit and what
relies on interactions between organizational units.
Following the logic of analytical generalization [cf. Yin (2018)], the di®erent
emphases that Production, R&D, and IT place on the di®erent agile components
may be expected in companies with similar contextual conditions. Knowledge
boundaries and their implications for large-scale agile transformation initiatives may
exist in manufacturing companies and other kinds of companies with similar set-ups,
for example, those that have legacy models, such as Stage-Gate and Waterfall, or
require the integration of di®erent technologies and knowledge domains into their
o®ering. The agile components values,teams,events,andartifacts [Schwaber and
Sutherland (2020)] may also be useful for identifying the knowledge of agile in the
organization. In general, as pointed out by previous studies [cf. Drutchas and
Eppinger (2023); Lindl€
of and Furuhjelm (2018); Sommer (2019)], the case may serve
as inspiration for other manufacturing companies in the initial phase of, or striving
for, a large-scale agile transformation initiative.
6.3. Limitations and directions for future research
Despite its contributions to the literature and practice of large-scale agile transfor-
mation, the study has limitations that open avenues for future research. First, the
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-19
study addresses only the Production, R&D, and IT organizational units due to their
crucial role in the transformation initiative. However, large-scale agile transforma-
tion initiatives are organization-wide; therefore, the knowledge boundaries among
other organizational units, such as Sales, Marketing, and Finance, are worth ex-
amining in future studies. Second, this study is limited to the initial phase of the
implementation of a large-scale agile transformation initiative. Therefore, a longi-
tudinal study would be a logical continuation to further examine changes in
knowledge boundaries and their implications for later phases of the implementation
of large-scale agile transformation initiatives in manufacturing companies. Third,
further studies could explore how to deal with these knowledge boundaries or, in
other words, how to consider °exibility and dynamism in large-scale agile transfor-
mation initiatives in manufacturing companies, for instance, how the di®erent or-
ganizational units could conduct their own cycles to internalize the agile components
or in what cases particular integration mechanisms are useful to articulate and
rede¯ne shared knowledge of agile among organizational units. Finally, further
studies exploring large-scale agile transformation initiatives in manufacturing com-
panies with di®erent characteristics would extend the body of knowledge on large-
scale agile transformation initiatives in manufacturing companies.
Acknowledgments
The authors are thankful to the company for its collaboration during the study. A
special thanks goes to the interviewees for sharing their perspectives and valuable
insights during the interviews. The authors extend their gratitude to the editors and
anonymous reviewers whose valuable feedback and insights helped to improve the
quality of this paper.
ORCID
Silvia Orejuela https://orcid.org/0000-0002-1244-355X
Glenn Johansson https://orcid.org/0000-0003-2314-3357
Damien Motte https://orcid.org/0000-0002-8649-4034
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Biography
Silvia Orejuela is a doctoral student in Transformative Innovation at the Lund
University, Sweden. She holds an M.Sc. in Industrial Management and Innovation
from the Uppsala University, Sweden, as well as a B.Sc. in Industrial Engineering
from the Los Andes University, Colombia. Her research focuses on enhancing the
e±ciency and e±cacy of product development systems. Speci¯cally, she investigates
large-scale agile transformation initiatives in organizations involved in the design,
manufacture, and delivery of complex products.
Dr. Glenn Johansson is Professor of Product Development at the Lund Univer-
sity, Sweden. His research interests include areas such as design for sustainability
and the circular economy, management and execution of product development, and
S. Orejuela, G. Johansson & D. Motte
2450039-24
integrated product and production development. Publications have appeared in
Journal of Cleaner Production, Technological Forecasting and Social Change,
Journal of Engineering and Technology Management, Research-Technology Man-
agement, Journal of Manufacturing Technology Management, among others.
Dr. Johansson has received an Outstanding Paper Award from the Emerald Literati
Awards for Excellence and he is co-founder of the Product Development Academy in
Sweden. He is also a member of the Swedish Production Academy.
Dr. Damien Motte is holding a position of Assistant Professor at the Lund Uni-
versity, Sweden. He received a Ph.D. in Machine Design from the Same University, a
Research Master in Industrial Engineering from the École Centrale Paris, France,
and an M.Sc. in Industrial Engineering at the École des Mines d'Albi, France. He is
currently working on alternative engineering design and product development
methodologies.
Examining the Implications of Knowledge Boundaries for a Large-Scale Agile Transformation
2450039-25
