Content uploaded by Jean-Michel Viola
Author content
All content in this area was uploaded by Jean-Michel Viola on Oct 05, 2020
Content may be subject to copyright.
Chapter 5
Learning-by-Doing Knowledge
Externalization: from Boundary Objects to the
Emergence of Tacit Knowledge
Knowledge management (KM) has been defined as the systematic and explicit
management of knowledge-related activities, practices, programs, and policies
within the organization and aimed at supporting the entreprise’s ultimate objectives
(Wiig, 2000). Following Hansen et al. (1999), we can map the knowledge
management field along two lines: managing explicit knowledge through
Information Technologies, in the expert organization, and managing tacit knowledge
through people, in the organization of experts. In their seminal work, Nonaka and
Takeuchi (1995) develop a theory of knowledge, describing the interplay between
tacit and explicit along four modes of knowledge conversion (see figure 5.1):
socialization (from tacit to tacit, from individual to individual), internalization (from
explicit to tacit, from organization to individual), combination (from explicit to
explicit, from group to organization) and externalization or explicitation (from tacit
to explicit, from individual to group).
Chapter written by Jean-Michel VIOLA and Réal JACOB, HEC Montréal
Trends in Applied knowledge Management
Figure 5.1. Knowledge conversion in four modes
Some major drawbacks have been identified in the process of externalization.
More often, it has been seen as an artificial process, ignoring people and social
dynamics. Amin and Cohendet (2004) discussed the idea that the externalization
process “is a process of knowledge creation that alters both the codified and the tacit
forms of knowledge” (p. 24). Following this statement, this text develops the idea
that the process of explicitation itself co-creates both explicit and tacit knowledge
and sheds light on two main issues: the critical importance of boundary objects and
the need for a more precise definition of tacit knowledge.
After describing a case of externalization in a large Canadian industrial firm, we
illustrate how this process of externalization has generated relevant and robust tacit
knowledge as a side product. Thus, the rise of the expert organization may also
foster tacitness. This scenario of co-occurrence raises striking questions to be
addressed in many KM programs.
5.1. Learning-by-doing knowledge management
A few months ago we were puzzled by a comment from a human resources
director. Speaking about why her firm was engaged in significant knowledge
management research with academics, she said straightforwardly: “We could have
Learning-by-Doing Knowledge Externalization
hired consultants but they are learning with us at the same time… every body is
learning in this field! So we are more comfortable if it’s crystal clear from the start!”
This quote opens a large window of opportunity for action research at the same time
as it illustrates a certain pragmatic approach to KM, a way to harness the value of
experience in the knowledge-driven firm (Geisler, 1999). We can encapsulate this
approach in the concept Learning-by-doing, which means in fact three interelated
features:
– Learning over time: being able to learn in action, being able to look back on
the output of knowledge initiatives, to make room for adjustments. However, it is far
from easy to do this (Huber, 1991) because you need to develop a sense of
experience.
– Learning together: being able to connect individual experiences through
collective thinking, as shown by the growing popularity of communities of practice,
e-learning activities, story telling, learning organizations and corporate universities.
– Learning from facts and from people through corporate cases1 and lessons
learned2.
We have chosen to present here the case of Power Corp (PC) to illustrate how
the process of externalization, rooted in the will to hedge the risk of knowledge
leakage, co-creates tacit knowledge. We emphasize how the building of knowledge
artifacts, acting as boundary objects, foster tacit knowledge.
5.2. A process of externalization: knowledge strategy at Power Corp
PC is a large Canadian industrial firm providing services in the energy sector.
Net income totaled over 1b euros in 2003. PC has formalized its knowledge strategy
into a strategic knowledge management plan (2004–2006). This is an ongoing
project largely focused on human resources in the context of a specific threat: the
expected retirement of thousands of baby boomers in the next few years. The plan is
then specifically targeted toward hedging of the risk of a potential loss of expertise.
Then externalization issues are critical in this context.
1 Siemens, with the help of Tom Davenport and Gilbert Probst, develop a company-wide
approach to case building and transferring. In the pioneer book, Knowledge Management
Case Book (Wiley, 2000), 13 cases about innovative knowledge management practices,
written by Siemens managers, are presented with key propositions and discussion questions.
2 Learned lessons methodologies was first developed on a large scale in the US army through
the CALL (Center for Army Lessons Learned). For more details on the approach, see for
example, Baird et al. (1997).
Trends in Applied knowledge Management
Nonaka and Takeuchi (1995) define externalization as the process of articulating
tacit knowledge into explicit knowledge. They stress the fact that this is triggered by
dialogue and reflection and that it represents the most intensive interaction between
tacit and explicit knowledge from individual to group entities. The new
competitiveness of organizations is based on collective knowledge and, from that
standpoint, externalization is the key process. In this way, externalization holds the
key to knowledge creation, taking the sequential shapes of metaphors, analogies,
concepts, hypotheses and models. PC develops such a sequential four-phase
externalization process through its own specific activities: knowledge mapping,
criticality assessment, knowledge modeling and knowledge planning. Outside the
sphere of marketing, western firms are not very good at playing with metaphors and
analogies, despite the seminal work of Morgan (1991). They are much more at ease
with concepts, hypotheses and models. Contradictions and fuzziness, usually
associated with metaphors and analogies, are very often seen as errors and a lack of
control, rationality or order.
At PC, the knowledge management strategy is rooted in two complementary
perspectives: first, to understand better what are and what will be our key needs in
terms of knowledge, second, to favour the acquisition, development and transfer of
such knowledge so as to avoid threats to future performance. Thus, knowledge
management at PC is organized around four lines (see figure 5.2, below) to take risk
hedging actions: knowledge mapping, criticality assessment, knowledge modeling
and knowledge planning. In this chapter, we mainly describe the process of
externalization as the basis of such a knowledge strategy.
Figure 5.2. Knowledge strategy at Power Corp
Learning-by-Doing Knowledge Externalization
Below, we describe each step in more detail.
5.2.1. Mapping as a knowledge audit and mapping as scenario planning
First, a knowledge mapping process started in the R&D division. The six
directors organized brainstorming sessions around one question: what are our
expertises? After a few iterative rounds they reached an agreement on a graphical
map linking expertise from general knowledge to its applicability within the firm.
The process was seen and actually carried out as a knowledge audit. But despite the
fact that they gathered key information, it was merely information and in no way
was it a basis for decision-making in terms of knowledge planning. They needed
some sort of quantitative estimates of the real value of what they know, now and in
the future, over a five- to ten- year time frame.
5.2.2. Criticality assessment scales as decision rules
In this context, it was decided to apply at PC the methodology once developed
by Jean-Louis Ermine and the Club de Gestion des Connaissances in France
(Ermine, 2003; Boughzala and Ermine, 2004). The organization started a process,
lasting nearly two months, through over 60 interviews with people to better evaluate
the criticality of what they know. It used 21 criteria along four axes (utility of
knowledge, rarity of knowledge, ease of capitalization, ease of access). This process
led to two types of results:
– a substantial description of the knowledge portfolio and trends;
– a qualitative description of the nature of the knowledge and the needs for
transfer.
These two outputs were the basis for the next step:
– Decisions on knowledge portfolio: hold, cut, develop alone or in partnership,
etc.
– Decisions on the need for and the nature of knowledge transfer: what to
prioritize in terms of transfer? How to transfer it?
5.2.3. Modeling as a learning tool, as co-creation of knowledge
Modeling is used at PC in two very different ways.
– The classical modeling approach to writing the book of knowledge, procedures
or methodologies to guide future work.
– A more innovative approach using co-modeling in the case of a very complex
task. Using simple modeling software, both the expert and the novice engage in a
Trends in Applied knowledge Management
modeling process concerning a specific task: the expert models his task, while the
novice models what he understands of the expert’s task. Then they engage in a co-
construction of the model until they are both satisfied with the representation. This
leads to a valid description of the expert knowledge and it is also a description that is
understandable from the novice’s point of view. This way of doing things has been
proven highly effective for complex tasks at PC.
5.2.4. Plans as road maps addressing more specifically the need for tacitness
Finally, a knowledge plan was written at the directors’ level and then integrated
at the level of divisions. The plan uses different inputs based around a similar
template: maps, criticality, human resources and workforce demography, trends,
transfer plans. Four additional pilot cases were chosen to develop this process. After
each level, in each of the five pilot cases “lessons learned” research was carried out
to identify a return on experience that could be reused. What we will discuss now is
the co-creation of tacit knowledge that occurred throughout this whole process.
5.3. The tacit output of externalization: the importance of boundary objects
What is tacit knowledge and how is it created and nurtured? Since the seminal
work of Polanyi (1958) and, more specifically, since the intensive use of the concept
in the growing field of knowledge management (Nonaka, 1994; Nonaka and
Takeuchi, 1995), tacit knowledge has been widely discussed in the literature.
Despite this abundance and the fact that it is considered a key issue in knowledge
creation and dissemination, it remains largely a black box. Part of this elusiveness is
due to its true nature but part of it is also due to a lack of a comprehensive
description of tacit knowledge at the individual level. In Polanyi’s view, knowledge
has a personal dimension and is context specific. Human beings are then creating
knowledge by involving themselves with objects and they know more than they can
tell. Following Polanyi, Nonaka and Takeuchi (1995) described the trajectory from
tacit to explicit and back to tacit, through socialization, externalization, combination
and internalization. In their view, the creation of tacit knowledge is first an
individual process. At the same time, they recognized (p. 69) that some kind of
externalization helps to develop tacit knowledge:
For explicit knowledge to become tacit, it helps if the knowledge is verbalized
or diagrammed into documents, manuals, or oral stories.
The case study of knowledge management at PC sheds lights on two issues: the
critical importance of boundary objects and the need for a more precise definition of
tacit knowledge.
Learning-by-Doing Knowledge Externalization
5.3.1. Externalization creates critical boundary objects
Boundary objects (BO) are artifacts of knowledge that serve as both containers
(content) and carriers (process) of knowledge (Grey, 2002), “being both plastic
enough to adapt to local needs and constraints of the several parties employing them,
yet robust enough to maintain a common identity across sites” (Star, 1989).
Then, at PC, we can consider knowledge maps, criticality scales, models and
plans as BO, the mere existence of which fosters the emergence of tacitness.
These BO allow for combination, that is, according to Nonaka and Takeuchi
(1995), the process of systemizing concepts into a knowledge system, combining
different bodies of explicit knowledge. This combination creates redundancy, a key
prerequisite for collective learning, the basis for collaboration and synergy, although
redundancy is also seen as inefficient in the machine organization. Redundancy
creates bridges for joint projects at PC. Moreover, the process of building artifacts
and the artifact itself create overlaps, “learning by intrusion” (Nonaka & Takeuchi,
1995) in others’ sphere of expertise.
Then, maps, criticality scales, models and plans effectively make knowledge
management happen in two ways:
– By fostering socialization. Artifacts, as referentials, create a shared space that
is the basis for dialogue (Schrage, 1995).
– By fostering internalization, creating identity and meaning. The fact that
people are now able to represent themselves in the knowledge map brings some
sense of belonging. Although this was not seen as an issue at the beginning, it led to
some unexpected empowerment.
Hence, BOs were used by members in very different ways, although the
representation is shared. As Grey (2002) stated, BOs are an important class of
knowledge artifacts as they are associated with process, meaning, alignment and
reification. They are centre stage in the dynamics of knowledge exchange. Thus,
they are key elements in fostering the emergence of tacit knowledge.
5.3.2. Refining the classical definition of tacit knowledge
To better understand the emergence of tacit knowledge through the process of
externalization, we need to refine the definition of tacit knowledge. Starting from the
classical distinction first made by Polanyi between tacit and explicit, Nonaka &
Takeuchi (1995) tried to develop more explicitly the definition of tacit knowledge.
They argued that tacit can include two dimensions:
– a cognitive element, a working model of the world;
– a technical elements, such as know-how, craft and skills.
Trends in Applied knowledge Management
Baumard (1999) brought the explicitation of tacit knowledge one step further by
making another distinction between tacit knowledge that cannot be articulated or
stabilized and tacit knowledge that can be. But the definitions of both Nonaka and
Takeuchi (1995) and Baumard (1999) merely concern epistemological issues about
tacitness. To consider tacit knowledge in-action, beyond know-how and skills, it
may be useful to consider management activities implied by tacitness. Hence, we
can look at BOs as fostering tacitness along four managerial dimensions: tinkering,
judgment, connectivity, and coordination.
5.3.2.1. Tinkering
Tinkering refers to “do-it-yourself”, the ability to invent, to put the parts
together, to see how the parts fit so as to build innovation or new synergies. BOs
allow for identification of parts in the organization, creating unexpected
connections, and establishing ground for new ideas. At PC, BOs were seen as road
maps for navigating through the whole organization and as tools to foster knowledge
brokerage between knowledge components in order to develop innovative projects.
5.3.2.2. Judgment
Judgment is the ability to take decisions in action, shaped by experience. For
example, judgment allows the salesman to be able to understand and to adjust to the
demands and reactions of his customers. BOs bring a better evaluation of the
decision-making context, improving judgment (Augier et al., 2001). At PC, BOs
were seen as collective referentials within groups and as building key bridges
between groups. They allow for the refinement of mental models, improving the
decision-making process by decreasing perceptual biases between groups within
PC’s complex organization.
5.3.2.3. Connectivity
Connectivity refers to the ability to map, understand, and use the social network,
to promote dialogue based on a shared space. BOs help to frame this network and to
understand better the perspectives of other stakeholders. At PC, there is some
concern about non-technical competences. Behavioral features are key and very
often implementation issues raise behavioral problems rather than technical ones.
And maps, criticality and models help develop transverse understanding, the ability
to interact between divisions.
5.3.2.4. Coordination
Coordination is close to tinkering as it is also a combining capability, but here it
is targeted toward operational efficiency and not toward creativity and innovation. It
is rooted in Polanyi’s example concerning the way a child is able to ride a bike, not
using all the technical knowledge involved but simply by an appropriate
coordination of his or her moves. BOs improve the efficiency of coordination by
Learning-by-Doing Knowledge Externalization
providing keys and identifying modular components. At PC, BOs are seen as a
common language allowing collective and collaborative work.
The process of externalization produces boundary objects as output. In the case
of PC such BOs are knowledge maps, criticality assessment grids, knowledge
models and knowledge management plans. These BOs are knowledge artifacts that
are fostering the creation of tacit knowledge as a side effect in the process of
externalization. More specifically, they allow for faster innovation through
improved tinkering capabilities, for better decision making through more accurate
judgment, for better social interactions through improved connectivity, and for better
operational efficiency through improved coordination.
5.4. Conclusions and lessons learned
Externalization and BOs increase both explicit and tacit knowledge. Although
this process is seen as a valid framework from the actors’ point of view, a lot of
questions remain unanswered. And there are also some intriguing pathological sides
to externalization.
Many hurdles still exist in the process of knowledge explicitation. First, it can be
seen as being on the edge of bureaucracy through excessively formalized
methodologies; second, the proof of time needs to be addressed as it is a long and
costly exercise that needs to be carried out over time with a constant rigor; Third, it
can be seen as a political issue, a way to build legitimacy around tough questions
about downsizing or reorientation; Fourth, it can be seen as a unique substitute for
continuous thinking about how to manage innovation, ignoring other valid
approaches that are more focused on tacit knowledge management.
Of course, the ability to build on new tacit knowledge is probably critical for
success and a major challenge for management. The interplay between tacit and
explicit is then a key issue to keep the game alive. But it is rarely recognized as
such. It needs a dynamic approach to KM, but we are still struggling to design a
static one!
5.5. Bibliography
Amin A., Cohendet P., 2004. Architectures of knowledge. Oxford University Press
Augier M,, Shariq S., Vendelo M.T., 2001. “Understanding context: its emergence,
transformation and role in tacit knowledge sharing”, Journal of Knowledge
Management, Vol. 5, No. 2, pp. 125–136
Trends in Applied knowledge Management
Baird L., Henderson J.C., Watts S., 1997. “Learning from action: an analysis of the
army lessons learned (CALL)”, Human Resource Management, Vol. 36, No. 4;
pp. 385–397
Baumard P., 1999. Tacit knowledge in organizations. London: Sage
Boughzala I.,. Ermine J.-L, 2004. Management des connaissances en entreprise.
Paris: Hermes
Davenport T., Probst G. 2000. Siemens. Knowledge management case book.
Munich: Wiley & MCD Verlag
Ermine J.-L., 2003. La gestion des connaissances. Paris: Hermes
Geisler, E. 1999. “Harnessing the value of experience in the knowledge-driven
firm”, Business Horizons, May–June, pp. 18–26
Grey D., 2002. http://www.voght.com/cgi-bin/pywiki?BoundaryObject
Hansen M., Nohria N., Tierney T., 1999. “What is your strategy for managing
knowledge?”, Harvard Business Review, March–April, pp. 106–116
Huber, G., 1991. “Organizational learning: the contributing processes and the
literatures”, Organization Science, Vol. 9, No. 1, pp. 88–115
Nonaka, I. 1994. “A dynamic theory of organizational knowledge creation”,
Organization Science, Vol. 5, No. 1, pp. 14–37
Nonaka I., Konno N., 1998. “The concept of “ba”: building a foundation for
knowledge creation”, California Management Review, spring, pp. 40–54
Nonaka, I., Takeuchi H., 1995. The knowledge-creating company. Boston: Harvard
Business School Press
Polanyi, M. 1958. Personal knowledge. Chicago University Press.
Schrage, M., 1995. No more teams. New York: Currency.
Star, S.L., 1989. “The structure of ill-structured solutions: boundary objects and
heterogeneous distributed problem solving”, In Gasser L. & Huhns M. (eds),
Distributed artificial intelligence, pp. 37–54.
Wiig, K. 2000. “Knowledge Management: an emerging discipline rooted in a long
history”, in Despres D. & Chauvel C., Knowledge Horizons. Boston:
Butterworth-Heinemann, pp. 3–26.
