Knowledge Transfer

Our organizations are based on the interactions of individuals, teams and other organizations into a complex adaptive environment. We need to manage productive relationships as part of a complex system and interactions among parts can produce valuable, new, and unpredictable capabilities that are not inherent in any of the parts acting alone. This is why knowledge management, having a learning culture, is such a fundamental part of the work we do.

There are seven major categories we engage in when we manage, maintain, and create knowledge.

SocializationTacit-to-Tacitdifferent agentsSharing of tacit knowledge between individuals
IntrospectionTacit-to-Tacit same agentThe conscious or unconscious examination of one’s own tacit knowledge, as taken at an individual level
ExternalizationTacit-to-Explicitagent to knowledge managementThe expression of tacit knowledge and its translation into comprehensible forms interpretable by external agents
CombinationExplicit-to-ExplicitAll usersThe conversion of explicit knowledge into other variants of explicit knowledge
InternalizationExplicit-to-TacitTraining and deliberate practiceThe conversion of explicit knowledge into tacit knowledge
ConceptualizationAction-to-TacitContinuous ImprovementThe creation of tacit knowledge from aspects related to real work actions.
ReificationTacit-to-ActionProcess/ProcedureThe activity of bringing tacit knowledge into action (e.g. translating a mental model of a process activity into the actual operating tasks)
Knowledge Work Activities

As can be seen in the table above these seven activities involve moving between tacit and explicit knowledge. The apply to both declarative and procedural knowledge.

Examples of tacit and explicit knowledge


Socialization is the level of interaction between, and communication of, various actors within an organization, which leads to the building of personal familiarity, improved communication, and problem solving. Often called learning the roles, this is the the process by which an individual acquires the social knowledge and skills necessary to assume an organizational role. Socialization encourages two-way information exchange, builds and establishes relationship trust, and enable transparency of information.

Socialization creates an operating style, enabling people to communicate with each other, have a language that they all understand and behavioral styles that are compatible. It reinforces basic assumptions and shares espoused values by helping create common norms and compatible cultures.

Socialization enables many influencing tactics which makes it critical for change management activities.


The exploration of our experiences. Introspection can arise naturally but it can also arise deliberatively, for example journaling.

Introspection can also include retrospection, especially as a group activity. This is the strength of lessons learned.


The work of making the tacit explicit. Knowledge management as continuous improvement.


The combination of knowledge drives innovation and a learning culture. This includes the ability to identify different sources of knowledge, understand different learning processes, and combine internal and external knowledge effectively.

Knowledge combination capability generates through exchange of knowledge between individuals and work teams is a process that allows the transfer of knowledge to the organization and that can be applied to develop and improve products and processes.


As we move towards qualification we internalize knowledge.


The insights gained from doing and observing work. Deliberative learning.


The process of translating work-as-imagined into work-as-done through work-as-prescribed on a continuous loop of improvement. The realm of transformative learning.

Know the Knows

When developing training programs and cultural initiative sit is useful to break down what we really want people to know. I find it useful to think in terms of the following:

  • know-how: The technical skills to do the work
  • know-what: The ability to perform functional problem-solving, to adapt the process and innovate
  • know-who: networking and interpersonal skills, with social/emotional intelligence, for empathy or social network capacities
  • know-where: institutional and system knowledge of how the work fits into a larger ecosystem
  • know-who/how: strategic and leadership skills, for political ‘ nous’ in setting agendas, managing institutions, mobilizing resources;
  • know-why: creation of meaning, significance, identity, morality, with practical intuition for creative arts, sports, everyday social exchange.

To build all six elements requires a learning culture and a recognition that knowledge and awareness do not start and end at initial training on a process. We need to build the mechanisms to:

  • Communicate in a way to continually facilitate the assimilation of knowledge
  • Incorporate ongoing uses of tools such as coaching and mentoring in our processes and systems
  • Motivate the ongoing enhancement of learning
  • Nurture the development and retention of knowledge

We are striving at building competence, to be able to grow and apply the knowledge and abilities of our workers to solve problems and innovate.

Training, Development, Knowledge Management, Problem-Solving – these are a continuum but too often we balkanize responsibility of these in our organizations when what we need is an ecosystem approach.


Ambiguity is present in virtually all real-life situations and are those ‘situations in which we do not have sufficient information to quantify the stochastic nature of the problem. It is a lack of knowledge as
to the ‘basic rules of the game’ where cause-and-effect are not understood and there is no precedent for
making predictions as to what to expect

Ambiguity is often used, especially in the context of VUCA, to cover situations in situations that have:

  • Doubt about the nature of cause and effect
  • Little to no historical information to predict the outcome
  • Difficult to forecast or plan for

It is important to answer whether there are risks of lack of experience and predictability that might affect the situation, and interrogate our unknown unknowns.

People are ambiguity averse in that they prefer situations in which probabilities are perfectly known to situations in which they are unknown.

Ambiguity is best resolved by experimentation.

Levels of Uncertainty

Walker et al. (2010) developed a taxonomy of “levels of uncertainty”, ranging from Level 1 to Level 4,
which is useful in problem-solving:

  • Level 1 uncertainties are defined as relatively minor – as representing “a clear enough future” set within a “single system model” whereby outcomes can be estimated with reasonable accuracy;
  • Level 2 uncertainties display “alternative futures” but, again, within a single system in which probability estimates can be applied with confidence.

Levels 3 and 4 uncertainties are described as representing “deep uncertainty”.

  • Level 3 uncertainties are described as “a multiplicity of plausible futures”, in which multiple systems interact, but in which we can identify “a known range of outcomes”
  • Level 4 uncertainties lead us to an “unknown future” in which we don’t understand the system: we know only that there is something, or are some things, that we know we don’t know.

This hierarchy can be useful to help us think carefully about whether the uncertainty behind a problem can be defined in terms of a Level 1 prediction, with parameters for variation. Or, can it be resolved as group of Level 2 possibilities with probability estimates for each? Can the issue only be understood as a set of different Level 3 futures, each with a clear set of defined outcomes, or only by means of a Level 4 statement to the effect that we know only that there is something crucial that we don’t yet know?

There is often no clear or unanimous view of whether a particular uncertainty is set at a specific level. Uncertainty should always be considered at the deepest proposed level, unless or until those that propose this level can be convinced by an evidence-based argument that it should be otherwise.


  • Walker, W.E., Marchau, V.A.W.J. and Swanson, D. (2010) “Addressing Deep Uncertainty using Adaptive Policies: Introduction to Section 2”, Technological Forecasting & Social Change, 77: 917–23.

Procedure is Work-as-Prescribed

Written procedures with their step-by-step breakdown are a fundamental tool for ensuring quality through consistent execution of the work. As a standardized guideline for tasks, procedures serve many additional purposes: basis of training, ensuring regulatory requirements are met, ensuring documentation is prepared and handled correctly.

As written prescriptions of how work is to be performed, they can be based on abstract and often decontextualized expectations of work. The writers of the procedures are translating Work-as-Imagined. As a result, it is easy to write from a perspective of ideal and stable conditions for work and end up ignoring the nuances introduced by the users of procedures and the work environment.

The day-to-day activities where the procedures are implemented is Work-as-Done. Work-is-Done is filled with all the factors that influence the way tasks are carried out – spatial and physical conditions; human factors such as attention, memory, and fatigue; knowledge and skills.

Ensuring that our procedures translate from the abstraction of Work-as-Imagined to the realities of Work-as-Done as closely as possible is why we should engage in step-by-step real-world challenge as part of procedure review.

Steven Shorrock calls this procedural level “Work-as-Prescribed.”

Work-as-Prescribed gives us the structure to take a more dynamic view of workers, the documents they follow, and the procedural and organizational systems in which they work. Deviations from Work-as-Prescribed point-of-view are not exclusively negative and are an ability to close the gap. This is a reason to closely monitor causes such as “inadequate procedure” and “failure to follow procedure” – they are indicators of a drift between Work-as-Prescribed and Work-as-Done. Management review will often highlight a disharmony with Work-As-Imagined.

The place where actions are performed in real-world operations is called, in safety thinking, the sharp-end. The blunt-end is management and those who imagine work, such as engineers, removed from doing the work.

Our goal is to shrink the gap between Work-as-Imagined and Work-as-Done through refining the best possible Work-as-Prescribed and reduce the differences between the sharp and the blunt ends. This is why we stress leadership behaviors like Gemba walks and ensure a good document change process that strives to give those who use procedure a greater voice and agency.