Improvisation

Improvisation Takes Practice” in HBR is a great read. When I first read it, I chuckled at how it brings my gamer hobby and my quality practice together.

Employee creativity—the production of novel and useful solutions, procedures, products, and services—is critical to organizational success. I would argue, creativity drives excellence. Improvisation is a key employee behavior that drives creativity and innovation.

Improvisation is essential for navigating volatile, uncertain, and complex environments and dealing with unforeseen obstacles. Improvisation is also key to drawing distinctions, implementing new ideas, and converting knowledge and insights into action in real time. When confronted with critical and disruptive events, employees can resolve challenges by following existing protocols and procedures. In contrast, when faced with novel events, employees cannot rely on routines and conventions to respond. Rather, they will have to shift their focus to new perspectives, features, and behaviors.

The process of building expertise, when practices are assimilated, embodied, and rendered tacit, creates improvisational competence. Improvisation is an important source of action generating learning: people act to make events meaningful and situations understandable and, in the process, deepen their expertise through further learning, becoming reflective practitioners.

As part of knowledge management, today’s improvisations are absorbed and embedded into tomorrow’s routines.

Improvisation leads to better decision making, as I discussed in the post “Yes…but….and

Tacit and Explicit Knowledge

Nonaka classified knowledge as explicit and tacit. This concept has become the center piece of knowledge management and fundamental concept in process improvement.

Explicit knowledge is documented and accepted knowledge. Tacit knowledge stems more from experience and is more undocumented in nature. In spite of being difficult to interpret and transfer, tacit knowledge is regarded as the root of all organizational knowledge.

Tacit knowledge, unlike its explicit counterpart, mostly consists of perceptions and is often unstructured and non-documented in nature. Therefore, mental models, justification of beliefs, heuristics, judgments, “gut feelings” and the communication skills of the individual can influence the quality of tacit knowledge.

The process of creation of knowledge begins with the creation and sharing of tacit knowledge, which stems from socialization, facilitation of experience and interactive capacity of individuals with their coworkers.

Creation and Sharing of Knowledge

Knowledge creation involved organizations and it’s individual transcending the boundaries of the old to the new by acquiring new knowledge, which is considered to be mostly tacit in nature. The key to tacit knowledge sharing lies in the willingness and capacity of individuals to share what they know (knowledge donation) and to use what they learn (knowledge collection).

Knowledge quality is the acquisition of useful and innovative knowledge and is the degree to which people are satisfied with the quality of the shared knowledge and find it useful in accomplishing their activities. The quality of knowledge can be measured by frequency, usefulness and innovativeness, and can be innovative or new for the system or organization. However, if the knowledge is not beneficial to achieving the objective of the objective of the organization then it does not fulfill the criteria of knowledge quality. There are six attributes to knowledge quality: adaptability, innovativeness, applicability, expandability, justifiability and authenticity,

Sources

  • Kaser, P.A. and Miles, R.E. (2002), “Understanding knowledge activists’ successes and failures”, Long Range Planning, Vol. 35 No. 1, pp. 9-28.
  • Kucharska, W. and Dabrowski, J. (2016), “Tacit knowledge sharing and personal branding: how to derive innovation from project teams”, in Proceedings of the11th European Conference on Innovation and Entrepreneurship ECIE, pp. 435-443.
  • Nonaka, I. (1994), “A dynamic theory of organizational knowledge creation”, Organizational Science, Vol. 5 No. 1, pp. 14-37.
  • Nonaka, I. and Takeuchi, H. (1995), The Knowledge-Creating Company, Oxford University Press, New York, NY.
  • Nonaka, I. and Toyama, R. (2003), “The knowledge-creating theory revisited: knowledge creation as a synthesizing process”, Knowledge Management Research and Practice, Vol. 1 No. 1, pp. 2-10.
  • Nonaka, I. and Von Krogh, G. (2009), “Perspective—tacit knowledge and knowledge conversion: controversy and advancement in organizational knowledge creation theory”, Organization Science, Vol. 20 No. 3, pp. 635-652
  • Riege, A. (2005), “Three-dozen knowledge-sharing barriers managers must consider”, Journal of Knowledge Management, Vol. 9 No. 3, pp. 18-35.
  • Smedlund, A. (2008), “The knowledge system of a firm: social capital for explicit, tacit and potential knowledge”, Journal of Knowledge Management, Vol. 12 No. 1, pp. 63-77.
  • Spender, J.C. (1996), “Making knowledge the basis of a dynamic theory of the firm”, Strategic Management Journal, Vol. 17 No. S2, pp. 45-62.
  • Soo, C.W., Devinney, T.M. and Midgley, D.F. (2004), “The role of knowledge quality in firm performance”, In Tsoukas, H. and Mylonopoulus, N. (Eds), Organizations as Knowledge Systems. Knowledge, Learning and Dynamic Capabilities, Palgrave Macmillan, London, pp. 252-275.
  • Sorenson, O., Rivkin, J.W. and Fleming, L. (2006), “Complexity, networks and knowledge flow”, Research Policy, Vol. 35 No. 7, pp. 994-1017.
  • Waheed, M. and Kaur, K. (2016), “Knowledge quality: a review and a revised conceptual model”, Information Development, Vol. 32 No. 3, pp. 271-284.
  • Wang, Z. and Wang, N. (2012), “Knowledge sharing, innovation and firm performance”, Expert Systems with Applications, Vol. 39 No. 10, pp. 8899-8908.

Experts think differently

Research on expertise has identified the following differences between expert performers and beginners

  • Experts have larger and more integrative knowledge units, and their represen­tations of information are more functional and abstract than those of novices, whose knowledge base is more fragmentary. For example, a beginning piano player reads sheet music note by note, whereas a concert pianist is able to see the whole row or even several rows of music notation at the same time.
  • When solving problems, experts may spend more time on the initial prob­lem evaluation and planning than novices. This enables them to form a holistic and in-depth understanding of the task and usually to reach a solution more swiftly than beginners.
  • Basic functions related to tasks or the job are automated in experts, whereas beginners need to pay attention to these functions. For instance, in a driving Basic functions related to tasks or the job are automated in experts, whereas beginners need to pay attention to these functions. For instance, in a driving school, a young driver focuses his or her attention on controlling devices and pedals, while an experienced driver performs basic strokes automatically. For this reason, an expert driver can observe and anticipate traffic situations better than a beginning driver.
  • Experts outperform novices in their metacognitive and reflective thinking. In other words, they make sharp observations of their own ways of think­ing, acting, and working, especially in non-routine situations when auto­ mated activities are challenged. Beginners’ knowledge is mainly explicit and they are dependent on learned rules. In addition to explicit knowledge, experts have tacit or implicit knowledge that accumulates with experience. This kind of knowledge makes it possible to make fast decisions on the basis of what is often called intuition.
  • In situations where something has gone wrong or when experts face totally new problems but are not required to make fast decisions, they critically reflect on their actions. Unlike beginners, experienced professionals focus their thinking not only on details but rather on the totality consisting of the details.
  • Experts’ thinking is more holistic than the thinking of novices. It seems that the quality of thinking is associated with the quality and amount of knowledge. With a fragmentary knowledge base, a novice in any field may remain on lower levels of thinking: things are seen as black and white, without any nuances. In contrast, more experienced colleagues with a more organized and holistic know­ledge base can access more material for their thinking, and, thus, may begin to explore different perspectives on matters and develop more relativistic views concerning certain problems. At the highest levels of thinking, an individual is able to reconcile different perspectives, either by forming a synthesis or by inte­grating different approaches or views.
LevelPerformance
BeginnerFollows simple directions
NovicePerforms using memory of facts and simple rules
CompetentMakes simple judgmentsfor typical tasksMay need help withcomplex or unusual tasksMay lack speed andflexibility
ProficientPerformance guided by deeper experience Able to figure out the most critical aspects of a situation Sees nuances missed by less-skilled performers Flexible performance
ExpertPerformance guided by extensive practice and easily retrievable knowledge and skillsNotices nuances, connections, and patterns Intuitive understanding based on extensive practice Able to solve difficult problems, learn quickly, and find needed resources
Levels of Performance

Sources

  • Clark, R. 2003. Building Expertise: Cognitive Methods for Training and Performance Improvement, 2nd ed. Silver Spring, MD: International Society for Performance Improvement.
  • Ericsson, K.A. 2016. Peak: Secrets From the New Science of Expertise. Boston: Houghton Mifflin Harcourt
  • Kallio, E, ed. Development of Adult Thinking : Interdisciplinary Perspectives on Cognitive Development and Adult Learning. Taylor & Francis Group, 2020.

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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.

ActivityConvertsInvolvingMeaning
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

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.

Introspection

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.

Externalization

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

Combination

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.

Internalization

As we move towards qualification we internalize knowledge.

Conceptualization

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

Reification

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.