I have read a great book about knowledge management, “Knowledge Management in Theory and Practice” by Kimiz Dalkir. In her introduction to the book, the author reflects on the importance that knowledge management is gaining in today’s world, how knowledge is now being considered as an invaluable commodity and an intellectual asset. I agree with her view – I think knowledge is becoming even more crucial by the day. Individuals and organisations are challenged in the navigation through the myriads of data and information streams that are supposed to describe and explain events, situations and how our world is meant to function. We need to make sense of how things that really matter (such as climate change, the economy, society, sustainable development, the pandemic) really work and our needs are pressing.
The book gave me the inspiration for this short series of articles. I would like to share my learnings and provide my take of what knowledge management is, how it can be approached and, importantly, I want to offer a reflection on how the management of knowledge might apply to projects and to the project management profession.
In this first article I will cover some basic concepts, such as:
- What is knowledge?
- Tacit vs explicit knowledge
- Knowledge management models
- The SECI model
- The Integrated Knowledge Management cycle
I hope this can be of interest and you enjoy the reading.
What is knowledge?
Knowledge is not ‘data’ or ‘information’. These are just components of the much complex concept of knowledge. So what is knowledge? If you take a very basic definition, this is what Wikipedia says:
“Knowledge is a familiarity, awareness, or understanding of something, such as facts, skills or objects”
Adapted from Wikipedia
Let’s look at a very simple situation to see how data, information and knowledge come together.
Say that you are in Costa Rica, visiting the Monteverde Cloud Forest Biological Reserve. You know that there are beautiful quetzals in the reserve and you would like to see them. If you want to try to spot them on your own, well … good luck! Only an experienced guide will be able to spot them and point them to you, in the far distance. The guide will have the familiarity, the experience and will know where to look.
Data are directly observable facts. In the example above, the documented number of breeding pairs of quetzals in the Monteverde area, the season and the time of the day when your visit takes place, the weather conditions, the number of people in your visiting party could be considered the ‘data’. Information is the analysed data, the facts organised in order to impart meaning to the data. So ‘information’ could be considered as the previous sightings of the birds in relation to the time of the day or in relation to the season and the weather or the behavioural patterns of the resident birds. Knowledge is the ability of the guide to put all the data and information together, add the own experience and skills and spot the birds for you in the dense canopy…
A more-business oriented definition of knowledge is the following:
“Knowledge is the subjective and valuable information that has been validated and that has been organised in mental models. It is used to make sense of our world. It typically originates from accumulated experience, it incorporates perceptions, belief and values.”
Kimiz Dalkir
This definition captures key important attributes and we can infer some important challenges:
– knowledge is much, much more than ‘data’ or ‘information’;
– it has to be related to a purpose;
– it has value (knowledge is precious, but the value can fluctuate as it is dynamic in its relation to a purpose);
– it has a degree of subjectivity and it links to individual mental models (knowledge will be difficult to standardise);
– it is biased (by perceptions, beliefs and human fallacy);
– it can accumulate (but only with effort, practice, means and dedication).
Knowledge management is much more complex than data or information management…..
Tacit vs explicit knowledge
“We know more than we can tell”
Michael Polanyi
We have many types of knowledge – there is even a suggestion that there are 14 different types. The simple distinction between tacit and explicit knowledge is a fundamental tenet for the purpose of this series. These two types are well researched and documented.
In brief, the tacit knowledge is the knowledge difficult to put into words, the highly internalised one, the one reflecting skills and abilities of an individual, such as knowing how to do something (or when not to do it..) or recognising analogous situations. It is based on personal experience, intuition, wisdom, insight.
Opposed to tacit is the explicit knowledge, the one that is codified and it has been (or can be) rendered visible and accessible through transcription into documents, drawn as a picture or a map, taped into audio-visuals etc.
In her book, Dalkir nicely contrasts the properties of the two types of knowledge (presented below with some adaptations):
| TACIT | EXPLICIT |
| Fluid | Institutional |
| Spontaneous, creative, dynamic, experimental | Structured, codified, controlled, measured |
| Ability to adapt, to deal with new and exceptional situations | Ability to reproduce and re-apply |
| Coaching and mentoring, to transfer experiential knowledge on a one-to-one basis | Ability to disseminate, teach and train |
| Ability to collaborate, to share a vision, to transmit a culture | Ability to organise, to translate a vision into a mission statement, operational guidelines or ways of working |
| Expertise, know-how, know-why, know-when (and when not) and care-why | Transfer knowledge via products, services and documented processes |
Dalkir points interestingly to the fact that the more we focus on operational aspects of processes or well defined, practical situations, the easier it will be (at least theoretically) to translate knowledge into an explicit form. If we focus on the top of an organisation, at the strategic level or at poorly defined or complex situations, the knowledge will be more elusive and subjective, and therefore it will be more difficult to make it explicit.
Knowledge management models
The management of knowledge in the organisations has been conceptualised, theorised, researched and experimented for decades. Many definitions have been proposed for Knowledge Management (KM). One that is really clear is:
“A systematic approach to manage the use of information in order to provide a continuous flow of knowledge to the right people at the right time, enabling efficient and effective decision making in the everyday business”
Payne & Briton
Knowledge (as intellectual capital or as an asset) is increasingly valuable for the organisations. However, the approach as “save the data … they may prove useful in the future” cannot work. It can be expensive, inefficient, risky and not really workable (unless your line of work is in the field of “big data”). There is a need for a more ad-hoc approach for the data handling and for the information / knowledge management.
To assist in the implementation of KM practices, many models or frameworks have been researched and proposed. We need models and frameworks to aid our comprehension of the mechanism for the creation, transfer, embedding and re-use of knowledge, to provide tools to analyse the needs and gaps and to help organisations and individuals to put in actions effective arrangements.
The SECI model
Of all the models presented in the book, this is the one that caught my attention. The SECI (Socialisation-Externalisation-Combination-Internalisation) model was formulated in the late 90s by Nonaka and Takeuchi. This model has received criticism, for example for being heavily based on research and studies about Japan-based organisations and also for not dealing with the issue of using the information for decision making. However, it is very interesting and illustrative. I think it is useful to help us understand the dynamic nature of knowledge creation and evolution.
According to this model, there is a ‘spiral’ of knowledge in the process, where the explicit and tacit knowledge interact with each other in a continuous process. The central principle of the model is that knowledge held by individuals is shared with other individuals so it interconnects to a new knowledge. This process leads to creation of new knowledge, with the spiral of ‘conversion processes’ leading to the ‘amount’ of knowledge to grow all the time when more ’rounds’ are done in the spiral. These ‘conversion processes’ are:
Socialization (tacit -> tacit)
The first conversion process is about sharing tacit knowledge through face-to-face communication or sharing experience in typically social interactions.
Examples can be informal social intercourse, teaching by practical examples or demonstrations, an apprenticeship or mentorship, brainstorming to come up with new ideas, arriving at a mutual understanding through the sharing of ideas, and so on. Socialization is among the easiest forms of exchanging knowledge because it is what we do instinctively when we gather at the coffee machine, engage in impromptu corridor meetings, meet in the car park before leaving work, meet in the canteen or at the office kitchenette (do you remember those days?). The advent of social media is probably the biggest innovation in this phase.
Externalization (tacit -> explicit)
This is about trying to convert tacit into explicit knowledge by developing concepts and models.
In this phase tacit knowledge is given a visible form, it is converted to understandable and interpretable form, so it can be also used by others. Externalized and theoretical knowledge is a base for creating new knowledge, in the forms of metaphors, analogies, concepts, hypotheses, plans or models. Knowledge previously tacit can be written down, recorded, taped, drawn, made tangible or concrete in some manner. Once externalized, knowledge becomes tangible and permanent. It can be shared more easily with others and leveraged throughout the group, the organization or the community. Again, the availability of various social media channels and the easy access to a variety of social (data or information) platforms is probably an incredible innovation of the recent decades.
Combination (explicit -> explicit)
It is compiling externalized explicit knowledge to broader entities and concept systems, combining or re-combining with existing knowledge.
In this phase knowledge is also analysed, organized and connected. Some examples would be a synthesis in the form of a review report, a trend analysis, a brief executive summary, a new training programme or a new database to organize content. No new knowledge is created per se – it is a new combination or representation of existing and already explicit knowledge.
Internalization (explicit -> tacit)
The last of the conversion processes that leads to an understanding of explicit knowledge. It happens when explicit knowledge becomes a part of an individual’s basic information and it transforms into tacit knowldedge. It occurs through diffusion and embedding newly acquired behaviours and newly understood or revised mental models.
Internalization is strongly linked to “learning by doing”, converting or integrating shared and/or individual experiences and knowledge into individual mental models. New knowledge is then used by the individual who broadens it, extends it, and reframe it within their own existing tacit knowledge bases. (What I am doing here is probably an example of an effort for me to internalise my learnings, on KM and on the use or WordPress for the blog..)
According to this model and its spiral, knowledge is a continuous flow, with creation, sharing and conversion by individuals, communities and the organization itself. The knowledge spiral shows (at least theoretically) how organizations can potentially articulate, process, organize and systematise individual tacit knowledge, for example by producing and developing tools, structures and models to accumulate and share knowledge.
Would this model have an application to project knowledge management? We shall have a look in the last articles of this series.
The Integrated KM Cycle
In her book, Dalkir presents the Integrated KM Cycle that she develops through the chapters, step by step. This cycle might have a practical application for those interested in looking at their organisation’s KM process. The cycle can be visualised as follows:
Knowledge Capture refers to the identification of the know-how within the organization, any previously unnoticed internal knowledge and external knowledge from the environment that may be relevant. Knowledge Creation is the advancement of new knowledge and innovation, know-how which has no previous existence within the organization and purposely created. The issue here is about the correct ‘conceptualisation’ and ‘codification’ of such knowledge.
According to Dalkir, “knowledge is actively contracted in a social setting“. This is why Knowledge Sharing and Dissemination takes a social dimension. It is true that the new digital tools have increased accessibility to data and information, but the author gives emphasis to the importance of groups, teams and communities, with their common goals and social commitments driving their understanding and use of information. There is an introduction of ‘Communities of Practice’ (CoPs), incredibly relevant in our hyper-digitalised and connected world.
Key to organisational success is not just with the ability of capturing or retrieving data or information from databases and data platforms. It is about Acquisition and Application for effective actions and decision-making, by the individuals and the teams, as an integration into the business processes of the enterprise. The cycle is then closed as users understand and decide to make use of content, assess usefulness, suggest what to change and improve.
Interestingly, the complete cycle is within the Organisational Culture domain. The cultural environment in which the organisation finds itself will play a crucial role in what happens with the entire KM process. There is an entire chapter in the book dedicated to organisational culture.
In this article I tried to cover the basics of knowledge management, supported by the reading of Dalkir’s book and complemented with my own view, ideas and experience. For those with a particular interest in the subject, I recommend the book. It is a comprehensive overview on the subject.
With the next article I will try to dip into the application of knowledge management principles. Please do not hesitate to contact me for any comments and constructive feedback.
Marco Bottacini, Senior Portfolio Manager, GALVmed
The views and opinions expressed in this blog are those of the author and do not necessarily reflect the views and opinion of GALVmed.
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