Undervaluing information and knowledge assets (IKAs) is a common mistake in organisations tied to dated business and operational models. Opportunities for competitive advantage and service excellence are narrowing in traditional areas of management efficiencies, but growing in value-added activities, products and services at least partly driven by creative, innovative uses of information and the application of knowledge.
This kind of innovation might occur by happy coincidence, serendipity, or dumb luck once in a while. But mostly it is the outcome of planning and management. Hence knowledge management (KM).
Establishing the architectural and management framework for KM is one of my specialties. Let me help you understand and take advantage of the opportunities represented by your organisational IKAs.
To explain further, this page will offer an introduction to some basic KM concepts, and a separate page will outline how to develop a KM architecture as blueprint for a working KM process.
Below I will explain–
- What the DIKW model tells us about different types of information and knowledge.
- How a knowledge audit creates a baseline for a knowledge architecture.
- Why organisational culture is critical to KM success.
- How ‘learning loops’ create new knowledge.
- What can be done to embed tacit knowledge inside organisations.
The DIKW hierarchy
The data-information-knowledge-wisdom model has no acknowledged originator, but is ubiquitous because it is a neat way to visualise the relationship between types of information and their uses, including especially what really separates useful knowledge from the ‘factoid noise’ with which we are surrounded in an online environment with feew reliable filters for reliability, importance, credibility, or relevance.
The diagram is my adaptation and combination of the DIKW model with other knowledge management concepts.
We can see that the hierarchy implies data is useless until it is sorted by purpose to become information, and that information needs to be contextualised and applied for it to be knowledge.
There is a bit of a leap of faith to propose that knowledge necessarily leads to wisdom, but the potential certainly exists for erudite, experienced people to be regarded as wise, or in professional terms, as experts.
Figure 1 also shows explicit and tacit knowledge as properties of the ascending hierarchy. Explicit knowledge is the kind easily passed on by demonstration, or written instruction. A good example of explicit knowledge are the instructions for assembling a flat-pack wine rack. Tacit knowledge is of a kind difficult to pass on. It is usually tied to personal experience, expertise, and domain knowledge as intuition and insight. An example of tacit knowledge is being able to play the piano to an internationally renowned standard.
As the diagram makes clear, the closer we get to wisdom or expertise, the more likely we are to encounter tacit knowledge. This is a challenge for organisations who cannot embed it in their processes and procedures, and risk losing it if the person who has it leaves. So, making sure tacit knowledge is captured should be a primary goal for KM.
The diagram also shows implicit learning in the upper y axis. This is to signal another phenomenon as knowledge approaches wisdom. Implicit learning is of an incidental or accidental kind, where the learning parties acquire new knowledge without necessarily knowing it. It is like making new connections between information and knowledge already acquired and processed through observation, experience, or discussion with others. Implicit learning is a complex problem for most organisations: it is desirable for its potential to drive innovation; but hard to embed in the organisation, because it is difficult for the people who have this knowledge to pass it on.
Important implications of the DIKWA model are that data and information are inert until put to specific uses in a motivated, directed manner by a human agent. However, some types of knowledge, which we can think of as expertise, are developed only individually, and are hard to pass on to others. Developing processes to capture such knowledge and embed it in organisations is a significant challenge, but also offers significant opportunities.
Creating environments in which knowledge can be shared and discussed might help not only to pass on tacit knowledge to others, but also to generate implicit learning.
Audit for a knowledge architecture
For most organisations, the first step in grappling with KM is to get a clear idea of how things stand as they are. That’s the purpose of a knowledge audit, a simple process which is illustrated in Figure 2 to the right.
My knowledge audits are quite similar in approach to business process analysis: they have a discovery phase that harnesses subject matter experts to reveal how the organisation currently uses information and knowledge. Discovery is followed by mapping and documentation that can be agreed on by all stakeholders as an accurate baseline from which to design desired new processes and capabilities.
An audit ought to capture information intakes, storage, usage, and transformation points. The audit process should not be so rigid as to overlook organisation-specific or otherwise unique dimensions that might be the source of advantage and opportunity.
When the audit has uncovered the as-is information and knowledge capabilities of the organisation, the next step is usually to map the audit information to a knowledge architecture. That architecture should reveal an intelligible overview in which gaps can be identified in information or knowledge necessary for successful organisational processes and operations. The architecture should also expose any other shortcomings that need to be addressed to improve current performance and achieve strategic goals for the future.
I look at a generic architecture on its own page because of the level of detail involved.
KM success culture
When analysing audit results, I am guided by a knowledge management model developed by NASA. See figure 3 below.
The illustration shows a key ingredient in a successful KM strategy is organisational culture and how people are supported to acquire and pass on knowledge.
In this context, IT infrastructure can be as simple as shared directories and as complex as information repositories in team-share software. I’m no fan of unnecessary expenses, so I counsel developing some ‘user stories’ to give an insight into actual patterns of information usage and how knowledge is applied. A user story is a short descriptions of how a typical ‘end-user’ might go about accomplishing a specific task.
Culture is often the least understood aspect in knowledge management. For example, it is futile to expect employees to innovate if organisational culture is about control, compliance, and underhanded politics in which credit for good ideas is stolen or unrewarded.
In Figure 4 to the left I have adapted the work of Chun Wei Choo to suggest the likely information culture of some major types of organisations.
It is no coincidence that highly risky, entrepreneurial, and disruptive organisations tend to be driven by knowledge sharing and creation not obstructed by internal hierarchies and often involving iconoclastic directions in developing business models. However, such organisations also risk losing their innovative momentum if the rewards for such information sharing and creation are not also shared openly and equitably.
Not every organisation can emulate the internal dynamics of small startups, but most organisations can act on the certainty that since knowledge is essentially a human quality, a people-focus is necessary to mobilise more effective use of information, and to collaborate in knowledge creation and application.
This cultural context for knowledge management is an important guide to any recommendations I might make to an organisation after a knowledge audit. It is important for principals to understand that sometimes the entire organisational culture needs to change if significant changes are desired in how knowledge is leveraged to best advantage.
Changing organisational culture is difficult. Changing it incrementally is easier than a big-bang approach. But applying a value proposition to a desired change will keep the goal in sight.
To create a knowledge culture, organisations should develop their own learning value stream, like the one illustrated in Figure 5 below.
The illustrated value stream requires consideration of how best to realise the before, during, and after learning outcomes–
- Most workplaces expect employees to have existing and relevant skill-sets, but rapid changes in business environments mean such skill-sets have to be updated more and more frequently. That means knowledge focused organisations must support continuous learning and training in some form.
- Quite a bit of learning occurs on the job as part of ‘doing’. To encourage not just individual learning, but organisational innovation through innovative doing, an organisation must encourage initiative and the flexibility necessary not to do things only ‘one right way’. There must also be incentives for improving on processes and procedures.
- Not enough learning yet occurs after the event in most organisations. Professional practices like journalling to record, among other things, how to improve methods and processes, should be applied to a much broader range of job rôles. In larger organisations peer communities should be encouraged to meet and exchange views regularly to create opportunities for implicit learning. The experience of recent achievements should be transmitted to a broad audience of internal stakeholders through seminars and workshops.
The value stream illustrated and explained above is just an example. Each organisation has its own dynamics and characteristics that should determine priorities and learning dimensions when developing value streams.
However, a common goal for almost all organisations should be to create an awareness of the value of knowledge creation, and to drive efforts to create the kind of workplace culture and environment in which knowledge creation can take place.
The notion that knowledge creation can be turned into a process is controversial. I’m not referring to information collection and publication, or the application of rules. I’m referring to the generation of knowledge as expertise in its own right.
The human creativity and intellectual activity required for knowledge creation seems quite resistant to the engineering and mathematical logics that drive process design and implementation.
Experience tells me, however, that knowledge creation can be encouraged by normalising certain kinds of behaviours. Normalising just means they are made routine and part of the normal mode of operation.
And those behaviours include the reflection and analysis necessary for ‘triple-loop’ learning.
How that works in practice was initially proposed as ‘double loop’ learning by administrative science practitioner Chris Argyris in 1976.
The diagram shows the DIKW model embedded in the top layer and then how it fits into the double and triple learning loops.
Double-loop learning in this context is to challenge assumptions at each step to go back to the stage at which assumptions are formed, and triple loop learning is to go back to the raw data to see whether there have been wrong or needlessly restrictive assumptions along the way to transforming the data into expertise or wisdom. Or whether there are alternative paths from the data to a new combination of information to new kinds of knowledge.
When I map that model onto organisational behaviours, what I see are steps that might include–
- Connections in thinking between organisational culture, influenced by management behaviour and actions, leading to staff assumptions, which can sometimes be modified with input from a consultant like me.
- Staff making sense of management directives by reconciling them with organisational culture they have observed.
- An outsider’s view, comparing what staff say with directives from management about what everyone’s supposed to do.
- An outsider’s view on assumptions that might arise from organisational culture, management directives, and staff perceptions of both to discover whether there are challenges and opportunities not already recognised.
To make double and triple loop learning work for your organisation might require a higher degree of trust and employee independence than you’re used to. Including, on occasion, the confidence for staff to be able to challenge management directives when these are perceived as blocking better ways of doing things.
A final part of the design phase for a KM architecture is the specific focus on embedding knowledge into the organisation rather than have it remain contingent on specific people remaining within the organisation.
Embedding knowledge in the organisation
A model developed by economist Robert M Grant shows a possible pathway for socialising even tacit knowledge so that it is transmitted and more likely to remain an organisational property than an individual one (see Figure 7 below right).
Grant based his model on what Japanese knowledge management pioneer Ikujiro Nonaka observed about knowledge management in an industrial context.
However, the model has application across a broad range of organisations. The dimensions range from individuals to organisations, and from explicit to tacit knowledge. Some examples are listed for each case, but the really important things happen in the green rectangles.
Clockwise from the top-
Combination means capturing the explicit knowledge of individuals in organisational repositories.
Routinisation is making knowledge repositories an integral part of daily work routines.
Socialisation is the process of creating routines of interactions by senior, or most experienced staff with other staff, and with processes with which they usually don’t interact.
Externalisation refers to people who have tacit knowledge making deliberately attempts to pass that knowledge on in exchanges with other staff, possibly through mentoring, regular information briefings or workshops.
Internalisation is the reverse of externalisation, with people who have explicit knowledge trying to acquire tacit knowledge, possibly through seminars and briefings, but also by seeking mentors, or becoming understudies to more experienced staff, or similar strategies.
Systematisation is the holy grail: it is the effort to embed tacit knowledge in the organisation by a direct transfer from the most experienced people to the organisation’s knowledge repositories, possibly by encouraging the regular contribution of white papers, briefing collateral (notes, PowerPoint slides) on successful interactions with clients, customers, vendors, or stakeholders.
Exactly how this might apply to your organisation might be revealed by a knowledge audit as centrepiece of some brainstorming workshops.
Some words of caution
Knowledge management is no instant panacea, and may not lead to instant successes as measurable sales increases or service improvements. To gain confidence in its methods and habits, quick wins have to be targeted as immediate goals flowing from a knowledge audit.
In addition, knowledge management enthusiasts should be cautious about rushing into expensive software solutions before knowing exactly how and when a return on investment will be realised.
Many organisations today collect significant amounts of information because they can, not because they have any idea of how to use that information, or what legal obligations they assume in collecting and storing that information.
Storage alone costs money, and law suits based on breaching privacy or other legislation are even more expensive. All this to say, organisational principals should be certain about why they want information before collecting it, and about legal obligations before that information is transformed and used in specific ways.
More on these topics on my page on developing a knowledge architecture.
Hopefully I have provided enough detail about a very complex domain of professional practice to whet your appetite for exploring opportunities in knowledge management for your organisation.
If you think you might benefit from finding out more, contact me to discuss your needs.
Choo, Chun Wei (2013). Information culture and organizational effectiveness’. International Journal of Information Management, 33(5), pp 775-779. Doi: https://doi.org/10.1016/j.ijinfomgt.2013.05.009.
Grant, Robert, M (2013). ‘Nonaka’s ‘Dynamic Theory of Knowledge Creation’ (1994): Reflections and an Exploration of the ‘Ontological Dimension’. Krogh, Georg von; Takeuchi, Hirotaka; Kase, Kimio; and González Cantón, César, eds, Towards Organisational Knowledge: The Pioneering Work of Ikujiro Nonaka, Palgrave Macmillan, DOI: 10.1057/9781137024961