The twin KM approaches of Connect and Collect

I have blogged quite a bit recently on Connect and Collect approaches to KM, aka the transfer of tacit and explicit knowledge. Here is a reprise and extension of a useful table which describes the two.

Three of my recent blog posts have touched on

Each of these deals with knowledge transfer through tacit and explicit knowledge, comparing the use of the two, its efficiency and its effectiveness.  These two approaches to knowledge transfer are the connect approach, where knowledge is transferred by connecting people, and the collect approach, where knowledge is transferred by collecting, storing, organising and retrieving documents.

Each method has advantages and disadvantages, as summarised in the table below and the blog posts referenced above.  Effective Knowledge Management strategies need to address both these methods of knowledge transfer. Each has its place, each complements the other. These are not “either/or” choices, they are “both/and”.



Advantages Very effective
Allows transfer of non-codifiable knowledge
Allows socialization
Allows the knowledge user to gauge how much they trust the supplier
Easy and cheap
Very efficient.
Allows systematic capture
Creates a secure long-term store for knowledge
Knowledge can be captured once and accessed many times
Disadvantages Risky. Human memory is an unreliable knowledge store
Inefficient. People can only be in one place at one time
People often don’t realize what they know until its captured
Ineffective. Much knowledge cannot be effectively captured and codified.
Capturing requires skill and resource
Captured knowledge can become impersonal
Captured knowledge cannot be interrogated
Transfer medium Conversation, whether face to face or electronically mediated, or in team processes such as knowledge exchange, retrospect, peer assist

Content in the form of documents, files, text, pictures and video.

Need for balance Managing conversation without content leads to personal rather than organisational learning. Unless new knowledge becomes embedded in process, guidance or recommendations, it is never truly “learned”, and without this we find knowledge becomes relearned many times.

A focus on content without conversation results in a focus on publishing; on creation of knowledge bases, blogs, wikis, as a proxy for the transfer of knowledge; on Push rather than Pull. But unless people can question and interrogate knowledge in order to internalise it, learning can be very ineffective.

Types of knowledge suitable for this form of transfer Ephemeral rapidly changing knowledge, which would be out of date as soon as its written down
 Knowledge of continual operations, where there is a large constant community
Knowledge needed only by a few
Stable mature knowledge
Knowledge of intermittent or rare events
High-value knowledge
Knowledge with a large user-base
Organisational demographics which suit this approach  A largely experienced workforce A largely inexperienced workforce
Comments One traditional approach to Knowledge Management is to leave knowledge in the heads of experts. This is a risky and inefficient strategy. A strategy based only on capture will miss out on the socialization that is needed for culture change, and may fail to address some of the less codifiable knowledge.

View Original Source ( Here.

Why transferring knowledge through discussion is over 10 times more effective than written documents

Connecting people is far less efficient than Collecting while being far more effective – but how much more effective?

Knowledge can be transferred in two ways – by Connecting people so that they can discuss, and Collecting knowledge in written (explicit) form so others can find and read it (see blog posts on Connect and Collect). 

Connecting people is less efficient than transferring documented knowledge, but more effective.  We can never be sure about the absolute effectiveness of knowledge transfer without some good empirical studies, but there are 2 pointers towards the relative effectiveness of these two methods. These pointers are as follows;

First, the often repeated (and sometimes challenged) quote that “We Learn . .

  • 10% of what we read 
  • 20% of what we hear 
  • 30% of what we see 
  • 50% of what we see and hear 
  • 70% of what we discuss 
  • 80% of what we experience 
  • 95% of what we teach others.”

This is similar to Media Richness theory, which ranks media on the basis of it’s richness, with unaddressed documents as least rich, and face-to-face as most rich.

Second, David Snowden’s principle that

  • We always know more than we can say, and 
  • We will always say more than we can write down
Our assumptions
Let’s make two assumptions here, firstly that the percentages in the first list are correct, and secondly that we equate the “more than” in Snowden’s principle to “twice as much as.” OK, the fist assumption is highly dubious and the second is entirely arbitrary, but I want to see what the consequences are.

With these assumptions, the effectiveness of the Connect route (knowledge transfer through discussion) is as follows
  • I know (100%)
  • I say (50%) 
  • You learn through discussion (70%)
The effectiveness of transmission of knowledge through Connecting is therefore 35% (100% x 50% x 70%) provided there is discussion involved.

If you connect people through video (seeing) the effectiveness drops to 15%. Through hearing only (eg podcasts) it drops to 10%. The most effective way to transfer knowledge would be to work together, so the knowledge donor does not need to tell or write, they just have to show, while the knowledge receiver learns by experience. That way you minimise the filters.

The effectiveness of the Collect route for knowledge transfer through documents is as follows
  • I know (100%)
  • I write (50% x 50% = 25%)
  • You learn through reading (10%)
The effectiveness of transmission of knowledge through Connecting is therefore 2.5% (100% x 25% x 10%)
Transfer through discussion is 35% effective, transfer through documents is 2.5% effective. In the first case you can transfer a third of what you know, and in the second case you transfer one fortieth.

Therefore transferring knowledge through Collecting is 14 times less effective than transferring knowledge through Connecting people.

If we change the proportions in Snowden’s principle then we change this conclusion. If for example 

we always know 3 times more than we can say, and we will always say 3 times more than we can write down, Collecting becomes 21 times less effective, and so on.

I know all these figures are arbitrary and inexact, but what we are looking at here is some sort of estimate of relative efficiencies.

Note that this does not mean that Collecting knowledge has no place in Knowledge Management – quite the opposite. Despite being very ineffective, it is very efficient. Knowledge has only to be documented once, to be re-used one thousand times. Efficiency can trump effectiveness. However we can conclude the following
  • Because of these relative efficiencies, Knowledge should shared in explicit form (the Collect route) only when it is relatively simple and when it can be codified with minimum loss of context. 
  • Where efficiency is more important than effectiveness (i.e. broadcasting relatively straightforward knowledge to a large number of users), the Collect route is ideal.
  • The Collect route is also necessary when a Learner (a recipient for the knowledge) cannot be immediately identified, so no Connection is possible (see “speaking to the unknown user“).
  • Even then, it is worth “keeping the names with the knowledge” so that readers who need to know more detail can call the originator of the knowledge and have a discussion.
  • Where knowledge is more complex or more contextual, it should be shared through discussion (the Connect route) – for example through conversational processes such as Peer Assist.

Given that transfer of knowledge through documents is so ineffective, choose your KM strategy carefully!

View Original Source ( Here.

The two chambers of the KM heart

The heart of KM keeps knowledge flowing, and that heart has two chambers. 

Image from wikipedia

You can think of the organisation as a body, and knowledge flowing round the organisation like blood flows round a body.  But what is at the heart of KM? Is it knowledge sharing? Is it communities of practice? Is it knowledge creation?

The answer is that if there is a heart, it is not a single thing, but two chambers working together.  The two chambers are our old friends Connection and Collection; the Connect and Collect routes for knowledge transmission through Conversation and Content respectively. 


Connection refers to connecting people so that they can share knowledge between them; through discussion and conversation. 


Collection supports knowledge transfer through collecting documented knowledge, synthesising it, sharing it and making it findable.

  • In the Collect route, Knowledge is transferred through documentation (“Knowledge capture”), through organisation and synthesis of that documentation, and through connecting the user with the documents, through search or through push.
  • It can be supported by processes such as Retrospect, Lesson Learning, Interview, creation of Knowledge Assets, and Knowledge Synthesis. 
  • It can be supported by technologies such as portals, lessons management systems, search, semantic search, blogs and wikis

You Need both routes!

In the past, Connect and Collect have been positioned as opposites, for example in the rival Personalisation vs Codification strategies described by HBR.

However they are not opposites; they are two sides of the same heart.  The two different approaches address different sorts of knowledge, both of which exist in your organisation. 

  • The Collect route is ideal for relatively simple non-contextual knowledge which needs to reach a large audience, for knowledge that needs shelf life, for knowledge where no immediate user is available, and for knowledge which needs compiling and processing (such as lessons). 
  • The Connect route is necessary for complex knowledge, advanced knowledge, deep skills, and highly contextual knowledge. 
  • Collection without connection results in bland knowledge bases which answer basic questions, but often lack nuance and context.
  • Connection without collection preserves no corporate memory, and runs the risk of overloading the experts with basic questions, and of loss of knowledge as the experts retire.
In reality, the two chambers of the heart work together. 
People can unite around collections of knowledge, connected people can collect what they collectively know. Conversation is where content is born, and content is something to talk about. In combination, both Connect and Collect drive the engine that makes knowledge flow. 

Keep the two chambers of Connection and Collection at the heart of your Knowledge Management strategy  if you want to succeed!

View Original Source ( Here.

The four contexts for Knowledge Transfer

There is no one-size-fits-all solution for knowledge transfer, because not every transfer context is the same.  However we can look at four main classes or types of knowledge transfer, by looking at the dimensions of TIME and LOCATION.

There are other dimensions as well, such as whether the transfer is Expert/Expert, Expert/Novice etc, but let’s stick with 2 dimensions at a time, as that helps build a Boston Square, as shown here. 
This particular Boston Square, based on location and time, allows us to identify 4 contexts for knowledge transfer, described below. 

OTJ (On The Job) Transfer

The transfer of knowledge between people or teams who are co-located – doing the same sort of work at the same time in the same place – can be done on the job. This is the sort of context you see within a project team. The knowledge does not need to be documented in order to be transferred, and because everyone is working with the knowledge every day, then your focus should be more on conversations about knowledge rather than building knowledge bases. Knowledge can be transferred through embedding processes like mentoring, coaching, and particularly After Action Reviews, as well as through numerous informal conversations. 

Serial transfer

The transfer of knowledge within a series of projects in the same location, one after the other (and often with the same team) is called serial transfer. Much serial transfer can be accomplished by the transfer of project plans, designs, basis of design documents, and so on, as well as by transferring lessons learned, and transferring core team members. Project knowledge handover meetings can also be useful – sometimes known as baton-passing. The focus here is less on conversation, and more on transfer and continuous improvement of artefacts. This can results in excellent examples of steep learning curves.

Knowledge transfer between individuals working in the same place but at different times is accomplished by personal knowledge handover – a planned set of conversations, and compilation of a set of key documents, contacts, lessons and tips and hints. This can be part of a Knowledge Retention Strategy.

Parallel transfer

The transfer of knowledge between a series of projects running simultaneously but in different locations, or between many individuals doing the same work in different parts of the business, is called parallel transfer. This can rely heavily on face-to-face activities such as peer assist, and knowledge visits, as well as real-time transfer of knowledge through communities of practice, online forums and enterprise social media. Because operations are simultaneous and continuous, much knowledge can remain tacit, and the focus is on conversation rather than content.

Far Transfer

The transfer of knowledge between projects running in different times and different places, or from person to person separated by time and distance, is called far transfer (a term coined by Nancy Dixon). Far transfer cannot rely on real-time conversations, or on simply transferring project plans, as the next project may take place in a completely different country in several years time. Knowledge will need to be transferred in written form as a knowledge asset, or as a series of Lessons Learned. Far Transfer relies on captured knowledge, the development of knowledge assets, and careful attention to well written and easily findable advisory and instructional content.

There is no one-size-fits-all approach to Knowledge Transfer; it depends on the specific context, which may  be one of the four described here. 

View Original Source ( Here.

How knowledge can be "the thread through the labyrinth"

“The thread through the labyrinth” is a metaphor for allowing others to follow our steps safely. This is what Knowledge can do. 

When Theseus negotiated Daedelus’ labyrinth in order to kill the Minotaur, he left a thread behind him (provided by Ariadne, daughter of Minos) so that the way through the Labyrinth would be clearly marked.

Cave divers do something similar, unreeling a line behind them as they explore the labyrinth of flooded passageways; both so they can find their own way out, and also so that others can follow the path without getting lost, or without having to explore the same dead ends and blind alleys that the first divers did. 

Sometimes, negotiating our projects feels like making our way through a labyrinth, especially when the project has to negotiate complex regulatory or bureaucratic hurdles, or technical difficulties.

When we successfully negotiate these hurdles, which sometimes can be long and taxing, we need to leave a thread behind us for the sake of the next project.

Imagine the first project of its type in a country – the first factory, or the first branch office. Imagine you have eventually worked your way through the maze of rules, regulations and red tape, contracts and logistics. The thread you leave behind is not string, but the collected knowledge (the “knowledge asset“) that enables the second factory, or the second branch office, to successfully follow the path of the first.

That knowledge might include;

  • The list of activities you need to undertake
  • The order in which to undertake them
  • The people you must contact, and how to contact them
  • The letters you must send, and how to write them
  • The evidence you must collect, and how to best present it
Without leaving this trail of knowledge behind you, the second factory or the second branch office will approach the maze of logistics and legislation with the same ignorance as the first, and may get just as lost and confused.

If you are the first to try something, then leave a guideline of knowledge for others to lean from.

View Original Source ( Here.

Three styles of Knowledge flow – centre-out, out and in, or multiflow

There are three common styles of knowledge flow that you can see in organisations. We can call them centre-out, out and in, and multiflow.

In our picture here, the red dots are the central group of experts, the white dots are the knowledge users or knowledge workers, and the white arrows are the flow of knowledge.

In the centre-out model, the knowledge is created by the experts in the centre, and “pushed out” to the knowledge workers, in the form of doctrine, work instructions and policies. The centre owns the knowledge – they are the Knowers – while the knowledge workers apply the knowledge – they are the Doers.

In the out-and-in model the knowledge is managed by the experts in the centre. Knowledge is gathered from the knowledge workers, synthesised and validated in the centre, and transferred back out to the workers. There are feedback loops such as lesson learning systems which mean that the central knowledge is always tested against reality and updated regularly. The centre stewards the knowledge and validates it, while the knowledge workers both apply and improve the knowledge.

In the multiflow model, the knowledge flows between expert and worker, worker and worker, worker and expert. Knowledge is created, updated and validated by all parts of the system, and is available in real time. The knowledge is managed and owned by the Community of Practice, while the centre manages and stewards, not so much the knowledge itself, but the knowledge-creating and knowledge-validating system.

The first model seems very old fashioned nowadays, and the third model seems much more attractive, and is becoming more common (see for example the use of Wikis to develop Army doctrine).

However in reality all three models may be needed simultaneously in any one organisation, to deal with different types or different levels of knowledge.

  • There may be mandatory knowledge, such as knowledge of company law, or knowledge of policies such as anti-money-laundering or anti-corruption policies, which has to be mandated and controlled from the centre.
  • There may be strategic knowledge, driven by company strategy, which can certainly be tested in the business, with clear (and welcome!) feedback, but which needs to be owned and coordinated centrally and strategically.
  • There may be operational and tactical knowledge which is owned by the Communities of Practice, and handled within wikis and blogs and discussion forums (and indeed the Army wikis mentioned above were specifically for tactical knowledge).

So it is not as simple as saying “model 1 is old fashioned and rigid and Bad, model 3 is free and liberated and modern and cool and Good”.

It is, as is so often the case in Knowledge Management, a case of determining which model is most appropriate for which knowledge.

View Original Source ( Here.

7 failure modes for knowledge transfer failure

There are at least 7 ways in which Knowledge Transfer can fail. Here are 7 of the most common. I am sure you can suggest others.

This post is inspired by this article by John F. Mahon and Nory B. Jones, authors of the book “Knowledge Transfer and Innovation“. They identify 5 failure modes of knowledge transfer. I have added one more

1) Knowledge is transferred, but too slowly to make a difference. This is a failure in the efficiency of the knowledge management process – your “KM clock speed” is too low

2) Knowledge is shared, but in an inadequate way so that the user cannot understand it. Maybe it is written in fuzzy statements, or statements of the blindingly obvious. These are both byproducts of the curse of knowledge, whereby an expert assumes that if something is obvious to them  it is obvious to everyone else They underestimate the difficulty of transferring that knowledge to a non-expert
 and so write the knowledge in the form of bullet points or aphorisms. This is a failure of a) km training, b) KM facilitation and c) KM quality control.

3) Knowledge is corrupted by inadvertent omission – for example, as Mahon and Jones say, “your neighbor accidentally leaves out a critical step or ingredient in a recipe. When you make the dish, it is not what was intended”. This is difficult to guard against, and you need to make sure your KM system is self-correcting, so that inadvertent omissions are corrected later.

4) Knowledge is corrupted by deliberate omission – for example if it is not politically comfortable to transfer the whole truth. Mahon and Jones give the example of the Gulf of Tonkin incident – “There were actually two such incidents reported, and there is credible information that one and possibly both reports were false. Based on this erroneous knowledge, Congress passed the Gulf of Tonkin Resolution, which granted President Lyndon B. Johnson legal justification for deploying U.S. troops to Vietnam and commencing open warfare”. This is a failure of culture and therefore of leadership.

5) Knowledge doesn’t get shared at all. This is the problem of knowledge hoarding, which affects many organisations. People hold on to their knowledge, largely through fear that it will leak to competitors – either to industrial competitors, or to people within the same job who are competing for the knowledge holders budget or job.  This is also a failure of culture and therefore of leadership.

Now my two

6) Knowledge gets shared, but not used.  This is the re-use barrier – potentially the most difficult barrier in KM, and there are several reasons why people may be unwilling to re-use knowledge – it’s difficult to find, difficult to understand, they don’t trust it, or they can get away with not using it. This is a failure of many things – the KM system, the culture, the incentive system – and often comes from treating KM as a supply problem rather than a demand problem.

7) Knowledge is not co-created. We often have a simple view of knowledge transfer; that it leaves one head and enters the other. In reality knowledge is often co-created through conversation and through collaboration. Knowledge is more often co-created than it is transferred in a one-way direction.  Ignoring co-creation is a failure in the KM philosophy as much as anything else. 

View Original Source ( Here.

The curse of knowledge and the danger of fuzzy statements

Fuzzy statements in lessons learned are very common, and are the result of “the curse of knowledge”

Fuzzy Monster
Clip art courtesy of

I blogged yesterday about Statements of the Blindingly Obvious, and how you often find these in explicit knowledge bases and lessons learned systems, as a by-product of the “curse of knowledge“.

There is a second way in which this curse strikes, and that is what I call “fuzzy statements”.

It’s another example of how somebody writes something down as a way of passing on what they have learned, and writes it in such a way that it is obvious to them what it means, but which carries very little information to the reader.

A fuzzy statement is an unqualified adjective, for example

  • Set up a small, well qualified team…(How small? 2 people? 20 people? How well qualified? University professors? Company experts? Graduates?)
  • Start the study early….(How early? Day 1 of the project? Day 10? After the scope has been defined?)
  • A tighter approach to quality is needed…. (Tighter than what? How tight should it be?)
You can see, in each case, the writer has something to say about team size, schedule or quality, but hasn’t really said enough for the reader to understand what to do, other than in a generic “fuzzy” way, using adjectives like “small, well, early, tighter” which need to be quantified.

In each case, the facilitator of the session or the validator of the knowledge base needs to ask additional questions. How small? How well qualified? How early? How tight?

Imagine if I tried to teach you how to bake a particular cake, and told you “Select the right ingredients, put them in a large enough bowl. Make sure the oven is hotter”. You would need to ask more questions in order to be able to understand this recipe.

Again, it comes back to Quality Control.

Any lessons management system or knowledge base suffers from garbage In, Garbage Out, and the unfortunate effect of the Curse of Knowledge is that people’s first attempt to communicate knowledge is often, as far as the reader is concerned, useless garbage.

Apply quality control to your lessons and de-fuzz the statements

View Original Source ( Here.

Knowledge Transfer is the wrong concept – Knowledge co-creation is nearer the truth

In another post from the archives (with some updates) let’s look at the common phrase “knowledge transfer” and discuss whether this is the wrong concept.

Knowledge transfer, when illustrated graphically, often looks like the picture below – knowledge leaving one head and entering another. 

image from wikimedia commons

This model is wrong in at least 3 ways.

Firstly when knowledge is shared, it doesn’t leave the first head – it stays there. You do not lose anything when transmitting knowledge to someone else. You do not pass knowledge to someone in the same way that you pass money

Secondly, in many or most acts of “knowledge transfer” the giver also learns and gains.  A Peer Assist is a prime example – the people who come to share their knowledge often some away with more knowledge than they started.

Thirdly knowledge changes as it is exchanged. The receiver adds their knowledge to the knowledge of the donor, and makes something new and better. In fact, the concept of donor and receiver is probably wrong as well. Both parties give, both receive, and collectively create something new.

Knowledge is more often co-created than it is transferred in a one-way direction.

Think of the following examples;

  • A Peer Assist, where peers from all over the organisation pool their knowledge to create new solutions and insights for a project team. This is not a case of one group of peers lecturing to another group; it is a setting for dialogue, where the peers collectively discuss how to apply knowledge from the past to challenges of the present and future.
  • A meeting within a Community of Practice where SMEs come together to create best practice, pooling their knowledge to create something new. This again is not a meeting where people sit passively and listen; it is a setting for dialogue where practices are discussed with the intention of co-creating something better.
  • A Knowledge Retention meeting between a senior and a junior – theoretically for the junior to learn, but where skilful questioning means the senior develops new insights into the practice. Both parties learn.
  • An After Action Review where the team comes to a collective understanding of the lessons from an activity. This is not a meeting where the team leader briefs the team on what he or she learned; it is an all-hands discussion so the collective learning of the team can be identified, discussed and developed.
  • People collaborating on a knowledge asset. This is not, or should not be, someone publishing a document for another to read. It should be more like collaboration on a wiki, containing knowledge supplied from many people and from many documents, and combined into something none of the people knew individually. Or collaboration on a checklist or a procedure, making sure the checklist is regularly updated as new knowledge becomes available, so that it becomes the record of knowledge from many many sources and the means to avoid all the mistakes of the past.

In each case this is not the transfer of something from one head to another, but co-creation of knowledge, or co-learning.

This co-creation is the C in the Nonaka and Takeuchi model – the idea of Combination of knowledge, so often missing in KM programs.

Perhaps Peter Senge said it best, in the following quote

“Sharing knowledge is not about giving people something,or getting something from them. That is only valid for information sharing. Sharing knowledge occurs when people are genuinely interested in helping one another develop new capacities for action; it is about creating learning processes.”

The co-creation process therefore looks more like the picture below than the picture above.

View Original Source ( Here.

Extending SECI – 9 transitions of knowledge transfer

The SECI model is a common model in KM. This blog post from the archives suggests a way to expand this model.

One of the basic models of Knowledge Management – often discussed, frequently challenged – is Nonaka and Takeuchi’s SECI model. This is a 2×2 matrix, looking at the transitions between tacit and explicit knowledge (and the challenges to the model is often whether tactic knowledge can ever be made explicit, or whether it needs to be, or whether explicit knowledge is the same as documented knowledge).

I would like to extend this model, because when we start to work with Knowledge Management in organisations, we find that knowledge actually lies in three natural states rather than two, and that we therefore need a 3×3 matrix rather than a 2×2.

The three states are as follows;

1. Unconscious “Knowledge in the head” – the things you don’t know you know.
2. Conscious “Knowledge in the head” – the things you know you know (of course the boundary between states 1 and 2 is gradual, and more of a transition than a boundary).
3. Recorded Knowledge (captured in documents, audio, video etc).

The most powerful knowledge – the deep knowledge  that experts possess – is in state 1. However if knowledge is to be transferred easily between people, it may need to change it’s state in order to allow transfer. The 3×3 matrix above represents the 9 possible transitions.

The dark blue squares are where Knowledge Management traditionally focuses (you can see that traditionally we only cover about half of the diagram).

It should be stressed that  every one of these transitions involves loss of value and loss of knowledge. We know (unconscious) more than we can say (conscious), and we often say (conscious) more than gets captured.

Here are the 9 transitions or transfers.

  1. The transition from one person’s unconscious knowledge to another’s can be called “Emulation“. This is how a baby learns, or how a craftsman can pass deep knowledge to their apprentice – by working together over years, often wordlessly. This is effective but very slow.
  2. To make unconscious knowledge conscious requires some form of analysis – usually self-analysis, as the knower has to be deeply involved in the process. Group self-analysis, or sense-making, is a powerful technique, and a good interviewer, facilitator, coach or psychotherapist can also help make knowledge conscious. Coaching and mentoring is a useful tool in this box, as are tem reflection exercises such as After Action review or Action Learning.
  3. To record unconscious knowledge is difficult. About all you can do is record what the knower does – through videoing them at work for example – for later analysis. But to be honest, it’s not yet knowledge, as all these recorded work products have to pass back through an analysis step in order to draw out the conscious knowledge. Maybe you can call the things in this box “latent knowledge”.
  4. The transition from conscious to unconscious knowledge is habituation. At one time you were conscious of your golf swing, your fishing cast or your ability to drive a manual car, but over time it becomes unconscious.
  5. The transition between one person’s conscious knowledge to another’s often comes through conversation and discussion (particularly dialogue), and through techniques such as demonstration and teaching. Here is where discussion processes and structures such as Communities of Practice and Peer Assist become useful.
  6. The transition from conscious knowledge to recorded knowledge comes through interviewing, writing, documenting, capturing lessons – all the standard tools of knowledge capture.
  7. The transition from written knowledge to unconscious knowledge is a tricky one, but we know it happens. If you are brought up on a diet of Fox News, you end up “knowing things” that are different from those you would “know” if you were brought up on a diet of the Washington Post. I don’t have the correct term for this box, but “Indoctrination” may be a good term.
  8. The transition from written knowledge to conscious knowledge is also difficult – here we can use the term “Internalisation” for that whole chain of “Read, Mark, Learn and Inwardly Digest
  9. The transition between various forms of recorded knowledge we can refer to as Synthesis – the bringing together, combination and “making sense” of disparate recorded sources into Knowledge Assets.

Depending on the sort of knowledge you are dealing with – the deep unconscious knowledge of the experts, or the shallow knowledge of company procedures – you may need to deal with more or fewer of these 9 transitions.

View Original Source ( Here.