Why "knowledge sharing" cannot replace "knowledge management"

Can we use the term “knowledge sharing” as better replacement for the term “Knowledge Management? There are two good reasons not to do so.

image from Wikimedia Commons

The terminology debate continues to rumble on in the KM world, with many people preferring the term “knowledge sharing” over the term “knowledge management”. This is partly due to a distrust of the concept of management, or use of the “management” term especially when used in conjunction with the word Knowledge.

As Tom Davenport wrote in his article “Does Management mean Command and Control?”

“I have a problem with overly simplistic characterizations of knowledge management, and management more generally. …. The term “management” is apparently a synonym for “command and control,” and we know that’s bad. “Command and control” is top-down, mean and nasty, and headed for extinction; “sharing” is bottom-up, nice and friendly, and the wave of the future. Maybe the Yale School of Management, for example, should become the Yale School of Sharing”. (However)…if your organization really cares about creating, distributing (I’m sorry–“sharing”), and applying knowledge, you need to manage it”.

But irrespective of whether you think Management equates to Command and Control or not, there are still 2 good reasons why you cannot replace “Knowledge Management” with “Knowledge Sharing”.

Firstly, sharing is not the end of the process of knowledge transfer and application.

There is a common misconception that sharing is the be-all and end-all; that people should first Capture and then Share their knowledge (and Sharing is often taken as meaning posting a document into a repository), and that this constitutes an effective transfer of knowledge.

However KM does not work like that. KM is not about one person with knowledge making it available to others; transferring knowledge as if you were transferring a can of beans from one person to another as in the image above. Knowledge is not transferred, it is co-created.

Once knowledge is shared, as a post on a discussion forum, a lesson in a lesson management system or a comment on a wiki, then it can be questioned, tested, combined with knowledge from other sources, and synthesised into new and better knowledge through discussion and dialogue. After sharing comes synthesis.

And after synthesis comes re-use. Even if knowledge is captured, and shared, and synthesised into up-to-date, valuable reference material, it still adds no value unless someone looks for it, finds it, and re-uses it.

All to often a “knowledge sharing” approach is strong on capture of knowledge, strong on some form of sharing (usually by publishing in a public repository), but weak or absent on synthesis and re-use.

Secondly, sharing deals only with supply and not with demand.

The common approached to knowledge sharing, and to the development of a “knowledge sharing culture” tend to focus only on the supply of knowledge. They assume knowledge will be captured and shared, creating a constant supply of new knowledge, and that this is enough.

But it is not enough.

To make any exchange work, you need demand as well as supply.  In parallel with knowledge sharing you need knowledge seeking, and in parallel with a knowledge sharing culture you need a knowledge seeking and re-use culture. A constant supply of new knowledge is a waste of time unless there is a constant demand for new knowledge.

In fact knowledge seeking is actually a better place to start than knowledge sharing (even though both are needed as part of a Knowledge Management Framework). Seeking stimulates sharing, and as McKinsey found, “direct requests for help between colleagues drive 75 to 90 percent of all the help exchanged within organizations“.

You could draw the whole knowledge cycle from a seeking point of view if you want – starting with seeking, then finding, reviewing, synthesising with existing knowledge, and applying, rather than starting with capture and sharing – which can give you a different way to look at KM.

Knowledge Management is therefore much more than knowledge sharing.

Knowledge Management includes Knowledge Sharing, as well as Knowledge Creation, Knowledge Capture, Knowledge Synthesis, Knowledge re-use, Knowledge seeking, Knowledge finding, and so on. To focus only on Knowledge Sharing is to underestimate the topic, and runs the risk of creating only a partial solution.

Beware of a focus only Knowledge Sharing. Focus on Knowledge Management instead.

View Original Source (nickmilton.com) Here.

Army definitions in Lesson Learning

The Army talk about building up lessons through Observations and Insights. But what do these terms mean?

Chinese character dictionaryLesson learning is one area where Industry can learn from the Military. Military lesson learning can be literally a matter of life and death, so lesson learning is well developed and well understood in military organisations.

The Military see a progression in the extraction and development of lessons – from Observations to Insights to Lessons – and we see a similar progression within the questioning process in After Action Reviews and Retrospects.

On Slide 7 of this interesting presentation, given by Geoff Cooper, a senior analyst at the Australian Centre for Army Lessons Learned, at the recent 8th International Lessons Learned Conference, we have a set of definitions for these terms, which are very useful.

They read as follows (my additions in brackets)

Observation. The basic building block [for learning] from a discrete perspective. 

  • Many are subjective in nature, but provide unique insights into human experience.
  • Need to contain sufficient context to allow correct interpretation and understanding.
  • Offer recommendations from the source
  • [they should be] Categorised to speed retrieval and analysis

Insight. The conclusion drawn from an identified pattern of observations pertaining to a common experience or theme.

  • Link differing perspectives and observations, where they exist.
  • Indicate recommendations, not direct actions,
  • Link solid data to assist decision making processes
  • As insights relay trends, they can be measures

Lesson. Incorporates an insight, but adds specific action and the appropriate technical authority.  

Lesson Learned. When a desired behaviour or effect is sustained, preferably without external influence.

What Geoff is describing is a typical military approach to lesson-learning, where a lessons team collects many observations from Army personnel, performs analysis, and identified the Insight and Lesson. As I pointed out in this post, this is different from the typical Engineering Project approach, where the project team compare observations, derive their own insight, and draft their own lesson.

The difference between the two approaches depends on the scale of the exercise. In the military model there can be hundreds of people who contribute observations, while in a project, it’s usually a much smaller project team (in which case it makes sense to collect the observations and insights through discussion). If you are using the military model, these definitions will be very useful.

View Original Source (nickmilton.com) Here.

50 shades of knowledge management reprieved

To mark the return of this blog after a short hiatus, here is another popular post from the past, first published 5 years ago.

  color wheel
The knowledge management world is large and complex, with many different understandings of what the term means, and what it encompasses.

Here is a first-pass map of the Knowledge Management Landscape, and some of the nooks, crannies, islands and archipelagos that make up that landscape.

Or if you prefer, the 50 shades within the KM rainbow.

Lets start down the data end, where the knowledge management landscape meets the border with data management. KM’s interest in data comes from combining data through linked data, and looking for the patterns within data, though data mining, so that new insights can be gained. Where this is applied to customer data or business data, then we get into the analogous disciplines of CRM and Business Intelligence.

Next to data comes Information, where knowledge management is involved in several ways. For example the structuring of information, through classification systems (taxonomies, ontologies, folksonomies) or information tagging. Or else the retrieval of information, where knowledge management encompasses enterprise search, semantic search, expert systems and artificial intelligence. Or the presentation of information, through intranets, or portals, supported by content management. The presentation of information, as well as the creation of explicit “knowledge objects” is an important component of customer-centric knowledge management, closely allied to the creation of customer knowledge bases and the use of knowledge centred support. Knowledge based engineering is a discipline where engineering design is done based on knowledge models.

The creation of explicit knowledge is a significant part of the KM world, containing many shades of its own. Knowledge retention deals with capture of knowledge from retiring staff aka Knowledge Harvesting), lessons management deals with learning from projects, as do learning histories based on multiple interviews.

Another part of the landscape is the organisational learning corner. This abuts the border with learning and development, but is concerned with learning of the organisation, rather than learning of the individual. In this part of the KM world we find action learning, business-driven action learning, and lesson-learning, plus analogous disciplines such as e-learning, coaching, and mentoring.

Organisational learning abuts the area of knowledge transfer, where we look at dialogue-based processes such as peer assist, knowledge handover, knowledge cafe,  baton-passing, after action review, appreciative enquiry, and so on – processes that are focused on knowledge, but are closely allied to other meeting disciplines.

Knowledge transfer between people – the tacit area, or experience management, takes us into the area of networking. Here we find the communities of practice, the centres of excellence, the communities of interest, and the social networks. The latter, of course, is closely allied to social media – social media being the technology which supports social networks. Then we have storytelling, as a means of knowledge transfer, crowdsourcing, as a means of accessing  knowledge from a wide source, and collaboration as a sort of catch-all term (supported by collaborative technology).

There is a whole innovation area to KM as well – open innovation, creativity, deep-dives etc

The finally we have the more psychological end of knowledge management, where we have disciplines such as epistemology, sense-making, complexity theory, decision-making theory.

Plus of course the part of knowledge management that deals with the lone worker – personal knowledge management.

So there are our 50+ shades of knowledge management – if I have missed any, please let me know through the comments option!

View Original Source (nickmilton.com) Here.

What’s the "white space" occupied by KM?

One of the issues involved in developing the ISO standard for Knowledge Management has been the definition of the “White Space” KM occupies.

After all, if Knowledge management is to add any value as a discipline, it must cover areas not already covered by other disciplines. This was the main thesis of “The Nonsense of Knowledge Management” by  TD Wilson, who argued that KM was partly or completely a rebadging of Information Management, and therefore a fad invented by management consultants to make themselves rich (I wish!). Knowledge Management must occupy a space of it’s own, surrounded by (but not totally overlapping with) other disciplines.

So when it came to defining the scope of KM for the forthcoming ISO standard, one of the things we looked at was existing standards for existing disciplines. Again, if a KM standard is to add value, it can’t be a rebadging of an existing standard.

There are many such adjacent ISO standards, either in existence of under development:

  • There are ISO document management standards, so document management cannot (for ISO purposes) be seen as part of KM;
  • There are existing records management standards, so records management cannot (for ISO purposes) be seen as part of KM
  • There are innovation management standards under development, which means that ISO must treat innovation systems and KM systems separately, 
  • Similarly there are ISO standards for non-formal training and learning, and for content management as it applies to product documentation.
In between these existing standards though there is some white space for KM.
  • There are no standards that address the value of tacit knowledge, and its expression, sharing, transfer and re-use;
  • There are no standards that address the externalisation or documentation of tacit knowledge, and its internalisation and application by others;
  • There are no standards that address the combination of knowledge from many sources in order to create new ideas and new knowledge;
  • There are no standards that address the disposal of old knowledge (which sometimes is more dangerous than no knowledge at all).
So there is space for Knowledge Management as a discipline; namely a discipline based on Knowledge, rather than on information and documents; which recognises that some knowledge may be transferred or retained in documented form, but which addresses the contents of the document rather than the way it is handled as a record.
That is the discipline which we should shortly see released in the draft Knowledge management standard: ISO 30401.  I will let you know when it is released, so you can view and comment on the standard, ready for the next phase of committee work.

View Original Source (nickmilton.com) Here.

"Time out" for knowledge

The concept of “Ba” in knowledge management is often assumed to represent a physical or virtual space. But what if it represents a time, rather than a space?

The term Ba was introduced, in the KM context, by professor Nonaka as a place or a shared environment that serves as a foundation for the creation of individual and collective knowledge. Nonaka and Konno talk about four Bas – one for socilaisation (face to face), one for externalisation (peer to peer), one for combination (group to group) and one for internalisation (at the work site).  The Ba is a learning environment where interactions happen.

Ba is a Japanese term and as such, fuzzy in its meaning. In the west, Ba is often identified with Space – physical or virtual – and applied to office design, or to online platforms. Westerners see Ba as physical; for example wikipedia defines Ba as

“a physical or virtual collaborative space, where participants feel safe and exchange insights.”

For me, there is another dimension of Ba which is more important, more valuable and often overlooked, and that is the time dimension.

Let me explain what I mean.

We recently conducted a knowledge management assessment of a busy company, and during the assessment we were asking about the transfer of knowledge through conversation.

“Oh, we talk all the time” they said. “We have operational meetings every morning, team meetings once a week, we talk with the suppliers every week, our boss has a briefing once a day. we are always talking”. 

“But what do you talk about?” we asked. It turned out that they talk about progress, about issues, about plans, but never about what has been learned, or what needs to be learned. 

“Why don’t you ever talk about learning?” we asked them. 

“Oh, we are too busy for that” they said. “We used to have meetings with other teams to find out what they were doing and why, but we got too busy and stopped that”. 

So there used to be “safe time” (Ba) for interactions and for learning from each other and exchanging insights, but it was not protected, and it vanished.

The issue in a busy company is not physical space; it’s protected time.

What this company needs to do, and what so many busy companies need to do, is to carve out safe time for knowledge management, otherwise it will be kicked off the agenda by busy short-term work, and the long-term value of learning will be lost. They need to be able to call “time-out” to reflect and to learn. Sure, we need the physical space, but more important (in many cases) is the protected shared time, dedicated to KM.  This can be

We need the time dimension of Ba – time dedicated to talking about knowledge, when people can feel safe and exchange insights.

View Original Source (nickmilton.com) Here.

Why some knowledge is also information, also vice versa, and what to do about it.

Not all knowledge is information, not all infomation is knowledge. However some knowledge exists also as information, and therefore needs to be managed by both disciplines in parallel.

This blog post is about the knowledge continuum, the relationship between knowledge and information, and how information management and knowledge management both handle the overlap between the two. This is still a thorny topic, and there are still organisations that think information management and knowledge management are essentially the same thing.
But they aren’t, and here’s why.

The Knowledge continuum
Let us assume that we are talking about knowledge in the sense that it refers to human ability, “know-how“, the ability to make decisions and take actions. Immediately we run into the deficiencies of the English language, because in English we also tend to use the word Knowledge for the accumulation of facts and information –  “know-what” in other words. Where in other languages these two concepts – know-how and know-what – have two different names (Savoir and Connaitre, Kennen and Vissen etc). But if we assume that we are talking about know-how, then this comes in a continuum, as  shown in the figure above, and as described below.

The continuum

  1. There is the knowledge you don’t know you have – the deep tacit knowledge, which is intimately linked with the person themselves, and which can only be deployed by deploying the person;
  2. There is the knowledge you know you have but haven’t yet expressed – explicit knowledge by the original definition (knowledge that can be readily articulated, codified, accessed and verbalised), or sometimes referred to as implicit knowledge. This knowledge can be transferred form one person to another by bringing them together in conversation; 
  3. This knowledge then, in conversation, moves to the next stage of the continuum and becomes knowledge you have expressed but not recorded. This is explicit uncodified knowledge – spread through conversation, and open to being recorded.
  4. Finally there is knowledge you have recorded – explicit codified knowledge in the form of documents or recordings which contain know-how, and which can guide or advise others towards action.  Here are your recipes, your tips and hints, your guidance notes, training material, best practices, standard operating procedures and checklists. 

As knowledge moves from the left of the continuum to the right, it loses richness and context, but gains in both manageability and robustness. By robustness I mean that much of the deep tacit knowledge may be a combination of real knowledge, options, biases and falsehoods (see here for a discussion of tacit knowledge and cognitive bias) and it is only through conversation and synthesis that these opinions are tested and become validated as knowledge. 

Various people draw the boundary between knowledge and information at different places on this continuum. Some draw it between stages 2 and 3, and claim that as soon as something is spoken it has become information. Others draw it between 3 and 4, claiming it has become information once it is codified. I would prefer to say that at stage 4, it is both information and knowledge. It is information which conveys knowledge in a written form, just as in stage 3 it is conversation which conveys knowledge, or knowledge in a spoken form.

Information and Knowledge are not exclusive alternatives in some sort of Western Dualism, and something in our stage 4 above can be both information and knowledge.

However there is one more item on our continuum.

  1. The codified explicit knowledge, which is held in the form of documents, finds itself rubbing shoulders with other documents – the documents which are not codified knowledge at all.
By “not codified knowledge” I mean they do not address know-how and do not transfer knowledge of what to do or how to do things.  An invoice, for example, allows you to know what price something was invoiced for, but it does not help you know how to become a better invoice clerk. A record of a meeting allows you to know what was discussed in a negotiation, but not how to be a better negotiator. These are documents, but do not carry knowledge.
I have drawn the boundary between codified knowledge and “not knowledge” documents above as a hard boundary, but there may be some overlap between then – there may be documents that contain SOME knowledge, such as project reports with a “lessons learned” section, for example.

The grey zone, and the relationship between information management and knowledge management.

We can see that there is a class of knowledge which is arguably both knowledge and information – class 4 above. This is the class that causes much of the confusion, with people assuming that because this knowledge is carried as documented content, then management of content equates to management of knowledge.

However I would argue that class 4, being both information and knowledge, needs to be addressed by both disciplines.

  • Codified knowledge, because it is in the form of information, is managed as information. It needs to comply with the IM requirements and needs to be categorised with the correct metadata using the correct taxonomy or ontology, and needs to follow the rules of information architecture and information lifecycle. 
  • Because it contains knowledge, it needs to comply with knowledge management, and the knowledge which the document contains needs to be valid, up-to-date, and structured in such a way as to be maximally useful to the reader. 
Knowledge Management addresses the content of the document, Information Management addresses the container – the document itself. Both the document and its contents are managed, but separately by the two separate disciplines. 
I think this insight is what we need to fully understand how the two disciplines work together, and I would summarise it as follows:
  • Knowledge Management and Information Management are two separate but complementary disciplines. 
  • Knowledge Management focuses on Knowledge, with the aim of developing and deploying collective know-how for business improvement. Information Management focuses on information, with the aim of getting the right information to the right people at the right time. 
  • Where knowledge is carried in the form of information, as codified knowledge within documents, then to these documents both disciplines are applicable. Information management is concerned with management of the document itself, knowledge management with the contents of the document.

View Original Source (nickmilton.com) Here.

KM definitions – good, bad and ugly?

Two years ago I blogged an analysis of a list of KM definitions. Here is a fresh look at a new list.

Wod Clud from the KMAus list
The analysis of the previous list showed a few “definition clusters”, as well as a definitional split between those who define KM in terms of knowledge, and those who define Km in terms of information.
The new list, which allows us to revisit this analysis, was created by KM Australia, and you can find it here. It contains 183 entries, but a couple are duplicates and many are not definitions, but commentary on (for example) why definitions are difficult. About 147 entries are real definitions.
The first thing we can do with this list is create a word cloud, shown here.

The word Knowledge is prominent in the list, as we might expect in a series of definitions about Knowledge Management. However Information is quite prominent as well, possibly the joint second largest term, together with “organisation”.

So lets start to subdivide and categorise the definitions. I categorised them by the main subject noun – such as “Knowledge Management is the management/sharing/capture/organisation of X” where X is the subject noun. Then I counted how many times the following nouns appeared as the subject, either individually, or as a shared subject. 
  • Knowledge
  • Know-how
  • Experience
  • Intellectual (as in intellectual property, intellectual assets)
  • Innovation
  • Information
  • Data
I plotted the results below in a cross-plot, so we can see the frequency of these nouns individually or in pairs.
  • You can see, for example, that 63 definitions used solely the word “knowledge”, such as “To harvest and store Knowledge within the company to increase productivity “. 
  • 1 definition includes “knowledge” and “know-how” as in “(managing) Your Knowledge and your Know-how : An Asset to improve every day”
  • and so on.

There were many examples of 3 or 4 words appearing in the same definition, but seldom the same 3 or 4 words.

Knowledge/information/experience             2 definitions
Knowledge/information/data                       3 definitions
Knowledge/information/know-how              1 definition  Know-how/experience/information              1 definition

These are not included on the matrix

Definition clusters

The matrix shows exactly what we saw two years ago – a set of “definition clusters” which I have marked on the matrix in colours, with green, amber, red representing how much I personally support these definitions.

The Knowledge/know-how/experience cluster

The green cluster contains the definitions I personally prefer, which define KM in terms of knowledge and (to a much lesser extent) experience and know-how. For me these are GOOD definitions. Management of knowledge should, at its heart, focus on Knowledge.

The KID cluster

In the orange cluster, top right, we see definitions which mix the terms Knowledge, Information and Data. I feel these definitions should be treated with caution, as they blur the boundary between KM, IM and DM. Certainly there are times when knowledge is transferred in documented form, and these documents are subject to information management processes. however KM is concerned primarily with the content of the documents, and how this may be used to help another person develop their knowledge. IM is concerned more with how these documents are stored, characterised, and made findable.

The intellectual cluster

The orange cell is where we see definitions based on “intellectual assets” or “intellectual capability” (an example would be “Management of the intellectual property of the organisation – using many and varied techniques”). I see what these definitions are getting at, but worry that they leave open the question “what is intellectual property” and they run the risk of focusing on patents and intellectual property.

The information/data cluster

In the red cluster we see 30 definitions that do not use the term knowledge at all, for example “Recognition and appropriate shared use of corporate information”. Such definitions are, I suggest, just plain wrong and should not be used. Any definition that focuses on what you do with information, is surely a definition of information management, For example we see in a couple of places on the list definitions which say “Right information to the right person at the right time” – which is an Information Management definition according to the AIIM. These to me are either BAD definitions or downright UGLY

In conclusion the confusion between KM and IM remains, with about 20% of the definitions on this list talking only about information and data, and not about knowledge at all. 

However about 50% of the definitions are firmly in the knowledge domain (the green sector) which is an improvement on the 40% in the green cluster 2 years ago.

Please note that in no cases are the terms knowledge and Information defined.

View Original Source Here.

How to avoid Dualism in Knowledge Management

We tend to divide Knowledge Management into opposing categories. Sometimes this is useful, but often this dualism is illusory.

Image from wikimedia commons

Dualism is the idea that, for some particular domain, there are two fundamental kinds or categories of things or principles. It is an “either-or” mindset, which seeks to separate things: mind and body, for example, or good and evil, or Yin and Yang.

Dualism is often a western mindset, and many eastern philosophies take a different view, where apparently opposite or contrary forces like Yin and Yang may actually be complementary, interconnected, and interdependent, and may give rise to each other as they interrelate (see picture!).

There has been a lot of dualism imposed on Knowledge Management – seeing things as alternatives rather than parts of a spectrum, or parts of a total system. For example, consider the following Knowledge Management questions, all of which I have heard asked:

  • “Which is more important – Questions or Answers?”
  • “Which strategy are you taking – Connecting or Collecting?”
  • “Is KM best introduced Top-down, or Bottom up?”
  • “Is KM all about People, or Process, or Technology, or Governance?”
  • “Which should I focus on – Conversation, or Content?”
All of these questions assume dualism, and only make sense if you assume dualism.
Now consider the following non-KM questions, and tell me if they make sense:
  • “Which is more important – the positive terminal on a battery, or the negative?”
  • “Which approach do you take when walking, using your right leg, or your left leg?”
  • “Is it better to begin with breathing out, or breathing in?”
  • “Which came first, the chicken or the egg?”
  • “Is a coin all about the Heads, or the Tails?”

These second questions are ridiculous, and we know they are ridiculous because they try to apply dualism to something we know is a system – an electrical current, breathing, a coin, chicken-breeding and bipedal locomotion.

For me, the first set of questions are equally ridiculous. They also are applying a dualistic mindset to something that is a system.

  • Questions and Answers are both equally important (or equally unimportant) in Knowledge Management. They are Demand and Supply, and both are needed for the flow of Knowledge. One without the other is pointless.
  • You should be developing a Connecting AND Collecting strategy. These are not alternatives.
  • KM is best introduced Top-down AND Bottom-up. Both the Top and the Bottom are stakeholders and both need to be involved.
  • KM is all about People, and it is all about Process, and it is all about Technology, and it is all about Governance. These are the 4 legs on the KM Table.
  • You should focus on Conversation AND Content. Content is something to talk about, Conversation is where Content is born and where it is Tested

In each case the apparent opposties may actually be complementary, interconnected, and interdependent, and may give rise to each other as they interrelate – juts like Yin and Yang.

Beware the Western Dualist Mindset, that loves alternatives and opposites. KM is less about “either-or” and more about “both-and”.

View Original Source Here.

What the C box in Knowledge Management SECI really means.

Most of us are familiar with the SECI model from Nonaka and Takeuchi, but sometimes forget that C stands for Combination, not Collection.

Image from wikimedia commons

The Nonaka and Takeuchi SECI model for knowledge creation is well known in the KM world, with its 4 components of  Socialisation, Externalisation, Combination and Internalisation.  Nowadays many people assume that Externalisation means Documentation (which is not strictly true), but what about the C box? What do we assume this means?

According to the Wikipedia site linked above. the C box involves

Explicit to explicit by Combination (organizing and integrating knowledge), combining different types of explicit knowledge, for example building prototypes. The creative use of computerized communication networks and large-scale databases can support this mode of knowledge conversion. Explicit knowledge is collected from inside or outside the organisation and then combined, edited or processed to form new knowledge. The new explicit knowledge is then disseminated among the members of the organization

The key word here is Combination. Explicit knowledge gets combined with other explicit knowledge, seeking out links and removing duplication and contradiction, and culminating in better knowledge or even new knowledge.

According to Nonaka, the combination mode of knowledge conversion is ‘a process of assembling new and existing explicit knowledge held by individuals into a knowledge system’ – a systemic approach to new knowledge. It involves the combination of what is known.

The C box does not stand for”collection”.

Collecting databases of documents is not part of the SECI development model (although collection is a precursor to combination). It actually involves synthesis – connecting, combining and synthesising knowledge into something new, integrated and better.

Combination might be the Wiki article that summarises and synthesises a whole series of reports, or it might be the improved procedure that comes from combining new Lessons Learned, or it might be the checklist created by a Community of Practice discussion.

If all you are doing is collecting documents, then your knowledge flow and knowledge development has got stuck at this stage,

The Combination of knowledge is a powerful part of the model, and is often overlooked when an organisation focuses only on collecting and tagging documents into a repository.

View Original Source Here.

3 arguments in KM we may never resolve

Here are three perennial KM arguments. Do they matter? (this is a reprise of an original blog post from 5 years ago)

Mockingbird argument, from wikimedia commons

Over the 20 years that we have been doing knowledge management, there has been a number of recurrent arguments that appear regularly, often several times a year. Watch the linked-in forums; you will see these arguments popping up like mushrooms. I call them cul-de-sac arguments, as they lead us nowhere. They are never resolved, and they make little difference to pragmatic knowledge management.

Here is the first and the biggest.

Can you manage knowledge?

This argument often comes about because people assume that “knowledge management” means “the management of knowledge”. Given that knowledge is intangible, they feel that it cannot be controlled as a “thing”, and that without control, there can be no management.

This argument is debated around and around and around and around, and usually ends up with the position that “it depends what you mean by knowledge, and it depends what you mean by management”. Often the argument is an emotional one, driven by the feeling that “Knowledge is Good, Management is Bad”, and that we ought to find another term. “Knowledge Sharing“, perhaps.

My position is that it doesn’t matter. The validity of “Knowledge Management” doesn’t depend on whether knowledge is a concrete object to be controlled, any more than the  validity of “Reputation Management” depends on whether reputation is a concrete object to be controlled, or that the validity of “Risk Management” depends on whether risk is a concrete object to be controlled.

The point is that you can do some really useful things through Management, which enable the flow and re-use of Knowledge, and which deliver real value to an organisation. It’s “Management with a focus on Knowledge“, and that’s enough to call it Knowledge Management as far as I am concerned.

Here’s the second

“If you write it down, is it still knowledge?”

Many hours have been spent arguing whether knowledge can ever exist outside the human head. Some say “Yes, it’s explicit knowledge”. Others say “No, it’s information”.

This argument is seldom resolved, but as far as I am concerned, it doesn’t matter. It is possible to help people understand how to do things through the transmission of the spoken or recorded word. You can add a huge amount of value this way, no matter what you call the medium of transmission (explicit knowledge, or knowledge-focused information). There is a loss of value when things get written down, but where does that loss turn knowledge into information? Is it

  • when you formalise your thoughts into coherent form?
  • when you speak your thoughts?
  • when you record what you speak onto video?
  • when you write a transcript of that video?
Nobody knows, and trying to pinpoint the step at which knowledge becomes information, is irrelevant to the fact that you can add value to an organisation (in many cases) through written transmission. It’s seldom the best way to transfer knowledge, but sometimes its the only practical way.
Here’s the third.

“What is knowledge?”

This is an argument that gets very philosophical, very quickly. Plato is often quoted, along with Senge, and other philosophers. The “justified true belief” definition is popular, but even this only covers propositional knowledge, and not other types of knowledge. Nobody can ever agree which definition is correct, nor which philosopher is authoritative.
I don’t think it matters.

You don’t need to agree on the definition of an electron, to be able to create an electronic circuit which does useful things like lighting a lamp or ringing a bell. Similarly you don’t need to agree on the definition of knowledge, to be able to help knowledge flow in order to do useful things like solve a problem or improve a process. You don’t need to define “a thought” in order to think, you don’t need to define “music” in order to sing, and you don’t need to define “knowledge” in order to do knowledge management. Knowledge is hard to define, but its not that hard to deliver real value through knowledge management.

So the answer is “we don’t really know, but see what we can do with it!”

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