"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!”

View Original Source Here.

Knowledge, Justified True Belief, and David Brent’s dance

If Knowledge is Justified True Belief, then what does “Justification” entail?  A recent New Scientist article, and a BBC charity video, give us some pointers.

BBC Comic Relief charity video including Ricky Gervais’ character “David Brent”

The April 1, 2017 edition of New Scientist magazine has the theme of Knowledge, and contains a set of Knowledge-related articles, the first of which explores the definition of Knowledge as “Justified True Belief” (aka the JTB definition).

I am not an epistemologist, but from what I read there are many type of knowledge, and this definition only applies to one type.  There is Propositional knowledge (“I know that Paris is the capital of France”), there is Acquaintance knowledge (“I know (am acquainted with) Paris”), and there is Ability knowledge or know-how (“I know how to drive in Paris”).   In other languages there may be different words used for these different types of Knowing, which is why Knowledge is often a term lost in translation. The Justified True Belief definition applies only to Propositional Knowledge.

For propositional knowledge, the three parts of Truth, Belief and Justification are important. To know something you must first believe it, and for Knowledge to be factual it must by definition be true, or else it is falsehood (although the definition of True is not easy. Given the half-life of facts, “True” often means “True for now, as far as we know”). However Belief is not enough, and that is what brings us to David Brent, and the question on whether he really knows how to dance.

Illusions of belief and David Brent’s dance

Most of us believe things that are not true, and in particular overestimate our own Ability Knowledge. For example,

  • In a survey of faculty at the University of Nebraska, 68% believed they were in the top 25% for teaching ability, and more than 90% believed they were above average. 
  • 87% of MBA students at Stanford University believed their academic performance was above the median. 
  • In ratings of leadership, 70% of US students put themselves above the median. 
  • In ability to get on well with others, 85% of students put themselves above the median and 25% rated themselves in the top 1%.
  • 93% of the U.S. students and 69% of Swedish students in a survey put themselves in the top 50% for Driving Abiility for safety,
  • in another survey almost 80% of participants evaluated themselves as being an above-average driver.

This is the “Superiority illusion” described by Wikipedia. We consistently overestimate our Ability Knowledge, and the estimates above are of course nonsense. 80% of people cannot be above average, and 25% cannot be in the top 1%.  To make things worse, it is often the people who know the least, who overestimate their knowledge the most (the Illusion of Confidence).

Ricky Gervais’ comic creation David Brent is funny largely because he consistently overestimates his own ability, and this becomes very obvious to the viewer in the embarrassing situations that follow.  In the video above,  he honestly believes he not only knows how to dance, but knows how to dance better than the professional.

It is his firm belief, but is it Knowledge? Is it justified? We can see, through our own reaction and that of his Office colleagues from 3 minutes into the video, that his self-knowledge is in fact totally unjustified, and that it is false opinion, and not knowledge at all.

So why is this important to Knowledge Management?

Knowledge management seeks to improve the Ability knowledge of knowledge workers in the organisation, and thus help them perform better. It requires some way of sharing, co-creating and transferring knowledge – making it more widely available than just leaving it in the heads of the experts. But how much of the expert knowledge is justified? And how much is “David Brent” knowledge – asserted with confidence, but actually false?  Just because an expert confidently believes something, does not mean it is true. 
When seeking to transfer knowledge, I think that we often (or maybe always) need to transform Ability knowledge and Acquaintance knowledge into Propositional knowledge. An expert can be able in a topic and acquainted with a topic, but to teach or coach a non-expert, they usually need to transfer a proposition like “I know this is a good, or useful, or recommended way to do something”, or “I know that this is a bad, or dangerous, way to do something, which you should therefore avoid”. (I have to say that I could well be wrong here, not being an epistemologist).
Once you turn your knowledge into a proposition, it needs to be justified.
  • Teaching material should be justified as “good things to learn from”
  • Tips and Hints should be justified as “good things to consider”
  • Recommended practices should be justified as “approved practices to follow”
  • Guidelines and standard procedures should  be justified as “as far as we know at the moment, the most reliable way” to do something.

Justification comes through two mechanisms:

  • Justification through experience. Know-how knowledge is justified if it reliably results in above-average performance. The justification requires not just a correlation between the knowledge and the performance, but a justifiable causal link. Saying “I did X and my project succeeded, therefore doing X will help project success” is no more justified than saying “I wore red socks to the football and my team won, so wearing red socks will help team success”. 
  • Justification by the community of peers and experts. Once the community agrees that “doing X is recommended, as a way of enabling project success” you have community justification. 
These two mechanisms are also seen in the scientific method, where scientific results should be repeatable, and externally reviewed. David Brent’s dancing would not be justified, as it would consistently by rejected by any dancing community as being repeatedly awful. 
We need deal with the issue of justification in our own Knowledge Management programs, lest we end up with unreliable knowledge, the equivalent of David Brent trying to teach others how to dance. Because if it’s not justified, it’s not knowledge.

However we also need to recognise that justifying knowledge is not an easy thing to do, and that any justification is probably only provisional.  As the New Scientist article concludes:

Various attempts have been made to tighten up the standards of justification, and provide a definition of knowledge everyone can agree on. (However) all these epistemological investigations point us to one fact that we are wont to forget: that knowing something is a far richer, more complex state than merely believing it. The ability to distinguish between fact and opinion, and to constantly question what we call knowledge, it vital to human progress and something we cannot afford to let slip”.

View Original Source Here.

"Knowledge Worker" – an illustration and definition

Peter Drucker introduced the term “Knowledge Worker” – but what exactly IS a Knowledge Worker?

Image from Wikimedia Commons

When Drucker introduced the term in 1959, in his book “Landmarks of Tomorrow”, he was primarily writing about people working in IT – the programmers, systems analysts, academics and researchers.  However this was before the field of Knowledge Management was developed, and as Knowledge managers we often see the Knowledge Workers as one of our primary stakeholder groupings.

So we need to know who the knowledge workers are, and how they differ from other workers.

Here is an illustration that might help.

When my wife and I first moved into our current house, we employed a local gardener. He was a very nice fellow, very happy and cheerful, but he knew nothing about gardening.  

 He was very good if you gave him detailed instructions, and would work hard mowing the lawn or trimming the hedge. However anything that required decision or judgement, was risky. There was the day that he weeded out all of the newly-planted border plants. There was the day my wife left some house plants by the car to take into school, and an hour later found them all planted out in the garden. There were many other examples of small scale garden disasters, and eventually we realised that we would have to replace him, as both of us work full time and are not able to supervise a gardener to the level that this guy required.   

Now we have a new team of gardeners. They are highly knowledgeable. We can give them a broad direction, such as “tidy up this border” or “prepare this area for soft fruit”, and they will do it, often adding bits that we had never considered, or giving us useful advice along the way. Sometimes they will even say “No, we shouldn’t be doing that, that’s not going to work; we should do this instead”.
The new team costs more than twice as much, on an hourly basis, as the first guy. That’s because they are knowledge workers, and he effectively was a manual worker. 

The simplest definition of a knowledge worker is “somebody who knows more about their job than their supervisor/client does”. (Or perhaps I should have said “Knows, or can find out,”).

 So instead of the client or manager providing the knowledge and the worker providing the labour (gardener number one), the client/managers provide the direction and they provide both the knowledge and the labour (gardening team number two).  The Knowledge Worker takes over much of the task-related decision making from the manager/client, applying their knowledge to make correct decisions.

Because a Knowledge Worker uses knowledge as a core resource for doing their job, Knowledge Management can increase the productivity of the Knowledge Workers by providing them better access to the knowledge resource.

So in our story, the first guy was not a knowledge worker, and we had to tell him in detail what to do, and sometimes how to do it. The current guys sometimes tell us what they should be doing, and always know better than us how it should be done. Also in this we can see the value of the knowledge, represented by the difference in the two hourly rates. The asset that the new guys bring is their knowledge, and we need to pay double the base rate in order to get access to it.

Being a Knowledge Worker is no longer the preserve of the IT staff. Anyone who makes decisions and judgments for a living can be a Knowledge Worker – an engineer, a doctor, an architect, an oil driller, or a consultant.

In fact, even a gardener can be a knowledge worker.

View Original Source Here.

Where does knowledge come from? ( a post from the archives)

Here is another blog post from 6 years ago, which is worth revisiting – the question of where Knowledge comes from.  This post generated a lot of dicsussion last time, largely because I was challenging a popular and common model. See what you think.

In most of the Knowledge Management training courses I run, I ask the question “where does knowledge come from?”

Always, every time, the first answer I get is “Experience – Knowledge comes from Experience”.  “Knowledge comes from Information” is never the first answer. Maybe the second, or third, or fourth, but never the first.

If you don’t believe me, try it yourself. Ask people “where does knowledge come from”? and see what they say.

So why do we persevere with the Data/Information/Knowledge pyramid? You know what I mean – that common diagam that asserts that knowledge comes from information, and that information comes from data. This relationship is not aligned with the majority view of where knowledge comes from.

We could in fact come up with a different pyramid, shown here, where experience leads to knowledge, knowledge leads to decisions, and decisions lead to action.

The great thing about this version of the pyramid, is that action then leads back to experience. And if we can share the experience from many actions, we can build shared knowledge which others can use to make correct decisions.


So the pyramids stack, as shown below.

If you believe that knowledge comes from experience, and shared knowledge comes from shared experience, then your KM approach will be based on review and transfer of experience, connection of people, and conversation.

This contrasts with approaches based on the Data/Information/Knowledge model, which can lead to Knowledge Management being seen as an extension of information management and data management, resulting in a belief that organising and aggregating information somehow turns it into knowledge.

Instead of Knowledge Management being seen as an extension of information management, let’s rather look at it as an approach of sharing experience in order to make better decisions and to take better actions.

(I followed up the original blog post with an interesting online poll, described here and results shown below, where only 6% of respondents believed that Knowledge comes primarily from information)

View Original Source Here.

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