Wednesday, 27 July 2016

Knowledge Management, a term lost in translation

Here's another post from the archives, which makes the case that much of the confusion around Knowledge Management may be due to an uncharacteristic deficiency in the English Language. 

Lost in TranslationKnowledge Management has always been in a state of confusion. There is no established understanding of the term; instead there are conflicting fields vying for the label. Library science, web 2.0, engineering KM, storytelling, lesson-learning; on a good day, these can be seen as clusters within a distribution or characters within a crowd, while on a bad day they are fierce combatants in a turf war, with IT vendors on each side adding to the noise and smoke.

Why the confusion? Largely, I would suggest , because of a strange deficiency in the English language.

In English, unlike in many other languages, we have only one verb for "Knowing" and only one noun for "Knowledge". Other languages have two words; one of which means "intimate knowledge, acquaintance, knowledge as capability, know-how", the other means "knowledge of facts, rote knowledge, know-what". Savoir and Connaitre in French, Kennen and Wissen in Germany, Kunne and Vite in Norwegian, and so on. Vestiges remain in dialect ("Do you ken?") but mostly the distinction between the two in English has gone.

Between these two words there is a world of difference. Someone might say  "I know Paris" ("Jeg er kjent med Paris"), someone else might say "I know the capital of France" ("Jeg vet hovedstaden i Frankrike"). The second person might be useful in a very easy pub quiz, but the first is the person you want as a guide to the best restaurants, hotels and sights.

It is the first type of knowledge that gives power ("savoir, c'est pouvoir") and creates an economy ("économie du savoir"). That is the Know-How knowledge, that deals with acquaintance and capability; that directs action and delivers business result. Knowledge Management focused on Know-How looks at improving the competence of the organisation by giving people access to the knowledge they need to make the correct decisions.

The second type of knowledge, the Know-What knowledge is close to Information, and managing "Know-What" gets very close to content management, to Information Management, or to Business Intelligence.  It is the marshalling of facts. 

Unfortunately, although it is "Savoir" that gives Power, Knowledge Management is too often translated as Connaitre (Gestion de Connaisance, Wissensmanagement, etc). The acquaintance and competence is lost in the lists of facts.

Two meanings in one word

English usualy has so many words, reflecting subtle variations in meaning. With the word "Knowledge", however, we have two meanings hidden in the one word; and as an outworking, we have two views of Knowledge Management. We have on the one hand a meaning that carries connotations of power, economy and capability, and on the other a discipline that all too often focuses on orgainsing information.  One looks at know-how; knowledge as capability. The other looks at know-what; knowledge as facts. The differences between the two are lost in translation, as we struggle over how to manage one word, with two meanings.

If we could have KnowHow management and KnowWhat Management, Gestion de Savoir and Gestion de Connaisance, Kennenmanagement and Wissensmanagement, then the turf war would subside, with the Storytellers and the learners-from-experience working under one heading, and the content managers, librarians and SharePoint vendors working under the other.

My own life in Knowledge Management has always been in the service of the first word - Know-How, as that is where I see the value, but I really wish we had the two words and therefore the two disciplines!

It would make life so much less confusing. 

Tuesday, 26 July 2016

Knowledge management for chefs, or for recipe-followers?

People often use the analogy of chefs and recipe users within Knowledge Management, frequently arguing that chefs are liberated by knowledge, and recipe-followers are straight-jacketed by "best practice". True to form, I challenge this view. 

ChefsBeing a chef, in KM terms, is often seen as "good" - creative, relying on tacit knowledge, at teh cutting edge of their craft.

Being a recipe-follower, or a user of best practice, is seen as "bad", and you will find many KM sites that use the term "best practice" as a boo-word.

However in the world of business there are places in Knowledge Management for "chefs", and places for "recipe followers", and the KM practitioner needs to know which approach to use when.

Firstly, for mature knowledge, especially with a high turnover of new staff, you primarily need people to follow recipes. You don't need to be a chef to make a white sauce, or to boil an egg. However even for this basic stuff, the complete beginner may need a beginners guide to follow (see Delia Smith's recipe "How to boil an egg").  The newest people joining your company will need a recipe book for mature knowledge, just to get them started on the basic things.

Where knowledge is mature, following a recipe can be a far more effective strategy than calling in a chef.

For some companies, the primary KM problem is educating the new people, because either of massive growth or of massive churn. The combination of rapid onboarding, rapid networking, and very good explicit guidance, needs to be part of the KM strategy  (for example in the Chinese car industry, where the average age of the engineers is 23, or in telecom businesses where the annual churn rate may approach 40%). So to bring these new people up to speed with mature knowledge, they need a recipe book to follow, as well as access to chefs when things go "off-recipe".

Secondly, creativity may be crucial, but so is productisation. A chef may have a brilliant idea, but the most successful industries are not always those with the best ideas, but the ones that bring those ideas rapidly to market. Once the chef has the new recipe, the recipe followers can rapidly spread it through the market and capture the market share.

Also there can be good business in following a recipe - McDonalds, Taco Bell, Pizza hut, to name but a few, make a global business out of it. For purely financial reasons, a share in McDonalds is probably a better bet than a share in Gordon Ramsay inc (though these might be outweighed by other reasons). A commercial business needs creative poeple to come up with the new ideas and new products, and then needs an army of people following them, to get these ideas to market.

Thirdly, for the most critical knowledge, even a chef follows a recipe. Think of an experienced airline pilot taking off from heathrow. He or she goes through the pre-flight checklist step by step, "following the recipe". If I were on a plane, and the pilot came on the intercom and said "Ladies and gentlemen, I am a highly knowledgeable pilot, I have decided not to bother with the preflight checklists today" then I would expect there to be an instant mad rush for the exits.

Or a surgeon, with the pre-operational checklists described in Atul Gwande's book, which I covered in this blog post on checklists. As I say in the post, most jobs nowadays are incredibly complex. The human brain can only remember so much at one time, and suffers easily from overload. Most mistakes are made, not because we don’t know what to do, but because we forget (or skip) a crucial step, especially in emergency situations. We need to be reminded of what we know, and what we need to remember. Checklists (recipes) force us to stop and review, remind us of what needs to be done, take us through the critical steps, ensure we remember the right things, ensure we ask the right questions, and ensure we have the right conversations. And updates in checklists as a result of new knowledge, can remind us to do new things.

Fourthly, too many chefs spoil the broth. Every kitchen needs a chef, then they need some sous-chefs, then they need a whole stack of people to follow recipes and follow orders. SImilarly every organisation will contain a whole spectrum of knowledge workers, and on each stage of their knowledge journey, they need their knowledge delviered or developed in a differrent way. We all start off as recipe followers, some of us end up as chefs, but we are all knowledge workers and Knowledge Management needs to address all our needs.

Monday, 25 July 2016

Making best use of the human brain in Knowledge Management

I have long argued that the human brain is a poor long term store for Knowledge. Here are the three cases where it's the best store there is.

Image from wikimedia commons
The poor human brain gets a bit of a bad press at times. The cognitive biases that plague us all are becoming well known and popularised in many books, and we recognise the cognitive illusions that get in the way of effective use of knowledge, such as

With such illusions as these, can we trust the memories in our heads?

However a recent post on the Farham Street blog, based on this book by Daniel Schacter makes the point that the human brain works marvellously well in getting us through life, by selecting automatically what we remember and what we don't.

It makes the point that

"Our brain has limitations, and with those limitations come trade-offs. One of the trade-offs our brain makes is to prioritize which information [knowledge] to hold on to, and which to let go of. It must do this — as stated above, we’d be overloaded with information without this ability. The brain has evolved to prioritize information which is: 
  • Used frequently 
  • Used recently 
  • Likely to be needed"

The converse of this is that knowledge which is used infrequently, was used some time ago, and which we did not realise was likely to be needed, gets forgotten.

This is exactly the knowledge which needs to be documented, lest we forget.

The current knowledge is best left in human brains, connected into Communities of Practice, where the knowledge can be shared, improved, discussed and kept fresh.  The occasional knowledge should not be left in the human memory without augmenting this somehow through collecting, recording and structuring it in Knowledge Assets, so that it is given a shelf-life which the human brain cannot give.

Our responsibility as knowledge managers is to work out which knowledge to deal with through connection, and which through collection.

Sunday, 24 July 2016

Knowledge transfer requires interactions between people (quote)

Picture from
“Successful knowledge transfer involves neither computers nor documents but rather interactions between people.” 

Tom Davenport

Saturday, 23 July 2016

Those companies that don't adapt to understanding knowledge as a force of production more important than land, labour or capital, will slowly die, and will never know what killed them".

Larry Prusak, KM guru

Friday, 22 July 2016

3 ways to make tacit knowledge as findable as Pokemon

Lots of work is done, as part of Knowledge Management programs, to increase the findability of documents. But how do you make tacit knowledge findable, given that it is as invisible to the naked eye as Pokemon?

The ratio of tacit to explicit knowledge in an organisation is an unknown factor. People often quote "80% of the knowledge is tacit" - but nobody knows for cure. It's a large proportion for sure, and in some organisations very new to Knowledge Management it can be way more than 80%. So how do we find that tacit knowledge when we need it?  You can't see it, you don't know where it is; you just know you  need it.

We work on finding documented knowledge through several approaches:

But how do we ensure tacit knowledge, still in people's heads, is findable?  The problem with tacit knowledge is that it is invisible. Like Pokemon, we can't see it, unless we have the tools to look for it.

Here are three tools we can use. 

Firstly we can link the people to the documented knowledge. By keeping the names with the knowledge we allow the reader of the document to find the originator, and ask for more detail - to ask for the tacit knowledge which never got into the document.

Secondly we network the people into communities of practice. If you ask a question of a community of practice, it will reach the person with the answer and with the relevant tacit knowledge, even if you do not know that person.

Thirdly we introduce a knowledge-finder system. By this I do not mean a personal directory system such as Facebook, LinkedIn or SharePoint's MySite. These sort of systems are very good for finding the personal details of someone who's name you already know, but are poor for finding people with specific knowledge or skills. Even LinkedIn struggles with this, with no way to search for a combination of endorsed skills, even if you trusted the endorsement system.

No, the best analogue for a people-finder is a dating site. Dating sites are designed to make people findable, based on certain personal characteristics ("Tall, dark haired, handsome, single etc"). People-finders in organisations need to make knowledge-holders equally findable ("expert in knowledge management, experienced in KM strategy and framework development") which means using metada lists of knowledge categories. Selecting knowledge-types from preset lists is constraining in terms of data entry, but it massively enhances findability, and findability is what we are looking for here - finding the tacit knowledge that is otherwise as invisible as Pokemon.

This sort of tacit-knowledge-finder is the Knowledge Manager's equivalent of Pokemon Go, acting as an index to all the tacit knowledge which is out there, but invisible to the naked eye. 

Thursday, 21 July 2016

Learning rates, and the value of Knowledge Management

Over time, with any technology, the costs come down. This is known as the learning rate. One value proposition for Knowledge Management is to increase the learning rate.

What is your organisation's learning rate?  What could KM increase this to? And what's the value of the difference?

The concept of the learning curve is very common. Wikipedia tells us that the term is used when the same task is repeated in a series of trials, or where a body of knowledge is learned over time. The first person to describe the learning curve was Hermann Ebbinghaus in 1885, in the field of the psychology of learning, and in 1936, Theodore Paul Wright described the effect of learning on production costs in the aircraft industry. This form, in which unit cost is plotted against total production, is sometimes called an experience curve.

Learning curves can be drawn as an upward sloping curve, representing gaining knowledge over time, or a downward sloping curve, representing decreasing costs over time. Experience curves are generally drawn as downward sloping curves, as are these learning curves from drilling in Oman, and oil platforms in Trinidad.  The steepness of teh curve is determined by something called the Learning Rate.

The value of Knowledge Management

The Learning Rate, in the case of production costs, represents the percentage reduction in cost when production doubles. In the case of oil wells, its the percentage reduction in cost when the number of wells doubles. Learning rate therefore is linked to cost.  I have explained here that the value of learning is represented by the area under the learning curve. The greater the learning rate, the steeper the curve, and so the more value generated through learning. 

The value in Knowledge Management, in any organisation involved in repeat activity or in learnign something new, comes in increasing the learning rate. The diagram above shows the link between learning rate and savings. Imagine you do a task 10 times, with a learning rate of 8%. The reduction in cost should deliver 17% savings compared to no learning at all. However if you can learn twice as quickly (16%) the savings increase to 30%.

Typical learning rates.

There is a natural learning rate, where people just get better through practice with no intervention from KM. Knowledge Management should help you improve on this natural learning rate, and so deliver added value. But what is a typical natural learning rate, and what is an enhanced KM-accelerated learning rate?

This is difficult to answer, and any studies of experience curves are usually careful to point out that there are other factors than knowledge behind the reductions in cost (economies of scale, innovations in labour, costs of raw materials etc).

However this paper shows some learning rates for Power Generation technology, for example

  • Coal - 8.3%
  • Onshore wind - 12%
  • Natural Gas - 14%
  • Solar - 23%
Also we have the examples of learning curves already mentioned on this blog:
  • Trinidad Patforms - 16%
  • Oman oil wells - 21%
  • I also have a North Sea example with a learning rate of 34%
The paper on the power generation examples attempts to separate what they call "learning by doing" from "learning through research", which maybe gets close to a "natural learning rate" vs an "enhanced learning rate". For the 5 examples where they manage to separate these factors, "learning by doing" averages at 7.5% and "learning through research" at an additional 11%.  The difference between 7.5% and 18.5% is an additional 20% savings over a program of 10 projects. 

It would be interesting to see if this also holds within organisations, with in-company Knowledge Management replacing "learning through research". 

Implications for Knowledge Management programs

The implication for Knowledge Management is that this provides us with a potential way to measure the value delivered through Knowledge Management. You would need to do the following:

  • Collect data on the learning rate of repeat projects within the organisation prior to the introduction of Knowledge Management
  • Collect data on the learning rate of repeat projects within the organisation after the introduction of Knowledge Management
  • Calculate the additional cost savings related to the increase in learning rates.

This should work when the organisation is involved in repeat activity, where operational efficiency (measured in cost or time) is the primary business driver.

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