Siloed organisations; knowledge in the hallways, knowledge in the walls.

There is a clear view than knowledge lies in the "walls" and the "hallways" between the "rooms" of an organisation.  Here are some of the implications of this view for Knowledge Management.

Image from wikimedia commons

This blog post was inspired by a post from Nancy Dixon entitled  Where Is The Only Place Employees Share Their Knowledge? (The Hallways of Learning). If you haven't read Nancy's excellent post, please do so and then come back, as I want to expand on some of the ideas it raises. 

Nancy talks about knowledge and learning in an organisation using 3 metaphors:

• Learning in "private rooms", and under this heading she talks about individuals learning for themselves, and creating their own understanding.
• Learning in the hallways, where individuals get together and create shared understanding, and
• Learning, or Knowledge, in the Storerooms of knowledge; the storerooms being the collections of knowledge created through the hallway conversations.

Nancy concludes as follows:

Hallways are the only space where it is possible for an organization to learn. It cannot learn in the Private Offices, although individual learning can certainly take place there. It cannot learn in the Storeroom, where it is only possible to affirm what is already known. If organizations are going to learn, they will need to construct Hallways in which the in-depth exploration of meaning can occur.

Nancy's blog post reminded me of something said by a one-time colleague of mine, Paul Whiffen, who was of the view that "Organisations are like a series of rooms, and knowledge lies within the walls". Paul was talking about teams at the time, and the rooms being "team spaces" (both metaphorical spaces and electronic spaces) while the walls represent the barriers to inter-team interaction. When those barriers are breached, knowledge flows.

Silos and hallways

We are talking here about silos, and silos in organisations exist at individual level, team level, and department level. Effective KM requires breaching some of the silo walls and creating the learning spaces ("hallways") in which knowledge can be shared. It is possible to learn within these silos - the Private Offices of the individual, and the Team Spaces - but the real value of KM - the challenge as well as the opportunity - comes when you break the silos. 

An illustration of the value of silo-breaking, and exchange of knowledge between individuals and teams, comes from the data from our classroom exercise "Bird Island" (reference here). This exercise has been rather like a controlled KM experiment which has run for over 20 years. We find that:

• teams that learn only from their own experience, see potential performance gains of 40% on average;
• when teams learn from experience of the other teams in the classroom, they see potential performance gains of 80% on average, and
• when teams use all the historical knowledge from all past teams (the knowledge in Nancy's storeroom), they see actual performance gains of, on average, 220%.

The 80% and the 220% performance increase came from knowledge that was "in the walls and the halls" and that needed the teams to break their silos and enter a shared space - a hallway or storeroom as Nancy would say.

Where are the hallways in hybrid organisations?

Nancy's use of the term Hallways does not necessarily mean real hallways in a building (although it could; when I ran a local knowledge management system in a Norwegian office in the 90s, before online collaboration was common, we posted lessons learned on the hallway noticeboard opposite the coffee corner, and there was often a knot of people looking through these), she refers also to tools like After Action Review and storytelling circles. She says:

The real hallways of our organizations will not suffice for the level of organizational learning that is necessary. Rather, organizations to need to develop processes that have the positive characteristics of real hallways, yet are more focused and intentional.

Increasingly that focused intentional activity needs to happen in a hybrid world. And here we see an added challenge. As the Microsoft study showed, in an online or hybrid world, the silos are strengthened. Proportionately more interaction tends to happen within teams, in "Team Space" while proportionately less happens in the walls and hallways between the team spaces. I quote from the study;

Our results suggest that shifting to firm-wide remote work caused the collaboration network to become more heavily siloed—with fewer ties that cut across formal business units or bridge structural holes in Microsoft’s informal collaboration network—and that those silos became more densely connected. Furthermore, the network became more static, with fewer ties added and deleted per month. Previous research suggests that these changes in collaboration patterns may impede the transfer of knowledge and reduce the quality of workers’ output.

In other words, in a hybrid world the silos are strengthened and the hallways begin to disappear. This is a real risk for KM. 

So what can we do?

As Nancy suggests, we need to become intentional.

At the start of a project, the project leader needs to intentionally ask their team "who else can we learn from?" This question forces them to look outside team space, to look through the windows in the walls, to look into the hallways to see who else has valuable knowledge. And then they track those conversations to make sure the knowledge is brought into the team space, perhaps through Peer Assist or another process.

During a project, the project leader needs to intentionally ensure that team conversations are not just about task and activity, and that the question "what have we learned" is a regular topic of discussion. After Action Review is a great format for this discussion. 

At the end of a project, the project leader needs to intentionally ask the team "who else do we need to share our lessons with"? Again this forces the team to look through the walls and into the hallways. 

All of this intentionality can be built into a KM plan for the project.

The organisation also needs to intentionally build and support the required communities of practice which will act as the hallway monitors and the silo-breachers. In a hybrid world, these communities need their own communication channels, as well as their own roles, processes and governance. Each community lives in its own hallway.

The communities of practice can then act as the custodians of the storehouses of knowledge. 

None of the above is new. However in a hybrid world, it needs to become, in Nancy's words, more focused and more intentional if we are to open the hallways and release the knowledge trapped in the walls. 

 

Optimising for the internal search engine

Internal company search seldom works as well as Google, because so few people optimise the findability of their content.

Image from Wikimedia commons

People often cite Google as the gold-standard in search, but partly Google works so well because of the prevalence of search-engine optimisation in the World Wide Web. Anyone who uses the web as a market place or a means of making publications available, knows about the issues of Search Engine Optimisation. And if you own a website, you probably receive 10 emails a day from people offering to improve your SEO ranking.

As far as internal sites on the Intranet are concerned, there probably is little thought given to optimising search. Metatags may be missing, document titles may be poor or unhelpful, documents may be filed in unhelpful ways (see my post on "a haystack is no place to store your needles"), and the whole issue of findability is often ignored.

I remember in the mid 90s when BP introduced their first Intranet, and the manager of BP Norway (my boss at the time) set up a BP Norway home page. It went live, and the next day we went onto the Intranet, typed in the search term "BP Norway", and .......... got no results!

It turned out that the words "BP Norway" only ever appeared in banner graphics, which had no Alt tags (I don't know if this was even possible at the time) and were therefore invisible to the search engine. Therefore this whole site had become unfindable, or search-engine-impaired.

Part of the role of the Knowledge Management team, in any organisation that makes extensive use of codified knowledge combined with search, is to educate the owners of the knowledge stores about how to ensure findability and about the need for optimising codified knowledge for the internal search engine.

Maybe in this way we will get a little closer to Google. 

8 demand-side principles for Knowledge Management

In 2008 David Snowden published a landmark article on 7 KM principle, mainly focusing on the supply side of knowledge management. The post below, upcycled from 2012, aims to present similar principles from the demand side. 

Principles by Nick Youngson 
CC BY-SA 3.0
 Alpha Stock Images

David's 2008 post is currently (Nov 2020) unavailable, but his principles are as follows:

1. Knowledge can only be volunteered it cannot be conscripted. 
2. We only know what we know when we need to know it.
3. In the context of real need few people will withhold their knowledge.
4. Everything is fragmented. We evolved to handle unstructured fragmented fine granularity information objects, not highly structured documents.
5. Tolerated failure imprints learning better than success.
6. The way we know things is not the way we report we know things.
7. We always know more than we can say, and we will always say more than we can write down.

All except number 5 addresses the expression and presentation of knowledge.  There is of course another side - the demand side, or the user side - which represents the transition from expressed knowledge to conscious understanding and to unconscious knowing. Here I offer a set of principles which apply to the other side of the equation - the learning side

These principles are based on our own experience in Knoco, and there is some overlap with the established “principles of learning” used in the educational field.

Here are our principles

1. People don’t pay attention to knowledge until they actually need it. People won’t  absorb knowledge until they are ready, and they won’t be ready until they feel the need.  I could give you detailed driving instructions of the quickest way to travel from Bath in Somerset to Woking in Surrey, but you wouldn’t retain them because they are of no immediate value to you. Then one day, you are at a garden party in Bath and your boss calls and says “can you get to Woking as quickly as possible, we have a potential big deal to close and I need you here right now”. THEN you will be highly receptive to the knowledge. The consequence of this "attention when needed" is that it is more effective to set up “just in time” knowledge sharing processes than “just in case” knowledge sharing processes (although these also have their place).

2. People value knowledge that they request more highly than knowledge that is unsolicited.  I don’t know the psychology behind this, but it seems to be true.  The best way to get knowledge into people’s heads seems to be by answering their questions. The old fashioned “show and tell” is far less effective than “question and answer”, and the blog is less effective than the discussion forum.  The company where the most questions are asked, is often the company that learns the quickest.  This principle is behind the design of most effective knowledge management processes, the majority of which are based on dialogue, and the primary focus of communities of practice should be answering questions rather than publishing ideas.

3. People won’t use knowledge, unless they trust its provenance.This is the “not invented here” principle, which is a very strong factor in knowledge management terms.  People won’t use knowledge they don’t trust, and they don’t trust knowledge if they don’t know where it has come from.  They need either to trust the individual who gave them the knowledge, or the organisational construct (such as the CoP) which provided the knowledge.  The source may be an expert, or a wiki (many people trust Wikipedia for example, despite its shortcomings), or a community of practice, and building credibility and trust has to be a key activity when building these constructs as part of the knowledge management initiative.

4. Knowledge has to be reviewed in the user’s own context before it can be received.  One of the knowledge receiver’s first questions is “is this relevant to me?” Everybody always feels their own context is different (even though the difference is often less than assumed), and they need to test the knowledge for relevance before they really pay attention.  We were recently facilitating a peer assist, where people were bringing knowledge from Africa, from India, from China, to be used in an Indonesian context.  For each of the learning points, we needed about half an hour to an hour’s discussion around context, before we could even approach discussion of how imported knowledge might be used. This means that transferring knowledge in a written form is difficult, unless you can introduce a process by which people can interrogate this within their own context.

5. One of the biggest barriers to accepting new knowledge is old knowledge.  This is the curse of prior knowledge. People have to unlearn, before they can learn.  Old assumptions, old habits, “the way we have always done it in the past” may all have to be challenged before people can absorb and make sense of new knowledge.  This can be hard work! As an example, see the story about the war of the hedgerows, where the U.S. Army completely missed the implication of the Normandy hedgerows, assuming they would not be a factor in tank and infantry warfare after the D day landings

6. Knowledge has to be adapted before it can be adopted.  If people are provided with guidance, tips and hints, or even a “recipe to follow,” they will always tweak it and adjust it in order to “make it theirs”.  Sometimes this tweaking and adjusting is necessary to fit the knowledge to their own context; sometimes it is unnecessary in practical terms despite being necessary in emotional terms.  So when you are providing people with guidance, tips and hints or even a “recipe”, you have to give them some idea of where they can still adapt it, and where dangerous tinkering should be avoided. Otherwise they may "adapt" the wrong thing. We see this all the time in our Bird island exercise - they all want to tinker with the final design, and you have to let them tinker, but try to guide them to tinker in non-fatal ways!

7. Knowledge will be more effective the more personal it is.  The more personal, emotional, and highly charged the learning situation, the more the knowledge will be easily adopted.  Discussion, story telling and coaching can be personal, and motional and highly charged, but it becomes difficult to translate this into the written word.  The use of stories is very helpful, the use of video even more so.  Obviously this has profound implications for knowledge transfer mechanisms.

8. You won’t really KNOW it until you DO it.  We very often see in lessons learned meetings, teams that say  “we picked up this learning from the previous project, we tried it and it really did work!  That was a great learning for us”.  When they picked it up they knew it intellectually; after they had tried it they knew it practically and emotionally.  Seeing is believing, trying is trusting, doing is internalising.  This sort of positive reinforcement of learning is a massive boost for your knowledge management program; as people try things and find they work, this reinforces the belief that knowledge from others is of real practical value.

The personal learning matrix

A personal learning matrix reminds people of the sources of knowledge available to them.

The matrix shown above is inspired by a really interesting blog post entitled "how rocket scientists learn" by Yasmin Fodil from NASA. Yasmin points out that 

Knowledge management is about the better application of collective knowledge to the individual problem. 

She includes a matrix, similar to the one above, to show the sources of collective knowledge available to knowledge workers, and the means by which they can access that knowledge. I particularly like the fact that is the whole matrix is pull-driven - "Who can I learn from", "What can I learn", "How can I learn it" - all driven by knowledge-seeking.

It's like a "seekers guide to knowledge sources". I like the concept, and have created the matrix here as an extension of Yasmin's example. 

This is refreshingly different from the more normal "who can I share with", "where shall I store this" conversation. It's like a personal Knowledge Management Plan - all that's missing is the "What do I need to learn" element. It would be a useful chart to stick on the wall during a Knowledge Gap Analysis or Knowledge Management Planning session.

A table like this would be a good reminder to all knowledge workers in the organisation of the sources of knowledge available to them, and the means at their disposal to access that knowledge. 

How newly hired graduates search for knowledge?

How do graduates search for knowledge, and what this means for KM.

 

Image by mohamed Hassan from Pixabay

Here (summarised here and slides here) is a really interesting study about the difference between the strategies that new-hires use when seeking for information and knowledge, and the strategies their employers expect them to use.  

The study was conducted in 2012, so some comments about the digitial illiteracy of non-graduates may no longer be valid, but there is still some very interesting material there.

The study is summarised as follows

"Overall, our findings suggest a dramatic shift is occurring in the workplace related to how information is found and used.  

"We found the traditional research competencies—the use of non-digitized information sources—may be disappearing with each passing year as a new batch of college hires joins the workplace and employers make assumptions about their information competencies.  

"We found that few, if any, of the employers we interviewed said they hired college graduates solely because they could solve information problems in record time. Yes, employers recruited hires with the ability to conduct online searches. At the same time, however, other qualities also mattered.  

"In particular, employers expected hires to possess low-tech research competencies, such as the ability to make a phone call, to poke their heads into a co-worker's office to ask a question, to interpret results with a team member, or to scour a bound report. However, many fresh-from college hires sorely lacked these traditional research competencies.  

 "These low-tech information skills are essential to the workplace research since so much information in the workplace is contextual and highly individualized to the operations of the organization itself. But many of these young adults considered perusing the index of a print volume or picking up the phone to consult a colleague as outdated as using an adding machine to balance the payroll.  

"These findings, of course, warrant further investigation. But they are certainly plausible as more and more information becomes digitized, as each new crop of college graduates is more than likely to be “born digital,” and as employers continue to make hiring decision based on online information gathering proficiencies".

Most graduates in the study focus groups said "they found it difficult to solve information problems in the workplace,where unlike college, a sense of urgency pervaded and where personal contacts often reaped moreuseful results than online searches.... New Hires tend to use online searches  in preference to any other mechanism, often using cursory search". 

The report states that "Most college hires were prone to deliver the quickest answer they could find using a search engine, entering a few keywords, and scanning the first couple of pages of results, employers said, even though they needed newcomers to apply patience and persistence when solving information problems in the workplace".

Given that searching and finding are crucial components of KM, then the implications of this study for Knowledge Management are as follows.

1. Graduates need induction into the company Knowledge Management framework and how to use it, including the location of the knowledge stores, and the communities of practice, to avoid the default of cursory use of search engines.
2. If graduates default to online search, then there needs to be a knowledge base for them to find; even if it is just an index of "people to contact"
3. New graduates need, as part of their induction, to be introduced to as many people as possible, in order to start building the social networks that can replace online search.
4. They need to be inducted into the relevant communities of practice, as in the office world, 80% of the knowledge is undocumented, and will never be found through online search.

The search habits of new graduates are "search first, ask later (if at all)". Until those habits change, make sure there is something for them to find even if it is only the name of the person to ask. Make your knowledge findable, especially by new hires.

Maximising use of bandwidth in KM

We all suffer from bandwidth issues in KM - generally due to the deluge of information. Here's a good principle from the military for dealing with these issues.

Information overload by SparkCBC on Flickr

The phrase - "Smart push, warrior pull" (described here). is a very useful military principle for maximising knowledge bandwidth. In the military case the bandwidth is often restricted by hardware rather than by attention, but the principle is a good one.

The US Department of Defence operates a global broadcast system (GBS) which acts as a knowledge and information transfer system to troops. Like any such communication system it suffers from bandwidth issues, so the transfer of knowledge and innovation must be strictly prioritised.  "Smart push, warrior pull", inevitably shortened to SP/WP, is a widely-applied principle to do this prioritisation. It represents the two following components;

• Intelligent transfer, from central command to the troops on the ground, of the information and knowledge they need at that moment and nothing more.
• The option for further requests for additional information and knowledge from the troops to the centre.

This is an excellent principle for a lean knowledge supply chain. 

It ensures that people get the right knowledge at the right time, with no waste. Send people what they must have, and let them pull what they might need.

The armed forces and intelligence units operate this way because of the bandwidth limitations of the GBS, but there is no reason why a similar principle cannot be used within organisations: "Smart Push, Front-line Pull" (SP/FLP) for example, where the customer facing staff, or staff conducting operations or projects, are provided centrally (or automatically) with the knowledge they need for that customer, or that operation, or that project, with the option to ask/search for more if needed. To do this effectively, the "senders" in the centre must anticipate the needs of the front line, so this "push" is probably best managed by the communities of practice and/or the domain experts.

Although organisations are less likely to have infrastructure bandwidth limitations, there is definitely an attention bandwidth issue, also known as "information overload". A principle such as SP/FLP would improve the efficiency of the KM system by reducing "knowledge waste" and minimising information overload.

Free access to knowledge, or structured access to knowledge?

Here is another excellent article from Tom Davenport, one of the clearest writers on the topic of Knowledge Management, making the case for a structured "just-in-time" approach to the supply of knowledge. 

Tom starts his article as follows:

In the half-century since Peter Drucker coined the term “knowledge workers,” their share of the workforce has steadily grown—and so has the range of technology tools aimed at boosting their productivity. Yet there’s little evidence that massive spending on personal computing, productivity software, knowledge-management systems, and much else has moved the needle. What’s more, a wide variety of recent research has begun suggesting that always-on, multitasking work environments are so distracting that they are sapping productivity.

He goes on to contrast two approaches to the provision of knowledge

• A "free access" approach where the organization provides free access to a wide variety of tools and information resources, assuming that the individual employees will do the selecting, prioritising and filtering and find the knowledge they need to conduct their work. 
• A "structured" approach where knowledge is delivered in the context of tasks and delivereables, providing just in time knowledge at the point of need. In this case the prioritising has been done before the knowledge reaches the knowledge worker. 

Long-term readers of this blog will recognise these options as the "knowledge firehose and the knowledge faucet", or will recognise the second as the lean knowledge supply chain. The first rapidly overwhelms the knowledge worker, the second efficiently provides the knowledge they need with no additional waste. 

However Davenport adds a nuance. He suggests that the free access approach may be valid among the autonomous knowledge workers with high levels of expertise, who can invest the time and energy needed to filter the firehose and draw out the selected nuggets which may make a subtle difference. 

The problem with providing free and unstructured knowledge to all knowledge workers is the associated productivity loss. Here are some of Davenport' statistics.

• One survey revealed that over a quarter of a typical knowledge worker’s time is spent searching for information.
• Another found that only 16 percent of the content within typical businesses is posted to locations where other workers can access it.
• Average knowledge workers access their e-mail more than 50 times, use instant messaging 77 times, and visit more than 40 Web sites a day.
• A UK study suggests that social-media use by knowledge workers costs British companies £6.5 billion a year in lost productivity.

Davenport contrasts this with the structured supply of knowledge using workflow technologies. Here productivity is the major gain - by providing people with the knowledge they need without them even having to look for it, task-based productivity can rise by 50%. The downside of these systems is the lack of a personal touch - the lack of the social component. 

However there is always a combined approach. Through Connect and Collect we can provide a push-based supply chain of explicit knowledge to the knowledge workers, linked to their task workflow (or prompt them to pull structured knowledge from a structured knowledge base) and in parallel allow them to pull unstructured tacit knowledge from a community of practice.  A Knowledge Management Strategy can be used to determine the balance between these two approaches for different knowledge topics. 

 Davenport concludes his article as follows:

It’s time to think about how to make [the knowledge workers] more productive by imposing a bit more structure. This combination of technology and structure, along with a bit of managerial discretion in applying them to knowledge work, may well produce a revolution in the jobs that cost and matter the most to contemporary organizations

Forget knowledge sharing, let's encourage knowledge seeking instead

People often ask us "how do we incentivise  knowledge sharing?" I often answer "don't bother. Incentivise knowledge seeking and re-use instead".

I give this answer, because knowledge sharing in itself achieves nothing. Knowledge needs to be sought and re-used before any value has been added, and re-use is often a far bigger barrier than knowledge sharing. The Not Invented Here syndrome is far more prevalent than Knowledge Hoarding.

As an analogue, think of a driver in a car in a strange city, looking for a building which is not on the satnav.  They need knowledge, people on the sidewalk have the knowledge, but why doesn't the knowledge reach the driver? It's usually not because people won't share, but because the driver doesn't ask.

Knowledge needs supply and demand - sharing is the supply, seeking and re-use is the demand. Supply without demand devalues a commodity. Demand without supply increases a commodities value. Supply and demand need to be in balance, but the best way to kick off a market is to stimulate demand. 

Without an appetite for knowledge re-use, knowledge sharing can actually be counter-productive, resulting in the feeling of the "knowledge firehose".  Better to incentivise knowledge seeking first then knowledge sharing later, create the appetite for knowledge before you create the access, and create the demand before you create the supply.

There will naturally be SOME supply already, as there are people who naturally like to publish. They like to share, they like to write, they were given two ears, one mouth and ten fingers and use them in that proportion.  If you create the demand and create the channel, the supply will follow. As David Snowden pointed out,

"In the context of real need few people will withhold their knowledge. A genuine request for help is not often refused unless there is literally no time or a previous history of distrust. On the other hand ask people to codify all that they know in advance of a contextual enquiry and it will be refused (in practice its impossible anyway). Linking and connecting people is more important than storing their artifacts".

Create the need, connect the people, and the sharing will follow.

And how do you create the need for knowledge?  There are a number of ways;

• Managers create a high performance culture, where people are eager to "push the envelope"
• Managers ask the two questions that drive KM behaviour, emphasising the first
• Managers set people challenges that they don't know how to solve using just their own knowledge

So don't incentivise knowledge sharing - incentivise knowledge seeking first. The sharing will follow.

Rocks and Sponges - Teachability and the desire to learn

According to one expert, people are either Rocks or Sponges when it comes to learning. 

The most powerful thing that leaders can do to help Knowledge Management succeed is to drive that desire to learn as part of the corporate culture.  If the drive to learn is there, the drive to share will follow. The desire to learn makes Knowledge into a valuable commodity, and where a commodity has value, a market inevitably arises.

But how do you instil a "desire to learn"?

Sir Clive Woodward, the sport coach and Elite Performance speaker, calls it "Teachability" - another word for a "Learner Mindset". He says

"To have a great team you need great individuals, but you also have to have Teachability ... In business or in sport you are a sponge or a rock. A sponge has a hunger for learning and taking on new knowledge  ... building a team full of sponges will lead to an exciting and vibrant environment where new ideas flourish and the norm is challenged".

You cannot teach someone something if they think they know it already, and you can't share knowledge with someone who doesn't want to know.  They are like a Rock - the knowledge just bounces off. The sponge however is thirsty for knowledge and will soak up all they can find.

We talk so much about developing a "culture of sharing", but that will achieve nothing without a "culture of learning", and without turning people from rocks into sponges. It is only sponges that turn into high performing teams. Having just one rock on your team is enough to vastly reduce your chances of winning.

Turning people from rocks into sponges.

When Sir Clive took over the England Rugby team, he was faced with the challenge to turn a group of rocks into sponges. He did three things;

• He built the desire to be the best
• He showed people, through data and statistics, how far from The Best they were, and
• He bought laptops for the whole team, so they could study and learn about themselves and their opponents.

There is a story about how Sir Clive was working with one of the players, and showed him a flipchart of statistics demonstrating that he was the best player at his team position in England.  He was obviously pleased! Then he turned over the page, and showed that in world terms, he was the seventh best player.  This was a shock, and immediately the player began to think and plan about how he could  learn and improve.

Desire to improve drives the desire to learn

Sir Clive Woodward used the power of data to instil the desire to improve amongst his team, which developed the necessary teachability, and which led to victory in the 2003 Rugby World Cup.

We see the same influences in our Bird island game, when we finally show people the benchmark data, and they realise how much they can improve. The emotional shock they receive destroys the mental barriers to learning.

Sir John Browne did the same at BP, with his vision that "every time we do something, we should do it better than the last time". 

Business leaders can do the same - by showing their teams where they are under-performing compared to their peers, and challenging them to improve.

If we are to implement Knowledge Management in our organisations, then we need to be changing rocks into sponges, and introducing a culture of Willingness to Learn, by instilling a culture of Desire to do Better.

Only when these are in place, will Knowledge Management reach its full potential.

Why so much knowledge sharing, so little knowledge seeking?

Knowledge Management requires knowledge seeking and knowledge sharing. But why so much focus in internal processes on sharing and so little on seeking?

Learning Happens by shareski, on Flickr

One of the standard models for Knowledge Management in project environments is the idea of "Learning Before, During and After".

Ideally these three activities should be embedded in project process, so that a project

1. Starts by reviewing and accessing all the knowledge it needs,
2. Learns as it goes, improving its processes during the course of the project, and
3. Identifies, analyses, documents and shares the new knowledge it has gained, for the sake of future projects. 

For the project itself, the most powerful of the three is "Learning Before". If a project can maximise it's knowledge up front, especially if the team can discover the things it doesn't know that it doesn't know, then success is much more likely. "Learning Before" activities such as Knowledge gap Analysis, KM planning or Peer Assist can overcome some of the more serious cognitive biases for KM, and are the nearest thing to KM Silver Bullets that we have. Learning before activities drive receptivity, increase absorptive capacity, and help teams "want to learn".  

And yet, when you look at internal company project frameworks, or even at  generic frameworks such as Prince 2 or ISO, there is almost always a requirement for capturing and sharing lessons after the project, and no such requirement for Learning Before. According to our global survey, 68% of companies require their projects to do some sort of Learning After, but only 15% require them to do Learning Before.  Prince 2 has a required, and well documented, step at the end, for creating lessons (although this could be much improved!), but has no step at the project start-up, requiring a search for, and review of, existing knowledge.  

This astounds me.

Why even bother to collect lessons at the end of a project, if nobody reviews them at the start of the next project!

I think the answer is that it is psychologically easier to share than it is to learn.  A project team can feel proud and recognised (even a little smug at times) for sharing lessons, while asking for lessons can feel like an admission of incompetence ("can anyone help me with this?"). 

Learning After is Teaching - Learning Before is Learning, which is Much Harder. Knowledge reuse is more difficult than knowledge sharing, yet that is all the more reason we should make it a focused and deliberate step. 

You get around some of these barriers by introducing non-judgemental techniques such as Peer Assist and Knowledge Management plans, which take the exposure out of asking for help, or seeking for knowledge. And you also address it by developing a culture of Asking, rather than a culture of Sharing.

Please, let's introduce the full cycle of Learning Before, During and After, and let's not skip the Before step!

The KM one-stop shop vs the multi-site experience

When we set up our KM systems, lets make it as simple as possible for the knowledge-seeker. Let's aim for the one-stop shop.

Image from geograph.org.uk

It is common for Knowledge Managers to start to plan their KM systems based on the supply of knowledge, or based on the different forms knowledge can take. 

"Let's set up a lessons database to collect lessons"
 "Let's put together a best practice repository"
 "Let's build a site where we can collect videos together. We can call it AcmeTube!"
 "Let's set up some forums for communities of practice"
 "Let's create an expertise-finder system so people can find others with relevant knowledge"
"Let's start a wiki site. We can call it AcmePedia!"

All of these are worthy aims, but the complication comes when a future knowledge worker comes looking for knowledge. Say they are looking for knowledge on a particular topic - a maintenance engineer wanting to overhaul a submerged pump for example. With the system above -

• They have to open the lessons database to see lessons on submerged pumps,
• They have to open the best practice repository to see best practices on maintaining submerged pumps,
• They have to visit AcmeTube to see videos on how to maintain submerged pumps,
• They have to visit the community of practice forum to see discussions on submerged pumps,
• They have to log into the expertise-finder system to find people who know about submerged pumps,
• They have to open AcmePedia to find if there are any articles about how to maintain submerged pumps.

By setting up multiple knowledge systems, and splitting up your knowledge based on it's type rather than its topic, you are setting unnecessary demands on the user. It is hard enough to get people to re-use knowledge without making it time-consuming and complicated. Far better to construct your technology around the needs of the user and to create a one-stop shop. Make it as easy as possible to re-use the knowledge.

The one-stop shop

The ideal situation for the user is that they search or navigate through "rotating equipment" and "pumps" until they find the Submerged Pumps Portal. The portal then gives them:

• Wiki guidance
• All videos are embedded in the wiki (even though they might be hosted elsewhere)
• Alongside the page is a list of experts on submerged pumps
• At the bottom of the page is a summary of open lessons on submerged pumps (the content of older closed lessons has already been used to update the wiki)
• Also at the bottom of the page is a summary of open community discussion on submerged pumps (the content of older closed discussions lessons has already been used to update the wiki)
• The wiki contains best practices, maybe with links out to Standards documents. It may also contain case histories, links to training material, and so on.

Ask yourself - if you were the maintenance engineer, which of these two approaches would you prefer to use? The one-stop portal, or the six separate systems?

Set up your technology systems with the needs of the user in mind. Don't structure them based on the type of knowledge or the provenance of the knowledge, separating out lessons from best practices, or separating videos from discussions. Instead structure them based on the needs of the users. Structure the knowledge according to the activities the knowledge workers undertake, or the equipment they work with. 

Set up the one-stop knowledge shop to make life quick and simple for the knowledge worker.

The knowledge cycle as you have never seen it before

We are used to seeing pictures of knowledge cycles, but there is one cycle you never see, and it's very important.

You can find very many versions of the knowledge cycle, and they all seem to work the same way.

They start with "Create" or "Capture", and progress through "Store", "Share" etc until they get to "Use" or "Apply. Some have as few as 3 steps, some have 8 or more steps, and the 4-step basic has even made it into the Stock Photo collections. However all these cycles work in the same way, as all of them are "Push" cycles.

By "Push Cycle" I mean a cycle that is driven by knowledge supply, and describes how that supply of knowledge works through various stages until the knowledge is used again. It is a supply chain model, and people use the cycle to put in place roles and processes to move knowledge along the steps in the supply chain.

However Supply is only half the story, and you need to look at Demand as well.

The diagram shown here is a cycle driven by knowledge demand - a "Pull cycle" - and it works like this.

• The cycle starts with a problem, and the identification of the need for knowledge to solve the problem (the "need to know")
• The first step is to seek for that knowledge - to search online, and to ask others
• Seeking/asking is followed by finding
• However generally we tend to "over-find". Unless we are lucky, or there is a very good KM system, we fInd more than we need, so the next step is to review the results and select those which seem most relevant in the context of the problem.
• This found knowledge then needs to be integrated into what is already known about the problem, and integrated into solutions, approaches, procedures and plans.
• Finally the integrated knowledge needs to be applied to the problem.

So why do we never see this Pull cycle in diagram form?

• Is it because Pull (Demand) is less important than Push (supply)? Surely not! Most people would see them as equally important, and there is an argument that Pull is in fact a bigger driver of knowledge transfer than Pull. 
• Is it because the Pull cycle is less useful than the Push model?  Surely not! If we can generate knowledge pull, and a demand for knowledge, we can spark knowledge supply. 
• Is it because the Pull cycle is more difficult to work with than the Push cycle? Maybe this is one reason. Asking is less of a natural behaviour and more of a cultural barrier than sharing, so sharing may be the easier option. But ignoring barriers wont help you in the long run.
• Is it because the Pull cycle is less measurable? The Push cycle is often linked with the creation of documents, and this is something that can be measured. Leaving aside the question about whether anyone is looking for these documents, and whether these documents are useful when found, it is easier to measure the first couple of steps in a Push cycle than it is to measure similar steps in a Pull cycle. However you can also measure searches, and measure questions in a community forum.
• Is it because people only want one diagram? Yes, probably, but we know that KM cannot be reduced to a single and simple diagram; it is far too nuanced for that.
• Is it because everyone else draws their cycles this way? Probably yes. But just because everyone else does it, doesn't make it correct or sufficient.

There are many places where this Pull cycle can be applied very well.

• Each individual uses this cycle when searching for knowledge. Most of the steps are done in the individuals head, but it may be useful to talk them through with a manager or colleague,. 
• You can apply the cycle within a Peer Assist meeting, and the format of the meeting can follow the entire cycle from asking the questions, to reviewing the answers, to integrating them into the forward workplan.
• You can apply it within a Community of Practice forum. Someone asking a question on the forum could  be asked to give feedback on the answers they received, the knowledge they selected from these answers, how they integrated this knowledge into their plans and (ideally) how it helped solve the problem. 
• You can apply it as part of KM planning. A project team can identify their knowledge needs, conduct a search/ask activity, then get together to discuss how they will select and integrate the knowledge they have found. 

Being more conscious and explicit about the Pull cycle gives you more ways to create and stimulate knowledge demand in your organisation, and helps drive a Knowledge Seeking culture. 

Please do not focus only on the Push cycle for KM - its only half the story. Make sure your KM Framework incorporates the Pull cycle as well. 

Is your knowledge base more like an underwear drawer or a supermarket?

There are three models for a knowledge base - which one is most like yours?

Your online Knowledge base is where you store your documented knowledge, It is a repository - but more than that, it is a knowledge resource for others. Someone looking for documented knowledge comes to the knowledge base to search and browse.

So what do they find?

Generally knowledge bases fall into one of three categories. Let's call them the underwear drawer, the library and the supermarket display.

The underwear drawer (see top picture), if you are anything like me, is the place you pile all your clean washing, generally with the newest washing on the top. The drawer is easy to fill - you just cram everything in - but you know that the hard work will be done when you search (often early in the morning, in the half-light) for a set of matching underwear with no holes. All the work is done when searching, and very little is done when storing. The knowledge base equivalent is the uncontrolled filing structure, where you rely on a good search engine to find what you want. Dump it all in, then search for what you need.

The library (or the organised underwear drawer, see bottom picture) is a managed and structured repository. You know the category, you know the title, and you find the book. Or you know the drawer, and the relevant section, and you find a rolled set of underwear of the right colour. The work is distributed between the seeker and the storer. You categorise when you store, and you browse to the right place when you search. The knowledge base equivalent is the organised and tagged knowledge base, where you can browse or search for the knowledge you know you need.

The supermarket goes one step further (see my post from last year on the knowledge supermarket). In my local supermarket, for example, you can find a section that displays pasta, pasta sauce, Parmesan cheese and Italian wine, all within the same attractive display. Without searching, you are presented with all the ingredients for an Italian meal. Similarly with curries - curry sauces, poppadoms, nan bread, Cobra beer, lime pickle - all in one display. Lots of work is done by the storer, so as to minimise the work for the seeker, and as a result, they pick up the Impulse Buyer - the person who was not actually looking for this material in the first place, or who had forgotten that they need lime pickle with their poppadoms. The knowledge base equivalent is the Knowledge Asset; the one-stop shop for knowledge on a topic - the wiki page or portal that gives you everything you need to know, whether you knew you needed or not.

So what's the lesson for Knowledge Management?

I believe there are three reasons why a supermarket is the best of the three models for your knowledge base.

1. Firstly the main barrier for KM is not supply, but re-use. Many companies have no difficulty in creating knowledge supply, but all companies struggle with re-use. Therefore if we are to lower the barriers, let's lower the barriers for the seeker and the re-user. Let's invest in knowledge packaging, and the creation of knowledge assets, so that there is no excuse not to re-use.
2. Secondly, although the search engine vendors will say that the search engine can do all the finding work for you, most people start by browsing rather than searching when they are shopping for something. Supermarkets are built for browsers, unorganised underwear drawers aren't. 
3. Thirdly, a search result will not return the "unknown unknowns" - the things you did not know to search for. The supermarket, on the other hand, is well designed for ensuring you find the impulse-buys which were not on your shopping list. 

Think about the knowledge user when you design your knowledge base, and don't make them or their search engine do all the work.

Why Yammer's default question is unhelpful

If you agree with me that the greatest value in organisational online discussion comes through answering questions, then Yammer's default prompt does not help.

"What are you working on?" asks Yammer - as a work-related version of the Facebook question "What's on your mind".

As a way of getting people to share work-related activity, that's a reasonable question, and pretty soon you will find your Yammer stream full of statements like

• "I'm working on a new proposal"
• "I'm getting ready to go on holiday"
• "I'm finishing the assessment report"

For some people, that's interesting connectivity, that helps them feel connected with co-workers. For others, that's unwelcome Noise; stuff they didn't need to know that distracts them from their own work. The risk is that the noise turns people off.

This blog has long championed the use of Knowledge Pull behaviours, and Knowledge seeking.  We know for example that Asking is tougher than sharing, but gives instant results. We know that the more questions that are asked in a Community of Practice, the more successful it is. We know that 75% to 90% of knowledge sharing comes as a response to a request for help. We (or I, at least) believe that an internal knowledge market is best grown through demand rather than through supply. And also  that Facebook is not a good analogue for in-house social media.

If you want to use a product like Yammer for knowledge sharing, then I can't help thinking there's got to be a better default prompt - one that drives Pull and not Push; one that develops the habit of Asking.

Maybe something like

"What knowledge do you need to help deliver your work?"
"What can your social network help you with today?"
"What question do you have for your network?"

The Knowledge Batphone - a role for KM?

One of the temporary roles a KM team can take on is to be an organisation helpdesk, manning the Batphone.

The batphone, by heven't the slightest, on Flickr

Imagine you are starting a KM project. You are extolling the virtues of KM, and the benefits of seeking and reusing knowledge as a way of saving time and delivering a better result. Yet your KM system is still not in place.

You have no communities of practice, or the ones you have are in the very early stages of maturity. People are still using your social media for tweets about what they are doing, rather than for knowledge seeking.  You have no structured knowledge assets, and knowledge is mostly scattered through various disparate repositories. You haven't started with curation of knowledge resources, and are a long way from synthesis of best practice. Your search engine is still struggling, and pulling up duplicate, outdated or irrelevant results.  Your lessons learned are still (if you are lucky) in a massive database or file folder, or (if you are unlucky) in the back pages of project reports.

In short, your knowledge is still in a mess. How then can you satisfy and support a demand for knowledge?

One thing you can do is set up a helpdesk service, or (as one of the KMUK delegates called it) the Batphone.

People who need knowledge call the Batphone, and the KM team does the searching for them.  This is an investment of the KM team resource, but the KM team should by now have a good idea of what knowledge resources are out there, and should be well trained in use of the search engine. They should be super-searchers, and be able to deliver a good answer more quickly than the operational staff can themselves.

The benefits of the knowledge batphone are these:

• It provides access to knowledge while the KM framework is being built;
• It allows the KM team to start to create success stories, by calling the person back and asking "how useful was that knowledge to you?
• It allows the KM team to understand the sort of knowledge which people are looking for, and therefore to prioritise the KM program to cover high-demand knowledge;
• It allows the KM team to begin to create FAQs which can for the foundation for knowledge bases on critical topics.

So what do you do with the Knowledge Batphone in the longer term?

You can either retire the Batphone once the Communities of Practice have taken on the roles of knowledge custodians, and are able to provide better knowledge than the KM team can, or you extend the role of the Batphone into a Knowledge Centre, such as those used by the big consulting firms.

Howver in the short term, you may find The Batphone is a great first step in providing access to knowledge. 

The 8 demand-side principles for KM

Here is another reprised post from the archives - as relevant now as it was 5 years ago.

David Snowden's 7 principles for Knowledge Management are justly famous in the KM literature as a simple and accessible set of principles. However they all relate to the supply side of knowledge management; to the transition from unconscious knowing, to conscious knowledge and to expressed knowledge. 

There is of course another side - the demand side, or the user side - which represents the transition from expressed knowledge to conscious understanding and to unconscious knowing. Here are a set of principles which apply to the other side of the equation - the learning side

These principles are based on our own experience in Knoco, and there is some overlap with the established “principles of learning” used in the educational field.

Here are our principles

1. People don’t pay attention to knowledge until they actually need it. People won’t  absorb knowledge until they are ready, and they won’t be ready until they feel the need.  I could give you detailed driving instructions of the quickest way to travel from Cheddar in Somerset  to Woking in Surrey, but you wouldn’t retain them because they are of no immediate value to you. Then one day, you are at a garden party in Cheddar and your boss calls and says “can you get to Woking as quickly as possible, we have a potential big deal to close and I need you here right now”. THEN you will be highly receptive to the knowledge. The consequence of this "attention when needed" is that it is more effective to set up “just in time” knowledge sharing processes than “just in case” knowledge sharing processes (although these also have their place).


2. People value knowledge that they request, more highly than knowledge that is unsolicited.  I don’t know the psychology behind this, but it seems to be true.  The best way to get knowledge into people’s heads seems to be by answering their questions. The old fashioned “show and tell” is far less effective than “question and answer”, and the blog is less effective than the discussion forum.  The company where the most questions are asked, is often the company that learns the quickest.  This principle is behind the design of most effective knowledge management processes, the majority of which are based on dialogue, and the primary focus of communities of practice should be answering questions rather than publishing ideas.


3. People won’t use knowledge, unless they trust its provenance.This is the “not invented here” principle, which is a very strong factor in knowledge management terms.  People won’t use knowledge they don’t trust, and they don’t trust knowledge if they don’t know where it has come from.  They need either to trust the individual who gave them the knowledge, or the organisational construct (such as the CoP) which provided the knowledge.  The source may be an expert, or a wiki (many people trust Wikipedia for example, despite its shortcomings), or a community of practice, and building credibility and trust has to be a key activity when building these constructs as part of the knowledge management initiative.


4. Knowledge has to be reviewed in the user’s own context before it can be received.  One of the knowledge receiver’s first questions is “is this relevant to me?” Everybody always feels their own context is different (even though the difference is often less than assumed), and they need to test the knowledge for relevance before they really pay attention.  We were recently facilitating a peer assist, where people were bringing knowledge from Africa, from India, from China, to be used in an Indonesian context.  For each of the learning points, we needed about half an hour to an hour’s discussion around context, before we could even approach discussion of how imported knowledge might be used. This means that transferring knowledge in a written form is difficult, unless you can introduce a process by which people can interrogate this within their own context


5. One of the biggest barriers to accepting new knowledge is old knowledge.  This is the curse of prior knowledge. People have to unlearn, before they can learn.  Old assumptions, old habits, “the way we have always done it in the past” may all have to be challenged before people can absorb and make sense of new knowledge.  This can be hard work! As an example, see the story about the war of the hedgerows, where the U.S. Army completely missed the implication of the Normandy hedgerows, assuming that these features would not be a factor in tank and infantry warfare after the D day landings


6. Knowledge has to be adapted before it can be adopted.  If people are provided with guidance, tips and hints, or even a “recipe to follow,” they will always tweak it and adjust it in order to “make it theirs”.  Sometimes this tweaking and adjusting is necessary to fit the knowledge to their own context; sometimes it is unnecessary in practical terms despite being necessary in emotional terms.  So when you are providing people with guidance, tips and hints or even a “recipe”, you have to give them some idea of where they can still adapt it, and where dangerous tinkering should be avoided. Otherwise they may "adapt" the wrong thing. We see this all the time in our Bird island exercise - they all want to tinker with the final design, and you have to let them tinker, but try to guide them to tinker in non-fatal ways!


7. Knowledge will be more effective the more personal it is.  The more personal, emotional, and highly charged the learning situation, the more the knowledge will be easily adopted.  Discussion, story telling and coaching can be personal, emotional and highly charged, but it becomes difficult to translate this into the written word.  The use of stories is very helpful, the use of video even more so.  Obviously this has profound implications for knowledge transfer mechanisms.


8. You won’t really KNOW it until you DO it.  We very often see in lessons learned meetings, teams that say  “we picked up this learning from the previous project, we tried it and it really did work!  That was a great learning for us”.  When they picked it up they knew it intellectually; after they had tried it they knew it practically and emotionally.  Seeing is believing, trying is trusting, doing is internalising.  This sort of positive reinforcement of learning is a massive boost for your knowledge management program; as people try things and find they work, this reinforces the belief that knowledge from others is of real practical value.

Bear these principles in mind in the design of your KM programs, as getting people to seek, use and adopt knowledge is as hard, or harder, than getting people to supply knowledge. 

The role of Asking in Knowledge Management

Most knowledge sharing in our private lives is driven by Asking. Let's use this in work as well.

Think about the last time you shared knowledge with one of your friends or family. Maybe it was this morning, or yesterday - maybe you shared advice, a tip or hint, or something you had found out that the other person did not know.

I bet you shared this knowledge bacause you were asked.

• "Where are the car keys?"
• "What's the weather going to do today?"
• "Are you doing anything tonight"?

That's the way that private knowledge sharing seems to work; it follows the three rules below.

When do we share?  Most often, when we are asked

Who do we share with? People who ask us

What is preventing us from sharing? Often, nobody is asking (see here to understand how to tell when sharing is broken)

So how do we take these principles into the workplace?

There are several ways in which you can introducing Asking as part of a Knowledge Management framework.

 The first obvious example is in Communities of Practice. The most important and powerful role of CoPs is providing a forum where CoP members can ASK questions of their peers. The forum allows the person who actually needs the knowledge to ask directly, and the answer comes from the members with knowledge to share.  Communities access the long tail of knowledge, and communities work better with a large element of "Knowledge Pull"

The second case is in After Action Reviews. Here someone in the team, such as the team leader, ASKS a series of 5 questions, to elicit the knowledge of the team. This knowledge will be used by the same team to improve their practices, so the knowledge providers and knowledge users are the same team.

The third example is in end-of-project Retrospects. Here the questioning is led by an experienced external facilitator. The process is an asking process - structured, quality assured, and aimed at answering (in advance) the likely questions from future projects.

Asking is the most powerful way to drive knowledge transfer - Pull is more powerful than Push

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?

Source publicdomainpictures.net

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 sure. 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:

• Making sure it is owned
• Making sure it is collected and stored in findable places (the knowledge supermarket - also see my post on "a haystack is no place to store a needle")
• Making sure it is named properly
• Making sure it is tagged and categorised.

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. 

Balancing knowledge supply and demand

If we view the flow of knowledge within an organisation as a Market, then we need to address the issues of supply and demand, and there are many advantages to starting by stimulating demand.

We can look at the flow of knowledge within an organisation as a market connecting the suppliers of knowledge and users of knowledge; the people in whose minds the knowledge is buried, and the people and teams who need access to that knowledge.

Knowledge is created through experience and through the reflection on experience, in order to derive guidelines, rules, theories, heuristics and doctrines. Knowledge may be created by individuals, through reflecting on their own experience, or it may be created by teams reflecting on team experience. It may also be created by experts or communities of practice reflecting on the experience of many individuals and teams across an organisation. The individuals, teams and communities who do this reflecting can be considered as ‘knowledge suppliers’. 

Knowledge is applied within organisational activity by individuals and teams. They can apply their own personal knowledge and experience, or they can look elsewhere for knowledge – to learn before they start. The more knowledgeable they are at the start of the activity or project, the more likely they are to avoid mistakes, repeat good practice, and avoid risk. These people are ‘knowledge users’.

Once we have knowledge suppliers and users, we have a marketplace for knowledge, where suppliers and users come together and exchange a "commodity" - knowledge. Knowledge is not like a normal commodity in that the supplier does not lose the knowledge, and both supplier and user get to keep the knowledge which has been exchanged.  However a marketplace analogy is a popular one in KM terms, and its an analogy I would like to explore here.

A marketplace works when there is supply and demand - suppliers and users. Supply and demand is at the base of much economic theory, and the concept of an equilibrium market as applied to normal products is that supply and demand will match each other through the mechanism of price adjustment.  When supply and demand are out of synch, then prices adjust as follows:

• When demand exceeds supply there is a shortage in the market and prices rise until demand decreases
• When supply exceeds demand, there is a glut in the market and prices fall until demand increases.

We see this very clearly in the oil markets. When oil supply falters, prices skyrocket. When oil production picks up, for example through the advent of shale-oil, prices fall.   

This relationship works with established commodities - any new product will create its own demand, at least for a while. There was no market for mp3 players before they were invented, and no market for Rubik's cubes or Pokemon until it was stimulated by supply of these new playthings.  After a while this "fad effect" wears off, and companies seek to stimulate continued demand through marketing and advertising in order to keep prices high. 

The Knowledge Market

In a Knowledge market there is no monetary price payable for knowledge, at least not within any one organisation. The price that a user pays for knowledge is the degree of effort they will put in to get it, and the amount of searching, filtering, asking and browsing they are prepared to do.

The diagram above shows four potential states for the Knowledge Market within an organisation.

• Where there is low supply and low demand, there is no knowledge market.

• Where there high supply and high demand, there is an equilibrium knowledge market, and to reach this level should be the Knowledge manager's goal.

• Where there is high supply and low demand, we find the typical problem area of knowledge oversupply. Here we find the huge databases nobody ever reads, the massive lessons learned systems with no lessons re-use, the communities or social groups where announcements and notifications outweigh the questions. The effect of this oversupply is both to introduce waste into the system, and also to destroy value. Larry Prusak said that the best way to de-knowledge knowledge is through oversupply.  Oversupply would not be problem if the price/cost of the knowledge dropped to compensate, but in fact the opposite happens. The more you oversupply knowledge, the more time and effort it costs to search, sift and sort through until you find the knowledge you need. Oversupply increases cost and decreases demand even further.

• Where there is low supply and high demand, we find the less typical problem area of knowledge undersupply. Here we find lots of people looking for knowledge, but little knowledge to find. The effect of this undersupply is to make people look harder, and to seek for knowledge even if it is not yet documented. They start asking people, talking to people, and eventually finding knowledge in its richest state - tacit knowledge. What documented knowledge exists becomes highly valued.

The route to equilibrium

The instinct for many Knowledge Managers is to create an equilibrium Knowledge Market by stimulating supply, for example by capturing knowledge, rewarding knowledge publishing, creating databases, promoting "knowledge sharing", or "working out loud". 

Unfortunately stimulating supply without stimulating demand leads straight into the issue of knowledge oversupply, and once this issue has arisen and knowledge has been devalued as a result, it can be very hard to escape. 

Better to take the green arrow in the diagram above, and start by stimulating demand for knowledge.  You do this by asking management to set the expectation that people and projects will learn before doing, and by promoting knowledge gap analysis, peer assists,  question-driven communities of practice, and "knowledge seeking".  Better to have the seekers outnumber the sharers, and to watch the value of knowledge rise as the seekers find what they need, apply it, and gain value as a result. 

Begining by stimulating demand avoids the common pitfall of the knowledge glut and a devaluation of knowledge.