4 ways to increase your "KM clock speed"

According to Erick Thompson, assistant VP for knowledge exchange, the St Paul companies, "KM initiatives should also focus on the speed factor. Companies have to learn how to learn faster". 

Clock Zoom by Rajiv Vishwa on Flickr

The world is increasingly a competitive learning field. In the past, when progress was slower and the rate of change was lower, an organisation could compete on its products, its patents, its reputation and on its people. However the rate of change is increasing, and companies need to adapt.

Markets are changing, customers are changing, expectations are changing, regulations are changing, the world is changing, and it is changing faster and faster. If companies are to adapt, they need to unlearn old habits and learn new ones. And in a competitive world, the fastest learner wins.

The British Army takes a similar view: you have to try to get inside the enemy's OODA (observe, orientate, decide, act) loop. If you generate faster tempo (rate of learning relative to that of the enemy), you will win.

So how do you hack the clock speed on your internal Knowledge Management cycle? Here are 4 steps.

1. Set targets
How long should it take to be able to find basic knowledge on your Intranet? How long should it take to receive an answer from a CoP? How long should it take before a new lesson is embedded into business process? Set some aggressive targets, like the senior manager at McKinsey who declared that all CoP questions should find an answer within a day.

2. You build the knowledge bases that cover routine activity
Any knowledge that is sufficiently mature, simple, and context-independent should be documented online in an easily findable location. All of your process documentation, manuals, training material should be put onto a wiki or similar knowledge base.

3. You build your Communities of Practice
Any knowledge that is less mature, more complex or more context-dependent may not be documented. Ensure you create the networks of people through which this knowledge can be transferred. Focus the CoP on problem solving and on answering questions if you want it to perform rapidly. Focus on Pull, not Push. 

4. You increase your lesson-learning speed through active lessons management
This blog post describes two lessons learned systems - one which takes 2 years to make changes based on new lessons, and one which takes a couple of weeks. You cannot afford to wait years for lessons to be embedded. Each unembedded lesson is a lesson currently unlearned, and an unlearned lesson carries the risk of reinvented wheels and repeat mistakes. Ensure you have an effective Lessons Management system, with a person or team in charge of making sure it is working well and quickly.

And here's a 5th way, for good measure


5. Measure against the targets you set.
Collect, and report, "speed of learning" metrics. Your dashboard should include online search time, the time to reply to CoP questions, and the time it takes to a) document and b) embed lessons. These are measures of your learning clock-speed. Seek to keep these times as low as possible, and continuously decreasing.

7 ways to speed up your KM

Just doing KM well is not enough, you have to do KM at the required speed. 

Public domain image from Pixnio

The world is changing, and organisations need to learn faster than the speed of change if they are to survive. According to Erick Thompson, assistant VP for knowledge exchange, the St Paul companies, "KM initiatives should also focus on the speed factor. Companies have to learn how to learn faster" (quote taken from Mahadmohan Rao's book ""Leading with Knowledge"). 

The world is increasingly a competitive learning field. In the past, when progress was slower and the rate of change was lower, an organisation could compete on its products, its patents, its reputation and on its people. However the rate of change is increasing, and companies need to adapt.  Markets are changing, customers are changing, expectations are changing, regulations are changing, the world is changing, and it is changing faster and faster. If companies are to adapt, they need to unlearn old habits and learn new ones. And in a competitive world, the fastest learner wins.

The British Army takes a similar view: you have to try to get inside the enemy's OODA (observe, orientate, decide, act) loop. If you generate and use knowledge at a faster tempo than your competitor (a faster rate of learning than the enemy), you will win.

So how do you increase the speed of your internal Knowledge Management cycle? Here are 7 ways.

1. Set targets
How long should it take to be able to find basic knowledge on your Intranet? How long should it take to receive an answer from a CoP? How long should it take before a new lesson is embedded into business process? Set some aggressive targets, like the senior manager at McKinsey who declared that all CoP questions should find an answer within a day, or the "three ones" target set by a Chinese knowledge manager ("a search for job-related knowledge should be successful within 1 minute, a question to a CoP should be answered within one day, and lessons from a closed project should be available to the organisation within one month").

2. Build your Communities of Practice
Any knowledge that is less mature, more complex or more context-dependent may not be documented. Ensure you create the networks of people through which this knowledge can be transferred. Focus the CoP on problem solving and on answering questions if you want it to perform rapidly. Focus on Pull, not Push. Ensure the community facilitator helps ensure questions are answered promptly.

3. Build the knowledge bases that cover routine activity
Any knowledge that is sufficiently mature, simple, and context-independent should be documented online in an easily findable location. All of your process documentation, manuals, training material should be put onto a wiki or similar knowledge base so people have it at their fingertips.

4. Ensure active lessons management
In a previous blog post I described two lessons learned systems - one which takes 2 years to make changes based on new lessons, and one which takes a couple of weeks. The second system is obviously far more efficient. You cannot afford to wait years for lessons to be embedded. Each unembedded lesson is a lesson currently unlearned, and an unlearned lesson carries the risk of reinvented wheels and repeat mistakes. Ensure you have an effective Lessons Management system, with a person or team in charge of making sure it is working well and quickly.

5. Update your knowledge bases as soon as new knowledge becomes available
There is no point in updating the knowledge bases annually, if the organisation needs to learn more rapidly. Lessons from the lesson management system, or answered questions from the CoPs, or results of trials and prototypes, should find their way into the knowledge base as quickly as possible. I was with a client last month, and they were feeding lessons into standards documents which they could only update annually, but they could at least collect new knowledge in a "pending updates" annex to the standard.

6. Measure against the targets you set.
Collect, and report, "speed of learning" metrics. Your dashboard should include online search time, the time to reply to CoP questions, and the time it takes to a) document and b) embed lessons. These are measures of your learning clock-speed. Seek to keep these times as low as possible, and continuously decreasing.

7. Fix any problems you see.
The measures that you collect will show you where there are delays and bottlenecks in your KM framework or workflow. Make sure you act on these to remove the bottlenecks.

Once the KM framework is in place, use these 7 methods to optimise your learning speed.

Effective learning is good, speedy and effective learning is even better.

Whatever your business plan, it's wrong. And it doesn't matter so long as you can learn fast enough.

The world is too complex for us to get things right first time. So what matters is the speed at which we adapt and learn.

Image from wikimedia commons

The British historian Michael Howard wrote, on the subject of military doctrine,

"I am tempted to say that whatever doctrine the armed forces are working on now, they have got it wrong. I am also tempted to declare that it does not matter. What does matter is their ability to get it right quickly, when the moment arrives......When everybody starts wrong, the advantage goes to the side which can most quickly adjust itself to the new and unfamiliar environment and learn from its mistakes."

In a complex and changing environment, it is the agile and the adaptive who survive. This is as true in the marketplace as it is on the battlefield. Planning is essential, but plans are not enough. No plan of battle ever survives contact with the enemy, and no commercial strategy or marketing plan survives contact with the market, the customer and the competition.

If Howard is right for business as well as for the Military and that the advantage goes to the organisation that most quickly learns from its mistakes, then Knowledge Management and Organisational learning is a survival strategy.

An organisation must be confident enough to embark into the unknown, prepared to modify or even abandon processes, practices and plans, based on focused and high-quality learning. Knowledge Managers must attend to

• Increasing the clock speed" of organisational learning
• Removing the waste from the knowledge supply chain
• Maximising signal to noise in knowledge transfer, and
• Bursting the knowledge bubbles.

An organisation can then learn it's way forward in an agile way, learning from mistakes and successes, "sounding the way forward" to find the safe passage.

Knowledge has a shrinking half-life, and where knowledge has a short half-life, Knowledge Management is not about documenting and protecting "what you know", it is about how fast you can know something new, and how easily you can let go of the old. That's what will win you the battle with the competition.

 Colonel Ed Guthrie of the US Army used to liken it to the aerial dogfights in world war 1.

"In those days" he used to say, "It was about getting inside the other guy's turning circle. That's what would win you the engagement. Now it's about getting inside the other guy's learning circle."

So whatever your business plan is, it's wrong, and it does not matter. What does matter is your organisations ability (enabled by Knowledge Management) to quickly adjust itself to the new and unfamiliar environment and learn from its mistakes and successes.

Your business plan is wrong. That doesn't matter if you can learn fast enough.

The world is too complex for us to get things right first time. So what matters is the speed at which we adapt and learn.

Image from wikimedia commons

The British historian Michael Howard wrote, on the subject of military doctrine,

"I am tempted to say that whatever doctrine the armed forces are working on now, they have got it wrong. I am also tempted to declare that it does not matter. What does matter is their ability to get it right quickly, when the moment arrives......When everybody starts wrong, the advantage goes to the side which can most quickly adjust itself to the new and unfamiliar environment and learn from its mistakes."

In a complex and changing environment, it is the agile and the adaptive who survive. Everyone starts wrong, but the adaptive get righter quicker.

This is as true in the marketplace as it is on the battlefield. Planning is essential, but plans are not enough. No plan of battle ever survives contact with the enemy, and no commercial strategy or marketing plan survives contact with the market, the customer and the competition.

If Howard is right for business as well as for the Military, and that the advantage goes to the organisation that most quickly learns from its mistakes, then Knowledge Management and Organisational learning is a survival strategy.

An organisation must be confident enough to embark into the unknown, prepared to modify or even abandon processes, practices and plans, based on focused and high-quality learning. Knowledge Managers must attend to

• Increasing the clock speed" of organisational learning to increase your adaptation rate
• Removing the waste from the knowledge supply chain to make KM more lean and efficient
• Maximising signal to noise in knowledge transfer to make the learning signal clearer, and
• Bursting the knowledge bubbles to make sure the decision makers are open to new knowledge. 

An organisation can then learn its way forward in an agile way, learning from mistakes and successes, "sounding the way forward" to find the safe passage. This is as true in the post-Covid recovery world as it ever has been. 

Knowledge has a shrinking half-life, and where knowledge has a short half-life, Knowledge Management is not about documenting and protecting "what you know", it is about how fast you can know something new, and how easily you can let go of the old. That's what will win you the battle with the competition.

 Colonel Ed Guthrie of the US Army used to liken it to the aerial dogfights in world war 1.

"In those days" he used to say, "It was about getting inside the other guy's turning circle. That's what would win you the engagement. Now it's about getting inside the other guy's learning circle."

So whatever your business plan is, it's wrong, and it does not matter. What does matter is your organisations ability (enabled by Knowledge Management) to quickly adjust itself to the new and unfamiliar environment and learn from its mistakes and successes.

How to remove waste from Knowledge Management

This updated reprise from the archives uses the Lean Supply Chain as an analogy for KM, and suggests ways in which we can remove waste from Knowledge Management.

There is a lot of value on using metaphors as different ways to look at KM, this blog has frequently used the metaphor of a Supply Chain.

Knowledge has a user - the knowledge worker who needs to make a decision or plan an action - and it has a source - usually someone else's experience, or the synthesised knowledge of a community of practice. The KM supply chain consists of getting the knowledge from the source to the user in the most effective,  efficient and timely manner.

In the industrial world, much work has been done on the concept of  a Lean Supply Chain - one in which all waste has been removed.  A Lean supply chain is one where components reach the manufacturer "just in time", with minimal additional processing, and in a form where they can be used immediately.

Can we eliminate the waste from our Knowledge supply chain, and end up with Lean Knowledge Management -  where knowledge reaches the knowledge worker "just in time", with minimal additional processing, and in a form where it can be applied immediately?

Let's look at the 7 wastes identified within Lean, and see what we can do to reduce these in the KM context.

Waste #1. Over-production—producing more than and/or ahead of demand.  

Over-production of Knowledge is very common in Knowledge Management.  We see this particularly in push-based enterprise social media, where we can be bombarded with hundreds of messages, very few of which are relevant. This blog post describes overproduction taken to the extreme, with massive push of (often duplicated) content resulting in destruction of value, with people spending far more time creating content, than time was saved re-using it. It is no coincidence that Lean Supply Chain is pull-based, and Lean Knowledge Management should be pull-based as well.

Waste #2. Waiting. 

Knowledge Management can be really helpful, but only if the knowledge arrives on time to impact the decision. A lean KM supply chain will focus on the "clock speed" of KM, to ensure questions receive answers as soon as possible, and new knowledge is identified and embedded into process within minimum time.

 Waste # 3. Unnecessary transport of materials.

In our knowledge management world, this really refers to hand-off, and to whether the chain between knowledge supplier and knowledge user can be made as short as possible. Communities of practice, for example, where "ask the audience"-type questions can be asked, and answered directly by the knowledge holder, will minimise the number of handoffs.  With a large community of practice, everyone is at One Degree of Separation.

Waste # 4. Non-value added processing—doing more work than is necessary. 

We often see this in lesson-learning systems, where the work of sifting and sorting multiple lessons or multiple search-hits has to be done by the knowledge user (the knowledge user searches the system, finds 20 hits giving conflicting or multiple advice, and needs to work out which is right, which is misleading, which can be combined, and which is obsolete). Far better is a system where the sifting and sorting is done once, at source, by the lessons management team or the relevant subject matter expert, so that right answers are combined and preserved and obsolete knowledge removed. Then instead of each reader doing the work of synthesis, the knowledge arrives already synthesised.

 Waste # 5. Unnecessary motion. 

In KM terms, this could be unnecessary online motion - the need to visit multiple databases, multiple knowledge bases, a separate CoP system, another place for Yammer feed etc. It is unfortunately all too common to see a KM platform with separate areas for Standards, Best Practice, Lessons Learned, Video etc, so a person searching for knowledge on a topic - Electrical Engineering Tools for example -  will need to look in all four areas t get a complete picture. Far better to have a topic based portal, where the Electrical Engineer Tools section of the portal or wiki will contain standards, best practices and lessons on the topic of Electrical Engineer Tools, with embedded video from the subject matter experts where appropriate.

Waste # 6. Excess inventory— frequently resulting from overproduction.  

Lessons systems jammed with lessons, hundreds of hits from the search engine, knowledge bases crammed with near-duplicate content, or obsolete content, or contradictory content - all of these represent the waste associated with excess inventory. Part of the role of the process owner in KM is to ensure that the knowledge inventory is well managed and free from dross.  This does not mean eliminating knowledge which might be useful some day; it means eliminating duplicates, wrong knowledge, and otherwise removing noise from the system and leaving the signal behind.

Waste # 7. Defects, or the cost of wrong knowledge. 

Wrong knowledge is worse than no knowledge. Any KM system needs to have a quality assurance step, whether this is Community QA of a wiki, or editorial QA of a knowledge base, of Quality Assurance of lessons at source through use of good facilitation.

The lean supply chain analogy allows us a new way to look at KM, and the 7 wastes give us a filter for improving the way we work. If we could make our KM supply chains truly lean, we could considerably improve the way our organisations use knowledge.

7 failure modes for knowledge transfer failure

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

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

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

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

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

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

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

Now my two

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

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

Measuring the waste in the KM supply chain

If KM is a lean supply chain of knowledge, how can you measure the waste in order to eliminate it?

Shredded waste, image from wikimedia commons

The concept of Knowledge Management as a supply chain is one I have been incubating for a few years (see here, here, here, here for example). I presented the idea at KM World last week, and got some very good feedback.

I presented the idea of KM as a supply chain, providing knowledge to the knowledge worker, and used the concept of the lean supply chain to suggest that we could eliminate "the 7 wastes", and make the transfer of knowledge more efficient.

Then one person asked "how can we measure that waste"?

I didn't know the answer, but said I would think about it and blog an answer.

Here it is.

• Waste #1. Over-production—producing more knowledge than we need.

We might measure this by measuring how much of what is published is actually useful. We could for example look at the read-rates of content (how much content never gets read), or the duplication of content. We could look at the push/pull ratio in communities of practice, balancing the number of question-led discussions against the number of publication-based discussions (see this analysis of linked-in discussions, for example).

• Waste #2. Waiting. 

Here we measure the clock-speed of knowledge, such as the time it takes for a community question to be answered, the time it takes to find relevant synthesised knowledge, or the time it takes for lessons to be a) collected and b) embedded into guidance.

• Waste # 3. Unnecessary transport of materials. 

 In our knowledge management world, this really refers to hand-off, and we might measure the number of links or steps between knowledge supplier and user. Communities of practice, for example, where "ask the audience"-type questions can be asked, and answered directly by the knowledge holder, will minimise the number of handoffs. With a large community of practice, everyone is at One Degree of Separation. 

• Waste # 4. Non-value added processing—doing more work than is necessary. 

We might measure this by looking at the degree of processing the end user has to do to get an answer to their question, and how much synthesising is done by the user, which could be done further up the supply chain.  For example, does a user have to read and understand all lessons in a database on a particular topic, or have these already been synthesised into guidance?

• Waste # 5. Unnecessary motion. 

We measure this by counting the number of places the knowledge user needs to go to in order to find relevant knowledge. Do they have to visit every project file to find lessons, or are the lessons collected in one place? Is there one community of practice to go to, or many? Linked-in, for example, has (or had at one time) 422 discussion groups covering the topic of Knowledge Management rather than only one. That is a waste of 421 groups (99.8% waste).

• Waste # 6. Excess inventory

Like waste 1, we look at the unnecessary, duplicate or unread knowledge in the knowledge bases and lessons learned systems.

• Waste # 7. Defects

Here we measure now much knowledge is out of date, and how much is poor quality. Some organisations, for example, measure the quality of lessons with a lessons database, and often find that much of the content is of very poor quality.

Removing waste from the KM supply chain

There is a lot of value on using metaphors as different ways to look at KM, and recently I have gained a lot of value from using the metaphor of a Supply Chain.  Can we use a Lean Supply Chain as a model for Lean KM?

leaning by acute_tomato on Flickr

Knowledge has a user - the knowledge worker who needs to make a decision or plan an action - and it has a source - usually someone else's experience. The KM supply chain consists of getting the knowledge from the source to the user in the most effective,  efficient and timely manner.

In the industrial world, much work has been done on the concept of  a Lean Supply Chain - one in which all waste has been removed.  A Lean supply chain is one where components reach the manufacturer "just in time", with minimal additional processing, and in a form where they can be used immediately.

Can we eliminate the waste from our Knowledge supply chain, and end up with Lean Knowledge Management -  where knowledge reaches the knowledge worker "just in time", with minimal additional processing, and in a form where it can be applied immediately?

Let's look at the 7 wastes, and see what we can do.

Waste #1. Over-production—producing more than and/or ahead of demand.  

Over-production of Knowledge is very common in Knowledge Management.  We see this particularly in push-based enterprise social media, where we can be bombarded with hundreds of messages, very few of which are relevant. This blog post describes overproduction taken to the extreme, with massive push of (often duplicated) content resulting in destruction of value, with people spending far more time creating content, than time was saved re-using it. It is no coincidence that Lean Supply Chain is pull-based, and Lean Knowledge Management should be pull-based as well.

Waste #2. Waiting. 

Knowledge Management can be really helpful, but only if the knowledge arrives on time to impact the decision. A lean KM supply chain will focus on the "clock speed" of KM, to ensure questions receive answers as soon as possible, and new knowledge is identified and embedded into process within minimum time.

 Waste # 3. Unnecessary transport of materials.

In our knowledge management world, this really refers to hand-off, and to whether the chain between knowledge supplier and knowledge user can be made as short as possible. Communities of practice, for example, where "ask the audience"-type questions can be asked, and answered directly by the knowledge holder, will minimise the number of handoffs.  With a large community of practice, everyone is at One Degree of Separation.

Waste # 4. Non-value added processing—doing more work than is necessary. 

We often see this in lesson-learning systems, where the work of sifting and sorting multiple lessons or multiple search-hits has to be done by the knowledge user. Far better is a system where the sifting and sorting is done once, at source, by the lessons management team or the relevant subject matter expert. Then instead of each reader doing the work of synthesis, the knowledge arrives already synthesised.

 Waste # 5. Unnecessary motion. 

In KM terms, this could be unnecessary online motion - the need to visit multiple databases, multiple knowledge bases, a separate CoP system, another place for Yammer feed etc. The best and most efficient KM systems have everything in a single portal - the community forum, the knowledge base etc etc.

Waste # 6. Excess inventory— frequently resulting from overproduction.  

Lessons systems jammed with lessons, hundreds of hits from the search engine, knowledge bases crammed with near-duplicate content, or obsolete content, or contradictory content - all of these represent the waste associated with excess inventory. Part of the role of the process owner in KM is to ensure that the knowledge inventory is well managed and free from dross.  This does not mean eliminating knowledge which might be useful some day; it means eliminating duplicates, wrong knowledge, and otherwise removing noise from the system and leaving the signal behind.

Waste # 7. Defects, or the cost of wrong knowledge. 

Wrong knowledge is worse than no knowledge. Any KM system needs to have a quality assurance step, whether this is Community QA of a wiki, or editorial QA of a knowledge base.


The lean supply chain analogy allows us a new way to look at KM, and the 7 wastes give us a filter for improving the way we work. If we could make our KM supply chains truly lean, we could considerably improve the way our organisations operate.

How to measure the waste in the KM supply chain

If KM is a lean supply chain for knowledge, how can you measure the amount of waste in the chain?

Shredded waste, image from wikimedia commons

I have often used the concept of a knowledge supply chain as a way of describing Knowledge Management; the supply chain being a mechanism for providing knowledge to the knowledge worker in an efficient and effective way, just as a materials supply chain provides materials to the manual worker. 

If you go one step further, you can use the principles of the lean supply chain, as applied to materials supply, to make the knowledge supply chain even more efficient. We do that by eliminating "the 7 wastes" of overproduction, waiting, unnecessary transport, non-value-add processing, unnecessary motion, excess inventory, and defects. 

But how can we measure the current level of waste in the knowledge supply chain? Here's how.

• Waste #1. Over-production—producing more knowledge than we need.

We might measure this by measuring how much of what is published is actually useful. We could for example look at the read-rates of content (how much content never gets read), or the duplication of content. For example the World Bank commissioned a study of "Which World Bank Reports Are Widely Read", which was able to analyse which of the reports were widely downloaded and cited, and which remained unread, and therefore represent over-production.  A lot of effort and knowledge goes into these reports, and the last thing the World Bank wants is to create reports which are never downloaded.  We could also look at the push/pull ratio in communities of practice, balancing the number of question-led discussions against the number of publication-based discussions (see this analysis of linked-in discussions, for example). 

• Waste #2. Waiting. 

Here we measure the clock-speed of knowledge, such as the time it takes for a community question to be answered, the time it takes to find relevant synthesised knowledge, or the time it takes for lessons to be a) collected and b) embedded into guidance.

• Waste # 3. Unnecessary transport of materials. 

 In our knowledge management world, this really refers to hand-off, and we might measure the number of links or steps between knowledge supplier and user. Communities of practice, for example, where "ask the audience"-type questions can be asked, and answered directly by the knowledge holder, will minimise the number of handoffs. With a large community of practice, everyone is at One Degree of Separation.  A wiki, where knowledge suppliers can update knowledge themselves without going through unnecessary editorial process, can also minimised handoffs.

• Waste # 4. Non-value added processing—doing more work than is necessary. 

We might measure this by looking at the degree of processing the end user has to do to get an answer to their question, and how much synthesising is done by the user, which could be done further up the supply chain.  For example, does a user have to read and understand all lessons in a database on a particular topic, or can you make sure that these have already been synthesised into guidance?

• Waste # 5. Unnecessary motion. 

We measure this by counting the number of places the knowledge user needs to go to in order to find relevant knowledge. Do they have to visit every project file to find lessons, or are the lessons collected in one place? Is there one community of practice to go to, or many? Linked-in, for example,  had at one time 422 discussion groups covering the topic of Knowledge Management rather than only one. That is a waste of 421 groups (99.8% waste).

• Waste # 6. Excess inventory

Like waste 1, we look at the unnecessary, duplicate or unread knowledge in the knowledge bases and lessons learned systems.

• Waste # 7. Defects

Here we measure now much knowledge is out of date, and how much is poor quality. Some organisations, for example, measure the quality of lessons with a lesson management system, and often find that much of the content is of very poor quality. If your users are telling you that the lesson management is full of poor quality lessons, then you have a defect problem.

All of these metrics are indicators that your KM framework, or knowledge supply chain, is far from efficient.