The Knowledge Manager as Supply Chain manager - an analogy

If Knowledge Management is like a supply chain for knowledge, then the Knowledge Manager is the Supply Chain manager.

Image from wikipedia japan

I have blogged many times about the analogy between Knowledge Management and a supply chain for knowledge. Like all analogies, this is limited (the view of the supply chain, which implies a supplier and a user, can be balanced by a view of knowledge co-creation and emergence, for example), but can also be a very useful lens through which to examine KM.

 A corollary of this idea is that the Knowledge Manager for the organisation or division takes the role of the Supply Chain manager for knowledge.  The knowledge manager does not create the knowledge nor use it, but is accountable for its creation and supply to the user.

We can explore this idea by looking at the job description of a supply chain manager, and seeing how this translates into KM terms. The supply chain job description below is taken from here and here.

Supply chain manager job description	Knowledge manager job description
Supply Chain Managers plan, develop, optimize, organize, direct, manage, evaluate, and are accountable and/or responsible for some or all of the supply chains processes of organizations.	Knowledge Managers plan, develop, optimize, organize, direct, manage, evaluate, and are accountable and/or responsible for some or all of the knowledge management processes of organizations.
Diagram supply chain models to help facilitate discussions with customers.	Diagram knowledge management models to help facilitate discussions with knowledge users.
Select transportation routes to maximize economy by combining shipments or consolidating warehousing and distribution.	Select knowledge transfer approaches to maximize efficiency and effectiveness
Assess appropriate material handling equipment needs and staffing levels to load, unload, move, or store materials.	Assess appropriate KM staffing levels for knowledge creation, transfer, storage, synthesis and re-use.
Confer with supply chain planners to forecast demand or create supply plans that ensure availability of materials or products.	Confer with the business to forecast the demand for knowledge; create strategies and plans that ensure availability of knowledge as and when needed.
Define performance metrics for measurement, comparison, or evaluation of supply chain factors, such as product cost or quality.	Define performance metrics for measurement, comparison, or evaluation of KM factors, such as knowledge availability or quality.
Monitor supplier performance to assess ability to meet quality and delivery requirements.	Monitor knowledge supplier performance (eg the the knowledge supply from projects or from research) to assess ability to meet quality and delivery requirements.
Analyze information about supplier performance or procurement program success.	Analyze information about knowledge supplier performance or knowledge creation / acquisition program success.
Meet with suppliers to discuss performance metrics, to provide performance feedback, or to discuss production forecasts or changes.	Meet with knowledge suppliers to discuss performance metrics, to provide performance feedback, or to discuss new knowledge needs.
Design or implement plant warehousing strategies for production materials or finished products	Design or implement storage and synthesis strategies for documented knowledge
Analyze inventories to determine how to increase inventory turns, reduce waste, or optimize customer service.	Analyze knowledge stores to determine how to increase re-use, reduce waste, or optimize customer service.
Review or update supply chain practices in accordance with new or changing environmental policies, standards, regulations, or laws.	Review or update KM practices in accordance with new or changing standards and requirements.
Implement new or improved supply chain processes.	Implement new or improved KM processes.

But what's different?

The main difference between the role of the supply chain manager and the role of the Knowledge Manager is that the supply chain manager can assume that there is a customer for their services. They can assume that there are manufacturing workers who are ready and waiting for the supply of parts and materials.

The  Knowledge Manager cannot assume this.

The Knowledge Manager also has to work as a Demand Chain Manager; stimulating the demand for knowledge, and introducing the process and systems by which knowledge is sought, as well as those by which it is supplied.

Also, as stated above, there are elements of KM which are more collaborative and less of a flow process.

But where knowledge flows from supplier to user, then the knowledge manager can see herself acting as a supply chain manager, with some of the accountabilities listed above.

Revolutionising the productivity of the knowledge worker - 4, becoming lean and efficient

This week I have been blogging about the challenge of revolutionising the productivity of the knowledge worker; the challenge which Peter Drucker set for us.

The lean working environment for the manual
worker (image from greenhousecanada.com).
Does the working environment for the knowledge
worker look like this?

We have looked at the division of knowledge labour, the automation/augmentation of knowledge work, and the knowledge supply chain. Now we look at how to make the knowledge work-flow efficient.

When we look at how the productivity of the manual workers has been revolutionised, then the most recent advances come from lean production, lean working and the lean supply chain have all played their part. The Manufacturing Advisory Service (quoted here) claims a 25% increase in productivity through lean principles - a small increment compared to the difference made by division of labour, automation/augmentation and an effective supply chain, but still a significant factor in the continuous improvement of productivity. Lean is also a mindset - a relentless focus on adding value on behalf of the customer and removing waste effort and stock.

However a lean and efficient approach has not yet reached knowledge management. 

Certainly most organisations now apply a division of knowledge labour, all are applying automation/augmentation to knowledge work, and many have the concept of a knowledge supply chain, supplying knowledge (or insights, experiences etc) to the knowledge workers, at the time and place they need it, to the required standard and quality, in a deliberate and systematic manner.  

However our track record of delivering that knowledge in a lean and efficient way is poor, and there is little or no sign of a relentless focus on removing waste and adding value.  Metrics measure the completeness of the KM framework and its effectiveness, but rarely its efficiency. 

Knowledge bases are often full and clumsy to use, poorly structured and indexed, with duplicate, outdated or irrelevant material. Knowledge workers are often required to use multiple search engines or to visit multiple sites, social media streams are unfiltered and full of noise, knowledge is often synthesised, often unfindable, and usually is poorly tagged and labelled.

All of this makes knowledge seeking a massive chore, which it is easier to skip than undertake.

A lean approach to Knowledge Management would involve eliminating the 7 wastes, such as

• Over-production of knowledge, which then becomes noise in the system
• Waiting for knowledge, and a slow turnover speed of knowledge
• Unnecessary hand-off of knowledge, with unnecessary steps in the chain between knowledge supplier and knowledge user  
• Non-value added processing—doing more work than is necessary. We often see this in lesson-learning systems, where the work of sifting, sorting and synthesising multiple lessons or multiple search-hits has to be done by the knowledge user. 
• Unnecessary "motion" - the need to visit multiple databases, multiple knowledge bases, a separate CoP system etc 
• Excess knowledge inventory— frequently resulting from overproduction.
• Defective knowledge.

Lean KM is the last of the four components to drive knowledge worker productivity. Together these 4 components can be revolutionary.

If we can have a lean and efficient knowledge supply chain, using automation and augmentation to deliver high quality knowledge to knowledge workers in a divided system of knowledge work, then we will approach Peter Drucker's initial vision of a 50-fold increase in productivity of the knowledge workers.

Revolutionising the productivity of the knowledge worker - part 3, the knowledge supply chain

Over the last two days I have blogged about the challenge of revolutionising the productivity of the knowledge worker, which Peter Drucker set for us. We have looked at the division of knowledge labour, and the automation/augmentation of knowledge work. Today we look at the knowledge supply chain. 

Parts, by Andy Malmin, on Flickr

The productivity of the manual worker was revolutionised through the transformation from craftsman production to factory production. Work was divided and automated, and individuals took their part within a work chain, or production line. Partly finished work came to them automatically, together with the parts and tools they needed, they did their own tasks, added their own value, and passed the updated work on to the next person. 

This is the supply chain for manual workers, who make things; an organised mechanism for making sure that the components they need to do their job are ready at hand when needed. The supply chain can be an assembly line, or a more complex arrangement involving parts, suppliers and warehousing.

Knowledge workers, on the other hand, make decisions rather than things, and the raw material for knowledge workers is knowledge. 

Therefore in a world where knowledge work is divided (where we do not rely on experts who carry all the knowledge in their head) the knowledge worker needs partly finished knowledge to come to them automatically, together with the knowledge tools and additional knowledge they need, and when they have made their decisions and added their own value (often this is the innovation piece), then the updated work needs to be passed on to the next knowledge worker.

This is the vision of the organisation as a knowledge factory, or a knowledge assembly line, and for this to work, we need the knowledge supply chain.  Often the knowledge supply chain involves knowledge suppliers, and warehousing, just as a supply chain for parts. 

I have already blogged several times about the knowledge supply chain (see the relevant tab in the word cloud to the right). The knowledge supply chain is a new way of looking at an organisation of knowledge workers (predicted 20 years ago by Lord Browne of BP), and for ensuring that the correct knowledge reaches each knowledge worker, at the time and place they need it, to the required standard and quality, in a deliberate and systematic manner. Knowledge Management then becomes the supply chain for the knowledge worker; a parallel knowledge workstream that works alongside the project pr product workstream.

Few organisations have got this right. The service-desk sector, where providing correct knowledge (answers to customer questions) to the front line staff is a vital KM service, have models for providing knowledge to those who need it. Toyota have got it right (I believe). The Military, with its chains of accountability and with the supply of knowledge and information built into the Battle Rhythm, probably do it best. 

This vision of "Knowledge Management as a supply chain" requires a complete Knowledge Management Framework to be in place, with roles, processes, technologies and governance, with the sole purpose of supplying knowledge to the knowledge workers, to enable them to make the correct decisions.

In the next and final post of this series we look at the nature of this supply chain, and what it needs to become Lean.

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. 

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.

Running the KM "supply chain" on lean principles

If we see KM as a supply chain, supplying knowledge to the knowledge worker in order that they can make the right business decision, then we can apply concepts such as lean to optimise that supply chain.

There are other ways to use lean principles to improve KM, such as the removal of waste from the KM supply chain.  Another approach is to ensure that every step is driven by Pull. Nothing moves along a step in the supply chain unless it is pulled by the need from the next step. This ensures that supply is always "just in time" and that there is no wasteful build-up of unwanted inventory.

Let's see how Pull can drive the steps in the Knowledge supply chain.

Knowledge transfer through conversation and discussion

Pull-based discussion includes online discussion driven by questions, and face to face discussion in Peer Assists. The questions of the knowledge workers are answered from the experience of their peers/

Knowledge documentation

Rather than wait for project teams and work groups to volunteer knowledge, the knowledge owners conduct interviews and hold facilitated retrospects to draw out their tacit knowledge. They focus particularly on knowledge of high importance to the organisation.

Synthesis of knowledge into a knowledge store or knowledge base

The knowledge owners and subject matter experts seek for new knowledge to incorporate into the knowledge base and to synthesise with existing knowledge. They may look in the community discussions and the lessons learned system for new knowledge, or may convene community meetings to discover and incorporate existing good practice. The knowledge base may well be constructed as FAQs - the most "pull-based" way of storing knowledge. 

Review of documented knowledge

The knowledge workers use search to access relevant documented knowledge, or use a system where knowledge is presented automatically at each stage in a work process.

Pull is an unusual way to look at the knowledge cycle, but it can significantly streamline your KM efforts.

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.

Lesson learning as a supply chain

Another reprise from the archives - the idea of lessons being the "car parts" of knowledge

This post is a combination of three ideas, to see if they come up with something new.

• Idea number 1 - the idea of an organisation as a knowledge factory, sparked by Lord Browne's quote - "anyone in the organization who is not directly accountable for making a profit should be involved in creating and distributing knowledge that the company can use to make a profit"  

• Idea number 2 - the idea that corporate process is a compilation or synthesis of all the lessons learned over time  

• Idea number 3 - the idea that we can treat knowledge management as a supply chain, designed to get the right knowledge to the right people at the time they need to make decisions.

So the combination idea looks like this;

The inner ring is a supply chain where components are manufactured, and assembled into products (like a car plant, or a construction site).

The outer ring is the lesson learning cycle, one of the procedural loops in Knowledge Management. Please note that this is only one of the many ways in which KM works; this is the systematic push-driven cycle involving the collection of explicit lessons, and there are many other types of interaction in KM (push and pull, connect and collect).

In our analogy, we have lessons from experience being collected, distributed through lesson management, and assembled into continuously improving corporate processes, rather like car parts are created, distributed, and assembled into cars.  The links within this chain are as follows

1. The raw materials for the supply chain are the experiences of the individuals in the workplace, who are trying to apply the processes in different contexts, in a changing world.
2. The supplier of the raw materials therefore are the individuals themselves.
3. Experiences are manufactured into lessons through processes of analysis and discussion - team meetings such as Retrospects, and After Action Reviews. Through discussion and analysis, individual unconscious knowledge is made conscious, and the experiences of many individuals are combined into the lessons of the team or the lessons from an event. These lessons are the components - the car parts within the supply chain. 
4. Now we get into the Distribution part of the supply chain. We need to get those parts to the assembly plant. This is a part where many Lessons learned systems break down. They leave those parts (lessons) in the warehouse (database), and expect people to come and find them (remember that scene from raiders of the Lost Ark?). We need instead to have active lessons management, to push the lessons to those who need them.
5. Those who need them are (primarily) the people in charge of corporate process, who need to keep those processes fresh and updated as new learning comes in. The Process owners, or SMEs.
6. However that is not the end of the story. The assembled knowledge needs to get to the consumer - though the equivalent of car showrooms (community portals), or supermarkets (Intranets) or street markets (wikis).
7. The consumer is the knowledge worker. They apply the new knowledge, and in doing so, gain new experience. 

And so the cycle begins again.

7 Metrics for the KM supply chain

The Supply Chain analogy for KM suggests several metrics we can use.

I have often used the analogy of the supply chain as one way of thinking about KM. This involves looking at KM as a chain of processes supplying knowledge to the user.

This analogy has the benefit of thinking about KM from the point of view of the knowledge user. You can ask "If a person in this organisation were in need of a specific piece of knowledge to make a specific decision, what system is in place to make sure that this knowledge a) gets to the person on time, and b) is of the correct quality?"

And like any analogy, it brings with it many other ways to think about KM. Can we apply "Lean Supply Chain" thinking to KM, for example? Can we remove waste from our Knowledge Supply Chain? Can we think of the Knowledge Manager as a supply chain manager?

Or - the subject of our blog today - can we use common Supply Chain metrics to help us understand how to metricate KM?

Here are 7 metrics from the supply chain world which might help us decide on metrics for our Knowledge Management Framework.

• Backorders - unfulfilled orders from the customer. In KM terms, these might be search queries, or questions to a Community of Practice, which receive no answers. These are indications of the need to create knowledge resources for the user, and the number of unfilled requests is a proxy of the completeness of your knowledge base (both tacit and explicit).

• Cycle time. There are many definitions of cycle time in the Supply Chain world, but for KM the crucial cycle time is how long it takes from the first observation of new knowledge, to that knowledge being embedded in the knowledge bases, training courses and community of practice resources. Or in lesson-learned terms it might be the time from "Lesson identified" to "Lesson closed". In CoPs it might be the "question to answer" time.

• Defects - defective supplied material. This is a quality measure of your knowledge content, measuring how much of it is out of date, wrong, or unhelpful. You could measure the quality of lessons entering your lessons management system for example, or of articles published to a knowledge base, or of answers in a community forum.

• Fill Rate - the amount of ordered supplies filled on the first order. In KM, this might be the number of community questions answered by the first response, or the percentage of times the answer is found in the first search.

• Inventory costs - what it costs you to stock and manage your inventory (cost of stock, cost of warehouse, salaries of warehouse staff etc). In KM terms, this is the cost of operating your KM framework, including the cost of KM roles, the licence cost for KM software, and the time cost from populating the system. This represents the total costs to the business of operating KM.

• Gross margin return on inventory - the  gross margin divided by the inventory costs, a popular metric for retail stores. In KM terms, the gross margin would be the overall value of KM to the business, which you would track and estimate through success cases, value stories and metrics such as decreased costs or increased sales. It is in effect the KM ROI.

• Inventory turnover - the average annual use of your inventory; for example if a store carries 1000 items and sells 10,000 items a year, that's a 10 times inventory turnover. In KM terms this would be applied only to explicit knowledge, and you would measure the number of reads of knowledge articles divided by the number of articles.  You could of course get smarter, and you could look at which articles get the most reads and which get none at all.

Hopefully that gives you some ideas of a few more metrics you can use to make sure your Knowledge Supply Chain is working - delivering valuable knowledge to the knowledge works in your organisation in an efficient, reliable and effective way.

A vision of the Knowledge Supply Chain

One of the clearest visions for the Knowledge Supply Chain comes from the UK National Health Service (NHS).

Image from wikimedia commons

The analogue of a Supply Chain for Knowledge Management is one I have been using for a while now (see here, here and here for example), as a different way to look at the purpose of KM and the role of the Knowledge Manager. The Google definition of a supply chain is

the sequence of processes involved in the production and distribution of a commodity

and if that "commodity" is Knowledge, then the definition above could easily refer to Knowledge Management.

The knowledge supply chain is a new way of looking at an organisation of knowledge workers (predicted 20 years ago by Lord Browne of BP), and for ensuring that the correct knowledge reaches each knowledge worker, at the time and place they need it, to the required standard and quality, in a deliberate and systematic manner. Knowledge Management then becomes the supply chain for the knowledge worker.

So I was very interested to receive this link from Anne Brice to a paper which laid out exactly this Knowledge Supply Chain vision for the UK National Health Service (NHS) 12 years ago.

The Knowledge Supply Chain vision for the NHS

The paper linked above is a guest editorial written by Anne Brice (currently Head of KM for Public Health England) and Muir Gray (previously CKO for the NHS), describing the vision for a National Knowledge Service for health, and containing the following text:

The generation of the knowledge that people need is the first step in a supply chain. It is necessary but not sufficient, because knowledge has to reach the point where it is needed and be available when it is needed. The National Knowledge Service is committed to ensuring that decisions are based on best current knowledge wherever and whenever those decisions are being made. This requires the supply chain to be organized from the producer to the consumer, ensuring that:

• the knowledge that is needed is generated; 

• the knowledge that is generated is organized; 

• the knowledge that is organized is delivered to where decision-makers need it before and during the process of decision-making; 

• the organizations and individuals within health care systems have the skills and resources to find, appraise and use the knowledge.

This is one of the clearest visions I have seen of the Knowledge Supply Chain, covering the whole chain from supplier to user.  This vision is still in progress within the NHS. The original structure of a National Knowledge Service has changed along the way, and the vision now seems to be part of the Library and Knowledge services, focusing more on the middle of the chain - the organisation and delivery of electronic resources.

As Anne Brice said to me this week by email, "If the vision is still alive then it needs to evolve to stress the whole 'health system'. Given the current emphasis on prevention and reducing inequalities, this can only happen if it encompasses public health and social care, and not just the NHS".

It is therefore important that the current library-focused organization and delivery role is seen as part of a larger supply chain for health system knowledge, much as a warehouse management role is part of a larger supply chain for other commodities. 

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. 

The Knowledge Manager as Demand Chain manager

Part of the role of the Knowledge Manager is demand chain management, and this needs to be recognised in the job description.

Image from wikimedia commons

I blogged last week about the Knowledge Manager as a Supply Chain manager, and cross-rerenced a Supply Chain manager role description with parallel tasks for the Knowledge Manager.

However I also made the point that the Knowledge Manager needs to manage demand as well as supply. We already see this mentioned in KM job descriptions such as the following:

• UNDP analyst role- "facilitate demand and supply of knowledge"
• Legal Knowledge Manager - "Work with the Groups and the Knowledge Management Officer to assess the relevant knowledge needs, define and implement a plan to meet those needs, and establish mechanisms for regular review of the plan". 
• The US Army KM Officer - "Help the staff perform internal and external knowledge gap analyses. Create techniques to bridge gaps"
• Samsung Knowledge Manager - "Performs the task of establishing the direction and strategy of knowledge management activities by analyzing an enterprise’s management strategy and employees’ knowledge requests and planning knowledge management programs  
• Sample Job Description & Specification From CILIP - "To ensure that the information needs of the organisation are met in a timely, effective and efficient manner" which sort of implies that you need to analyse these needs.

However while the demand side is mentioned in these job descriptions, it is generally either one line, or part of one line, and outweighed by the supply side activities.

We can therefore compare a typical demand Chain Manager role description with potential demand-side elements of the KM role. This comparison leads us into a more rigorous approach to knowledge forecasting, such as statistical forecast models, and also highlights the area where Demand Chain management is weak, namely the stimulation of demand (which in most sales organisations would be addressed by Marketing).

Demand chain manager job description	Knowledge manager job description (demand side)
This role is responsible for all demand forecasting activities associated with customers and products.	This role is responsible for all activities associated with the demand for knowledge, including demand stimulation and demand forecasting
Develop demand forecasts (operational forecasts) at multiple levels of aggregation for multiple time horizons as part of a demand planning function.	Develop demand forecasts  for knowledge at multiple levels of aggregation for multiple time horizons as part of a KM planning or strategy function.
Review historical sales trends, research demand drivers, prepare forecast data, develop statistical forecast models, and evaluate forecast results.	Review historical use of knowledge, research drivers for knowledge demand, prepare forecast data, develop statistical forecast models, and evaluate forecast results.
Interact with sales, marketing, and customer finance to understand demand forecast drivers.	Interact with the business to understand the drivers for the future demand for knowledge.
Provide input to the Supply Planning organization in developing inventory strategies on existing items, new products, and product phase-outs.	Provide input to the KM and R&D organization in developing knowledge acquisition strategies.
(missing)	Promote the demand for knowledge within the organisation

The Knowledge Manager as Supply Chain manager

If Knowledge Management is like a supply chain for knowledge, then the Knowledge Manager is the Supply Chain manager.

Image from wikipedia japan

I have blogged many times about the analogy between Knowledge Management and a supply chain for knowledge, and am presenting this idea later today in KMUK.  A corrolory of this idea is that the Knowledge Manager then takes the role of the Supply Chain manager for knowledge.  The knowledge manager does not create the knowledge nor use it, but is accountable for its supply to the user.

We can explore this idea by looking at the job description of a supply chain manager, and seeing how this translates into KM terms. The supply chain job description below is taken from here and here.

Supply chain manager job description	Knowledge manager job description
Supply Chain Managers plan, develop, optimize, organize, direct, manage, evaluate, and are accountable and/or responsible for some or all of the supply chains processes of organizations.	Knowledge Managers plan, develop, optimize, organize, direct, manage, evaluate, and are accountable and/or responsible for some or all of the knowledge management processes of organizations.
Diagram supply chain models to help facilitate discussions with customers.	Diagram knowledge management models to help facilitate discussions with customers.
Select transportation routes to maximize economy by combining shipments or consolidating warehousing and distribution.	Select knowledge transfer approaches to maximize efficiency and effectiveness
Assess appropriate material handling equipment needs and staffing levels to load, unload, move, or store materials.	Assess appropriate KM staffing levels for knowledge creation, transfer, storage, synthesis and re-use.
Confer with supply chain planners to forecast demand or create supply plans that ensure availability of materials or products.	Confer with the business to forecast the demand for knowledge; create strategies and plans that ensure availability of knowledge as and when needed.
Define performance metrics for measurement, comparison, or evaluation of supply chain factors, such as product cost or quality.	Define performance metrics for measurement, comparison, or evaluation of KM factors, such as knowledge availability or quality.
Monitor supplier performance to assess ability to meet quality and delivery requirements.	Monitor knowledge supplier performance to assess ability to meet quality and delivery requirements.
Analyze information about supplier performance or procurement program success.	Analyze information about knowledge supplier performance or knowledge creation / acquisition program success.
Meet with suppliers to discuss performance metrics, to provide performance feedback, or to discuss production forecasts or changes.	Meet with knowledge suppliers to discuss performance metrics, to provide performance feedback, or to discuss new knowledge needs.
Design or implement plant warehousing strategies for production materials or finished products	Design or implement storage and synthesis strategies for documented knowledge
Analyze inventories to determine how to increase inventory turns, reduce waste, or optimize customer service.	Analyze knowledge stores to determine how to increase re-use, reduce waste, or optimize customer service.
Review or update supply chain practices in accordance with new or changing environmental policies, standards, regulations, or laws.	Review or update KM practices in accordance with new or changing standards and requirements.
Implement new or improved supply chain processes.	Implement new or improved KM processes.

But what's different?

The main difference between the role of the supply chain manager and the role of the Knowledge Manager is that the supply chain manager can assume that there is a customer for their services. They can assume that there are manufacturing workers who are ready and waiting for the supply of parts and materials.

The  Knowledge Manager cannot assume this.

The Knowledge Manager also has to work as a Demand Chain Manager; stimulating the demand for knowledge, and introducing the process and systems by which knowledge is sought, as well as those by which it is supplied.

Customer-centred KM

Knowledge transfer in an organisation is like a market-place, and every transfer of knowledge requires a supplier and a customer. To be effective, a market must be customer-centred.

Customer Satisfaction, by Roland Tanglao, on Flickr

I am focusing here on knowledge transfer, not on the creative act of innovation that comes from people combining their knowledge to make something new.  I am also focusing, not on the customers of your organisation, but on the customers for the internal knowledge transfer, namely the knowledge workers in your organisation.

In knowledge transfer, there is someone who knows something (the supplier) who interacts with someone who needs knowledge (the customer), so that the customer can learn something new.

In any transactional organisation, you need to focus on the customer. The needs of the customer are paramount, and we see this in commerce with the rise of the customer-centric organisations such as Amazon and Zappos.

Customer centricity is defined as putting the customer first, and designing a great customer experience, so they are delighted with the product, and with the process of finding and buying the product.  Markets which are not customer focused and customer centric lose their customers. The customers find the products disappointing, and the purchasing process too cumbersome, and the market dies.

Your internal knowledge market, and the transfer of knowledge to internal knowledge workers and knowledge users who are the customers for that knowledge, needs also to be customer-centric.

If KM is a market, how customer-centric is your KM program?

By customer-centric, I mean the following

1. Driven by the knowledge needs of the customer - by Knowledge Pull (see here)
2. Transferring knowledge the way the customer needs it to be transferred (see here)
3. Transferring knowledge in a medium that works for the customer
4. Putting "ease of finding" above "ease of sharing" (see here)
5. Maximising the knowledge signal, minimising the knowledge noise (see here)
6. Minimising the waste in the knowledge supply chain (see here)
7. Knowledge customers delighted by the knowledge products they find, and by the process of finding them.

Too many KM programs focus on the supplier and neglect the customer, and struggle to make a difference as a result.  Don't be one of them!  Be customer-centric, before your knowledge market starts to lose its customers.

Revolutionising the productivity of the Knowledge Worker 4 - eliminating the waste

Last week I blogged about the challenge of revolutionising the productivity of the knowledge worker, which Peter Drucker set for us. We looked at the division of knowledge labour, the automation/augmentation of knowledge work, and the knowledge supply chain. Now we look at the lean knowledge working environment.

The lean working environment for the manual
worker (image from greenhousecanada.com).
Does the working environment for the knowledge
worker look like this?

We have been looking at how the productivity of the manual workers has been revolutionised, and certainly lead production, lean working and the lean supply chain have all played their part. The Manufacturing Advisory Service (quoted here) claims a 25% increase in productivity through lean principles - a small increment compared to the difference made by division of labour, automation/augmentation and an effective supply chain, but still a significant factor in the continuous improvement of productivity. Lean is also a mindset - a relentless focus on adding value on behalf of the customer and removing waste effort and stock.

Many organisations are now beginning to realise the importance of the correct knowledge reaches each knowledge worker, at the time and place they need it, to the required standard and quality, in a deliberate and systematic manner.  However our track record of delivering that knowledge in a lean and efficient way is poor, and there is little or no sign of a relentless focus on removing waste and adding value.

Knowledge bases are full and clumsy to use, poorly structured and indexed, with duplicate, outdated or irrelevant material. Knowledge workers are often required to use multiple search engines or to visit multiple sites, social media streams are unfiltered and full of noise, knowledge is unsynthesised, often unfindable, and usually is poorly tagged and labelled.

All of this makes knowledge seeking a massive chore, which it is easier to skip than undertake.

A lean approach to Knowledge Management would involve eliminating the 7 wastes, such as

• Over-production of knowledge, which then becomes noise in the system
• Waiting for knowledge, and a slow turnover speed of knowledge
• Unnecessary hand-off of knowledge, with unnecessary steps in the chain between knowledge supplier and knowledge user  
• Non-value added processing—doing more work than is necessary. We often see this in lesson-learning systems, where the work of sifting, sorting and synthesising multiple lessons or multiple search-hits has to be done by the knowledge user. 
• Unnecessary "motion" - the need to visit multiple databases, multiple knowledge bases, a separate CoP system etc 
• Excess knowledge inventory— frequently resulting from overproduction.
• Defective knowledge.

Lean KM is the last of the four components to drive knowledge worker productivity. Together they can be revolutionary.

If we can have a lean and efficient knowledge supply chain, using automation and augmentation to deliver high quality knowledge to knowledge workers in a divided system of knowledge work, then we will approach Peter Drucker's initial vision of a 50-fold increase in productivity of the knowledge workers.

Revolutionising the productivity of the Knowledge Worker 3 - the Knowledge supply chain

Over the last two days I have blogged about the challenge of revolutionising the productivity of the knowledge worker, which Peter Drucker set for us. We have looked at the division of knowledge labour, and the automation/augmentation of knowledge work. Today we look at the knowledge supply chain. 

Parts, by Andy Malmin, on Flickr

The productivity of the manual worker was revolutionised through the transformation from craftsman production to factory production. Work was divided and automated, and individuals took their part within a work chain, or production line. Partly finished work came to them automatically, together with the parts and tools they needed, they did their own tasks, added their own value, and passed the updated work on to the next person.

That's how it works for manual workers, who make things.  Knowledge workers, on the other hand, make decisions rather than things. 

The raw material for knowledge workers is knowledge. Therefore in a world where knowledge work is divided (where we do not rely on experts who carry all the knowledge in their head) the knowledge worker needs partly finished knowledge to come to them automatically, together with the knowledge tools and additional knowledge they need, and when they have made their decisions and added their own value (often this is the innovation piece), then the updated work needs to be passed on to the next knowledge worker.

This is the vision of the organisation as a knowledge factory, or a knowledge assembly line, and for this to work, we need the knowledge supply chain.

I have already blogged several times about the knowledge supply chain (here, here and here). The knowledge supply chain is a new way of looking at an organisation of knowledge workers (predicted 20 years ago by Lord Browne of BP), and for ensuring that the correct knowledge reaches each knowledge worker, at the time and place they need it, to the required standard and quality, in a deliberate and systematic manner. Knowledge Management then becomes the supply chain for the knowledge worker.

Few organisations have got this right. Perhaps the only sector where KM approaches this model is the service-desk sector, where providing correct knowledge (answers to customer questions) to the front line staff is a vital KM service.

This vision of "Knowledge Management as a supply chain" requires a complete Knowledge Management Framework to be in place, with roles, processes, technologies and governance, with the sole purpose of supplying knowledge to the knowledge workers, to enable them to make the correct decisions.

In the next and final post of this series we look at the nature of this supply chain, and what it needs to become Lean

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.

"Smart push, warrior pull" to avoid information overload

I came across this phrase - "Smart push, warrior pull" recently, and looked it up online (for example here). It's a very useful military approach to maximising knowledge bandwidth. 

Information overload by SparkCBC on Flickr

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.

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" 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. 

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.

The lean km supply chain

If we see KM as a supply chain, supplying knowledge to the knowledge worker in order that they can make the right business decision, then we can apply concepts such as lean to optimise that supply chain.

One of the principles of a lean supply chain is that every step is driven by Pull. Nothing moves along a step in the supply chain unless it is pulled by the need from the next step. This ensures that supply is always "just in time" and that there is no wasteful build-up of unwanted inventory.

Let's see how Pull can drive the steps in the Knowledge supply chain.

Knowledge transfer through conversation and discussion

Pull-based discussion includes online discussion driven by questions, and face to face discussion in Peer Assists. The questions of the knowledge workers are answered from the experience of their peers/

Knowledge documentation

Rather than wait for project teams and work groups to volunteer knowledge, the knowledge owners conduct interviews and hold facilitated retrospects to draw out their tacit knowledge. They focus particularly on knowledge of high importance to the organisation.

Synthesis of knowledge into a knowledge store or knowledge base

The knowledge owners and subject matter experts seek for new knowledge to incorporate into the knowledge base and to synthesise with existing knowledge. They may look in the community discussions and the lessons learned system for new knowledge, or may convene community meetings to discover and incorporate existing good practice. 

Review of documented knowledge

The knowledge workers use search to access relevant documented knowledge, or use a system where knowledge is presented automatically at each stage in a work process.

The dangers of knowledge oversupply

In a market where supply grossly exceeds demand, prices fall, and value is destroyed. This is an unhealthy market, and these conditions can apply to knowledge as well as to commodities.

A commodity where supply far exceeds demand is a devalued commodity. Maybe supply will stimulate some demand, but most of the time you just create an oversaturated market, and you end up dumping surplus stock at rock bottom prices.

We saw this in the European Union, where farmers were paid to produce more wine and butter than the market needed. To keep prices stable the EU had to stockpile the produce, these stockpiles being referred to as "butter mountains" and "wine lakes". This was not a sustainable solution.

On the other hand, what happens when demand exceeds supply? Prices rise, and the value of the commodity increases. A commodity where demand exceeds supply is a valued commodity. Almost always demand will create supply, and you will end up with a vibrant marketplace.

These situations apply to knowledge as well as commercial commodities. 

An oversupply of knowledge (full databases not being used, loads of stuff filed and not read, loads of blogs with no readers, "knowledge lakes" and "knowledge mountains") devalues knowledge. Its seen as "a waste of time to capture all this stuff". "Why bother? Nobody reads it". Knowledge sharing, without knowledge reuse, quickly becomes a low-value activity.

An overdemand for knowledge (lots of questions on community forums, lots of people searching for answers, lots of expert opinions being sought) may cause frustration if the sought knowledge is NOT found, but certainly raises the value of the knowledge which is unearthed. Initially the bulk of knowledge which is found is tacit (people find knowledge through asking people), but this level of demand will cause increasingly more knowledge to be documented. Once the expert has been asked the same question frequently enough, he/she starts an FAQ, and the supply of explicit knowledge starts to grow as well.

If you are creating a knowledge marketplace in your organisation where knowledge can be exchanged and re-used, beware of the Knowledge Oversupply trap.

It may be tempting to focus on knowledge capture and on knowledge sharing, and on creating knowledge bases with lots of content.  However unless there is an equal focus on knowledge seeking and knowledge re-use, you may just be dumping an oversupply onto an uninterested market, resulting in devaluation of the commodity.

Make sure supply is balanced with demand, and a call for "knowledge sharing" balanced with a call for "knowledge seeking".