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

A great video metaphor for social knowledge "sharing"

The video below is a great metaphor for knowledge sharing. Or is it???

I use this video a lot in our Knoco Knowledge Management training courses. I have yet to find a better metaphor for connectivity within communities of practice and social networks.

BT used the video (about 5 years ago) to sell the concept of connectivity, and to show the possible power when large communities of people are connected and can interact.

However as you watch the video, make a note of the sort of interactions that take place, and then scroll down to my analysis below, to see if you noticed the same thing that I did.

Now scroll









Scroll a little more








Here you are

Analysis

Did you notice that almost every interaction, other than the last one, was driven by a Question?

• What's this groove called under my nose?
• Who wants to buy my fish?
• What do you think of our prototype?
• I love being a mum, but does anyone else sometimes feel overwhelmed?
• Did anyone here go to St Margarets school, Tobago, in 1952?
• I am looking to meet someone .....

Even that last one is a quesiton in disguise - "does anyone want to go out with me?"

Questions lead to rich interaction. Announcements don't.  

We can see this in LinkedIn, where the announcements-heavy groups have mostly become ghost towns, other than the few question-led examples. Announcement threads received on average 0.1 follow-up responses and comments. Threads that started with a real question received on average 13.5 comments.

Imagine the BT video, but where the interactions were all led by anouncements, and imagine how different the scenario would have felt. Imagine in each case it was the supplier of knowledge stood in the centre of the stadium, starting with the guy in the white coat announcing that "The groove under your nose is called a filtrum", and hoping that someone, somewhere might be interested. That would have been a far less compelling video.

The video is a great metaphor for knowledge seeking, rather than knowledge sharing. This is important - direct requests for help drive 75% to 90% of exchanged knowledge, and asking for help is a far tougher barrier than reponding and should therefore become the focus for our communication and culture change efforts. 

If you are taking the trouble to connect up the individuals in your organisation, by social media or in communities of practice, make sure that the interactions are question-driven wherever possible. 

Sports KM is not for the athletes

Sometimes we use Knowledge Management to improve the performance of someone who is not a knowledge worker, by improving the knowledge of their coach.

Image from wikimedia commons

Two weeks ago at KMUK 2016 we heard two presentations from the Sports industry on Knowledge Management - one from Peter Brown of the English Institute for Sport (EIS), and the other from Chris Payne of the Olympic Games association.  Both described KM in Sport, and in neither case did they focus on providing knowledge to the individual athlete.

(Note I am focusing here on individual athletes - runners, boxers, gymnasts, canoeists, triathletes etc - rather than on team sports. KM has a lot to offer sports teams, as described here, here and here).

Peter Brown described KM at EIS as being in service of the drive for team GB to win even more medals at the Rio Olympics than they did in London. His main focus is on developing and sharing knowledge between the technical specialists - the performance coaches, the nutritionists, the biomechanics experts, the designers of bicycles and bobsleighs, the physiotherapists and the strength and conditioning teams. He also looks at knowledge sharing between the athletes, on issues such as "how to prepare for a trip to Rio", but the primary focus is on the management of Sport Science knowledge.

Chris Payne focused on knowledge related to the logistics of the Olympic Games rather than knowledge available to the athletes, as is appropriate for an organisation that must remain objective. I have already shared a video of knowledge management for Olympic airport logistics, and Chris gave other examples, such as knowledge related to providing TV lighting.

In a competitive situation like the Olympics, the athletes themselves provide mostly physical factors such as strength, skill, endurance, coordination, use of equipment and so on. The bulk of the knowledge work is done by the coaches, the equipment providers and the support staff, which is where KM efforts are best focused.

We can translate this into the business world.

There are some cases where vital work requires less on knowledge and more on the skills of individual performers. Certainly this is true of manual workers, but can also be true of sales staff, for example. If you try to apply KM to a sales persons role, you often meet the challenge that "Salesmanship can't be taught - you either have it or you don't".

There is some truth in this statement. The sales person is often an individual performer, applying soft skills such as relationship-building, influencing, negotiation and persuasion. Knowledge can improve these skills to an extent, but often they are innate.

In a circumstance like this, Knowledge Management can be better focused on the people who "coach" the sales staff - their team leaders for example. We did a very interesting peiece of work for a global provider of consumer goods where we conducted knowledge interviews with the top sales team leaders across the world to develop good practices and best practices in managing a sales team.

This produced some fantastic knowledge, which the sales team leaders could use to bring the best out of their sales staff.

Sometimes KM should be focused not so much at the people "at the sharp end of the business", but more on those who support and coach them.

Understanding decisions, understanding knowledge

“Decision making is a knowledge-intensive endeavour ... To understand decisions and decision making, we need to understand knowledge and knowledge management” 

It's your decision, by ljphillips34 on Flickr

(Holsapple, C. W. Decisions and Knowledge, Handbook on Decision Support Systems 1, International Handbook on Information Systems F. Burstein and C. W. Holsapple, eds., pp. 21-53: Springer Berlin Heidelberg, 2008.)

Rationalising the KM programs

Applying the Lean approach to KM involves removing the waste from the knowledge flow. Sometimes this involves combining existing KM efforts.

3D Simplify Business by Chris Potter on Flickr

Large organisations sometimes develop many parallel KM programs which have grown "bottom up" in different parts of the business.  Last week in KMUK Lutz Lemmer described just this situation in Transport for London. 

By rationalising and combining these disparate approaches into a single KM framework, TFL have been able not only to provide a simpler, unified and complete framework, they have been able to cut costs at the same time. 

This is a lesson for anyone introducing, re-introducing or rationalising KM in a large organisation.

Find out what's being done already in terms of KM, find the lisste bottom-up activities, the samll communities, the local KM sites, and then

• Combine
• Reduce
• Simplify

Combine small efforts into larger systems to increase the power of the collective (as well as filling in the gaps),

Reduce waste, duplication and support resources, and the number of places people must go to to find knowledge,

Simplify the flow of knowledge.

How scaleable are communities of practice ?

Communities of practice are seen almost as a silver bullet in KM terms - a must-have item.  But does the concept of communities scale to all organisations?

Communities of practice as a concept is 25 years old, going back to the original work of Etienne Wenger and Jean lave, who define communities of practice as “groups of people who share a concern or a passion for something they do, and learn how to do it better as they interact regularly".

The uniting force for the community is that "something they do" - an area of practice - and the focus of the community is "learning through regular interaction".  By learning in a community, community members can both use each other as a knowledge resource, and also co-create knowledge within the community. Communities of practice are as much knowledge-creating mechanisms as they are knowledge-sharing mechanisms.

There are two end-member approaches to Communities of Practice - large online communities, and small face-to-face communities.

The large online communities are immensely successful KM solutions for multinational organisations. The big consulting houses make extensive use of online CoPs, as do the big oil companiesand engineering houses. I have CoP success stories from  Siemens, Merck, Halliburton, Fluor, Caterpillar, Orange, Conoco and Shell.

These CoPs are largely focused on problem solving, and responding to reauests for help ad advice from members. They work through online discussion, often with the help of a facilitator or moderator.  The bigger the better, as far as these communities of practice are concerned, as shown in the graph below. Some of the most effective communities have thousands of members, and there is certainly an issue of critical mass. Communities need to have a "buzz" - they need regular, and to have regularity, they need mass. Online communities of practice which are too small are unable to sustain enough activity, and die. (see this blog post about how much buzz an online community needs)

At the other end of the scale are small communities of practice that meet face to face. The type example here is the tech clubs from Daimler Chrysler; small groups of tens of people that would meet once every two weeks to discuss technical issues and solve technical problems.  These online communities are often very valuable knowledge sharing mechanisms, but seldom grow beyond about 50 people. This is because discussion becomes difficult above 50, and because larger groups tend to meet less regularly and, again, that feeling of buzz dies away.


It is between these two end members that Communities of Practice get most awkward.


Firstly you cannot scale down an online community of practice far before you run into the issue of critical mass. This is what is behind the decreasing satisfaction in the column graph above. Most of the surveyed communities were online communities, or had some online component, and the smaller they are, the less effective they are deemed to be.

Secondly you cannot scale up face-to-face communities. Above 50 people, they cannot have a good discussion.  They start to fragment. The effectiveness of face to face communities would show the opposite trend to the column graph above.

There is an awkward zone for community size, where they are too large to meet face to face, and too small to be viable online. This zone is probably about 50 -  250 people, and this is a zone where considerable effort will be needed from the community facilitator.  You will either need smaller face to face groups within a larger online community, or you will need to amalgamate several of your awkward communities into one larger community with the requisite level of buzz.

Communities of practice is a great concept, but neither the face to face nor the virtual community solutions are fully scaleable, and they leave an awkward zone where neither solution works properly. Therefore think carefully when scaling a community solution. 

Middle managers -the KM blockers

Middle management can form an almost impenetrable layer to knowledge management in many organisations.

The two main stakeholder groupings for KM are the senior managers and the knowledge workers. The value proposition for the senior managers is that KM will deliver greater efficiency, greater effectiveness, faster growth, bigger market share, faster time to market, and happier customers. The value proposition for the individual knowledge workers is that KM will provide then with easy access to reliable knowledge that will save them time, will reduce their risk of failure, and will make their results better.

However between these two groups lies a layer of middle management; the sales directors, the plant managers, the project managers etc.

These are the people who have tough choices to make. They have demanding customers, tight budgets, and tighter deadlines. Every penny they spend on KM is a penny less to spend on operational issues. KM, for them, is two steps away from operations (the first step is that operations reauires knowledge, the second is that knowledge requires management).

The result is that these are the poeple for whom KM is the toughest sell - the people who won't be swayed by high level arguments or appeals to emotion.

Here is what John Keeble, CKO at Enterprise Oil, had to say

"It is that bunch between (top management and the "coalface" that I think are almost the most important - the team leaders, the middle management. They are the people who are constantly trying to juggle this dilemma of too much to do and not enough people. So if you cant convince them of the value of knowledge management, its likely not to get the resources applied to it. So then you get the situation where in theory you have support from the top, and demand from the base, but that demand from the base is being frustrated by the fact that their managers aren't freeing them up to do it. And that can be a very negative cycle if you get trapped in it. Overall I think you have got to get support from all levels, but it is very easy to overlook that middle management level, and they are perhaps the most important"

We heard the same message from Lutz Lemmer at Transport for London last week, and have heard it from many many clients over the years.

Make sure your stakeholder management plan clearly addresses the middle managers as a core group, and that you have a well worked business case that addresses their concerns. Without this, they can derail the whole program.

Knowledge Management and Knowledge replication

Knowledge Management is a key tool for organisations that want to replicate their services in new markets. The Olympic Games can give them some pointers in how to do this. 

Knowledge Management in service of growth is a special case model for KM. In a growing organisation - one that wants to move into new markets, new cities and new countries - the core issue is being able to replicate past success somewhere new, rapidly and effectively. Replication of knowledge is part of the solution to this issue.

When I was working in BP in the 90s, we looked at this issue in the context of entering new countries.  Whenever the company wanted to open a country office somewhere new, the same generic set of actions was needed, albeit in a different cultural and legislative context. We introduced the idea of the "new country briefcase" - not a literal briefcase, but a collection of knowledge, good practice and advice that would give the new country manager and their team a head start.

The US Army have created a similar collection of knowledge for their company commanders, to give them guidance on their "first 100 days" in post in Afghanistan. Based on the universal lessons in combat survival in a counterinsurgency, and research collected by the Centre for Lessons Learned,  this handbook emphasises what experienced soldiers and leaders said are important in terms of training, skills, and knowledge.  Here the knowledge replication is from one group of soldiers to the next.

At KMUK last week we hard from Chris Payne of the Olympic games about a similar need for knowledge replication. Each Olympic games looks to reproduce the success of the games in a new cultural and legislative context, and each new host country seeks for the lessons that previous host countries have said are important in terms of training, skills, and knowledge

According to Chris, the new host countries have three sequential knowledge acquisition priorities:

• Firstly they want to get data. Data on budgets, sizes of teams, plans for organisation, construction, broadcast and so on. 
• Next they want to get knowledge about organisation structure. Chris described how organisation structure is not static during a Games, and the change from a function-based structure to a venue-based structure is one of the risk points that needs to be handled well.
• Finally they want knowledge about the processes to use, and the best practices in these processes. 

These knowledge needs are met through a comprehensive program of conversation with previous host nations, secondment and shadowing for fist hand experience, and a set of guidance manuals.

If your organisation ever needs to replicate activity and success, then knowledge replication needs to be part of your Knowledge Management strategy. 

5 things I learned at KMUK

Wednesday and Thursday last week saw Knoco at the KMUK 2016 conference in London. Here are some reflections from the event.

At KMUK 2016, from left, Laura Brooke, Lutz Lemmer
Ian Rodwell, Steve Perry, Rupert Lescott, me.
Photo by Laura Brooke

These conferences - always very interesting, always very well organised - are an opportunity to take the pulse of KM in the UK. Thank you very much to Ark group, Laura Brooke, Ian Rodwell, Paul Corney and the conference speakers and delegates for a great event.

Here are some of my thoughts on the current state of the art of KM in the UK, based on the presentations and discussions at the conference.

There seemed to be four main themes within the bigger topic of KM: Communities of Practice, Lesson-learning, Knowledge Transfer, and Technology. Communities were prominent in the presentations from Steve Perry (E&Y), Monica Danese-Perrin (Lloyds), and Christine Astaniou (FCA). Lessons were prominent in the presentations from Lutz Lemmer (TFL), and Ian Tinsley and Rupert Lescott (British Army/Knoco). Chris Payne (Olympic Games) and John Hovell (BAE systems) talked in the context of Knowledge transfer from organisation to organisation, and from person to person.  The technology presentations included James Loft talking about Artifical Intelligence, Ben Gardener on Semantic methors, and Nathaniel Suda on SharePoint.


You can see, within these themes, varying approaches to the issues of Content and Conversation - the two subjects of KM. The demonstrated processes - John Hovell's knowledge transfer planning, and the perennial favourite, the Knowledge Cafe - were conversational processes. Many presenters discussed KM frameworks that covered both content and conversation (Chris Payne, Lutz Lemmer, Peter Brown from the English Institute of Sport). Others were firmly down the content end. David Smith from the civil service described the KIM professionals as being certified in content management (library) skills for example, while the technology presentations covered content only (unless you count voice interactions with AI as conversation, which in a way it is, but it certainly isn't dialogue).  One thing that surprised me is that the demonstrated conversational processes were seen by many as something new, which makes me concerned that we may have lost sight of some of the conversational basis of KM. Sharing knowledge through structured conversation is a bedrock of KM, not something new.


The term "communities of practice" was very widely used at the conference, but the nature and scale and method and purpose of the networking within these "communities" was radically different. At one end of the scale you have the E&Y tax community of 13,000 members, interacting remotely through a sophisticated online site, and at the other end of the scale you have the groups of 10 experts in the FCA coming together for face to face meetings on specific topics. I wonder whether we need to be more precise in our descriptions of different types of networks (see here for example) as to lump them all together as "CoPs" is to mask the differences.


The best examples of Knowledge Management presented at the event were related to the areas of clearest  knowledge need, such as the need to "learn before doing" when hosting an Olympic games (which Chris Payne described as the largest and most complex endeavour other than military conflict), or the need to upgrade the transport infrastructure of one of the worlds busiest cities (Lutz Lemmer), or the need to save lives in Afghanistan (Ian Tinsley and Rupert Lescott). In other areas, people are still trying to do KM by stealth, or KM with no budget, or KM by technology, or KM by little incremental changes; all of which are very risky approaches.


The big issues for discussion in the knowledge cafe were the same issues we have been discussing for years - the issues of KM Value, and of Culture Change, for example, have been constant recurring discussions for years. In these two cases in particular I believe we have enough knowledge and experience of KM to give definitive answers, which makes me wonder how we can get those definitive answers out there so that people no longer have to keep struggling with these issues every time there is a conference.

Genghis Khan - ace Knowledge Manager

Here is an interesting analysis of Genghis Khan, suggesting that an open approach to knowledge acquisition was the Mongol leader's key to success.

Genghis Khan, image from wikipedis(not a photograph)

The analysis is published in the Farnham Street blog, and is reproduced from the book "Ego is the enemy" by Ryan Holiday. Holiday's thesis is that great leaders do not achieve results through force and through the power of Ego (D Trump please take note), but through softer approaches including confidence, humility, hard work, and learning. 

Genghis Khan is one of his more unexpected examples. 

Genghis Khan, born in or around 1162, was the founder and Great Khan (Emperor) of the Mongol Empire, which became the largest contiguous empire in history. He has a reputation for brutality and genocide, but far less of a reputation for Knowledge Management. Ryan Holiday would like to redress this.

As he says:

Not only was Genghis Khan one of the greatest military minds who ever lived, he was a perpetual student, whose stunning victories were often the result of his ability to absorb the best technologies, practices, and innovations of each new culture his empire touched....  with each battle and enemy, [the mongol] culture learned and absorbed something new. 

Holiday gives the following examples of Genghis Khan's knowledge acquisition and integration program:

• The concept of splitting his soldiers into groups of ten, taken from neighboring Turkic tribes
• How to attack fortified cities through the use of siege engines, learned from Chinese engineers
• How to hold territories through a hearts-and-minds campaign, learned from campaigns against the Jurched
• How to build cannon, learned from an innovative combination of Chinese gunpowder, Muslim flamethrowers, and European metalwork

He describes how

"in every country or city he held, Khan would call for the smartest astrologers, scribes, doctors, thinkers, and advisers—anyone who could aid his troops and their efforts. His troops travelled with interrogators and translators for precisely this purpose"

As the Mongol empire grew, so Khan added to his knowledge, seeking out new ideas that he could put into practice. This openness to learning was one of the factors that enabled Khan's success.

I wonder, how open are today's business Khan's - the CEOs who take over other organisations in order to build their empires? Are they open to learning? Do they have teams of "interrogators and translators" (aka Knowledge Managers) to identify and capture the new knowledge they use in their own business purposes? Do they see each acquisition as a learning opportunity?

Or are they driven by their egos to conduct downsizing exercises (the business equivalent of massacre and genocide) with no thought to the knowledge that will be lost?

Let's not just learn from Genghis Khan; let's learn LIKE Genghis Khan.

How sports teams "learn before doing"

Business can learn a lot from Sport.  In Knowledge Management terms, one of the things it can learn about is the practice of "Learning before Doing".

No sports team would take the field without spending a massive amount of time reviewing their own performance, reviewing the playing styles of the opposing team, and reviewing the preferences and biases of the referee.

Generally, in weekly sport with weekend matches, Monday is Analysis Day. The day is spent in performance analysis, in order to plan the coming week's training.

Much of this review is done through video, and through extensive video analysis of tactics and strategies; see here for a discussion of how a sports team can use video throughout their training week. There is an entire industry building up around video analysis software, and video analysis services, all with the aim of understanding your own team and your opponents. This can be an exposing affair - the statistics on individual players can show up the weak links as well as the star performers (see example) - but in today's intensive industry such honest and exposing learning makes the difference between success and failure.

So what can business learn from this?

I think there are a couple of points.

Firstly the more you "learn before doing", the better your results will be. You need to learn about yourselves to improve your methods and tactics, you need to learn about your competitors and their products and approaches, and you need to learn about your customers and clients.

Get data - get as much data as you can. understand it, analyse it, look for the root causes, and look for the learning. Reflect on your performance as an organisation after every intervention, every activity, every project. Ask "How can we do it better next time". Draw out the lessons. And next time, deliberately seek out the knowledge and the lessons as input into your plans. 

Secondly you need ruthless self-analysis. As a team, you need to know how you perform, and where your weak spots are, so you can work on them. Business is a ruthless game, but the purpose of a team is to draw out the best from all its members, and you need to know how to do this. So don't be worried if this self-analysis identifies weaknesses, so long as you have a plan to work on those weaknesses.

Sometimes a knowledge manager needs to take a risk

Sometimes playing it safe in Knowledge Management is a dangerous approach. Sometimes we need to be bold.

Jon Harman is the head of Knowledge Management at Syngenta Crop Protection. I know him quite well, and admire the work has has been doing. In 2010 Jon had been in post for many years, making steady though slow progress. Then, in 2011, he had a breakthrough - he had the most productive year in KM that he has ever had.

The reason? He had lost his job.

Or perhaps to be more exact, he was under notice that his KM post was closing.

For Jon, this was liberating. Released from the fear that he might lose his job (because he knew the axe had already fell),  Jon decided to live dangerously. Instead of waiting for permission, he acted. Instead of working through is boss, he went direct to the CEO. Things started to happen, the CEO liked what he saw, and the KM train started to accelerate. Not only that, but Jon was offered another KM post within Syngenta.

So what's the lesson?

If you are going to make Knowledge Management work, you have to be bold. You have to live dangerously, because (as I said in the post "KM, simple but not easy"), "it needs courage and it needs dedication and it needs perseverence and a thick skin, and it needs you to work at some very difficult conversations".

Jon learned the lesson through the risk of losing his job. If you learn the lesson, rather than making your job more risky, it may actually make your job safer.

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.

Knowledge - easy as ABC

The 4 steps of lesson identification

The identification of new knowledge, or new lessons, involves a few steps. One critical step is making an analysis of a number of observations.

The steps involved in identifying a lesson from experience, or new knowledge gained, are as follows:

1. Making an observation. Something unexpected or unwanted has happened, and the first step is to make this observation.
2. Analysis. You analyse the observation, look for the root causes behind it.
3. Generic learning. You decide the learning point - what the recommendation would be for the future, to repeat the unexpected success, or avoid the unwanted problem.
4. Decide the action. Here you decide what to change in the organisation, to ensure the generic learning is embedded in process.

Think of the 4 or 5 questions of the After Action Review. The first two ("what was supposed to happen? What actually happened?") cover the observation. The third ("why was there a difference?") is the analysis. The fourth (""what have we learned?") is the generic learning. The optional fifth ("What action do we take") is the action.

Who carries out these steps, and using what process, varies from organisation to organisation.

Analysis as a separate function

• In the NATO system, observations come from the troops, and all the other steps are carried out by JALLC (the joint analysis and lessons learned centre). NATO therefore separate observation from analysis and identification of learning points.
• This same approach is taken by many  Aid and Development organisations, lending organisations such as the World Bank, and government departments such as DFID (department for international development). Here there are whole evaluation departments set up to analyse observations and draw out lessons. 
• A similar approach is seen in major accident investigations, where an evaluation and analysis team is set up.

Analysis by management 

• In a major engineering company we work with, the observations, analysis and generic learnings are identified by the project teams, using the Retrospect process. The actions are decided by a central group of senior functional managers (in another company, a central lessons coordination team decides the actions). These companies combine observation, analysis and lessons identification into one process, but separate the step of identifying the actions.

Analysis combined with Observation

• In standard processes such as After Action Review and the Toyota A3 process, the project teams conduct all the steps, including suggesting the actions.

When you design your own lesson learning system you will need to decide, for your organisation, who does what in this process of indentifying the learning from activity, and whether you separate observation from analysis, or lessons from actions.  The key question to consider is whether the project team are both objective enough, and saw enough of the aftermath of the project or activity, to conduct the analysis themselves. 

Nuclear Knowledge Management

The IAEA has made public an excellent reference on Nuclear Knowledge Management (NKM), in the form of the NKM Wiki

Image from wikipedia

This wiki provides definitions and commentary on Knowledge Management as it is applied within the Nuclear sector.

Nuclear KM is different from that in other industries in three ways:

• There is a much stronger emphasis on knowledge of equipment and plant, given the complexity of many nuclear
• There is a very strong emphasis on safety knowledge, and 
• There is a huge emphasis on recording knowledge so that it can be passed down many generations of workers. The life of a nuclear power plant, especially if you measure this life from construction to decommissioning, exceeds the working life any of the employees, and knowledge must be passed from one generation to another. 

Some highlights of the wiki include:

• A role description for a Nuclear CKO
• An approach to competency loss risk assessment (a component of a Knowledge Retention strategy)
• An academic paper on whether and how NKM supports performance (answer, it does - strongly)
• An article on KM implementation
• Guidelines on managing safety knowledge
• An introduction to Nuclear KM
• An example NKM policy
• Transfer of knowledge between generations

Knowledge Management at ENI - case study

ENI, the Italian oil company has just published some details of their KM system. Here is a summary. 

ENI NC41 DP4 Bouri platform, from wikimedia commons

 ENI is a large Italian oil company, headquartered in Rome, with 80,000 staff over 79 countries. The upstream side of ENI employs 29,000 staff and covers oil exploration and production activities. 

ENI upstream have just published details of their KM system here and here. 

ENI Upstream define knowledge management as "the processes and systems that support the creation, development, sharing and application of knowledge within the company", and believe that KM will make it possible to reach the right people at the right time to solve problems quickly, with "contributions from the finest experts inside the company".  Their focus is on efficiency, cost reduction, problem solving and innovation.

There are two main streams to KM at ENI - the well-known approaches of Connect and Collect.

They approach the connection of people through the establishment of Communities of Practice. The describe the following statistics for CoPs for 2015:

• 50 business-based CoPs (27 hosted by Upstream)
• 7274 members of the business CoPs (an average of 145 members per community)
• 8 cross-business CoPs
• 708 members of the business CoPs (an average of 89 members per community)

 For an international oil company of this scale, these Communities seem quite small. 

The approach the collection of documented knowledge through a Knowledge Management system described as "a technological platform that captures, disseminates and enhances the on-the-job knowledge gained by its people".  This is based on an Enterprise social network approach, thus merging connecting and connecting. Documented knowledge is stored as "Knowledge nuggets" and "innovation ideas". As ENI says"

"Our Knowledge Management System allows us to align operational subsidiaries abroad with internal standards of excellence and at the same time build a store of technical experience in the field at headquarters"

One interesting adaptation is  the ability for staff to tap into the social network through their smartphones.

ENI describe seeing a rapidly growing use of their KM system, and claim as follows:

"The benefits generated by Eni’s KMS have been immediate and strategic. We cut costs thanks to solutions we have developed ourselves, while we contribute to strengthen the company’s identity by involving everyone in the construction of our successes ... we improve the way we work, enabling us to speed up the dissemination of innovative solutions and avoid the repetition of mistakes".

The knowledge manager's request to senior management

Following on my post last week about managers being knowledge workers; here is a reprise of a post from 5 years ago which rings just as true today.

It takes the form of a letter from the Knowledge Management team to the senior managers of the organisation.

Dear Senior Managers

Over the past year, our pilot projects in Knowledge Management have shown that there is huge value to be delivered to the organisation through introducing a systematic managed approach to knowledge. The ROI of these pilots has been in the order of 10-fold, and we believe this can be scaled up to corporate level.

We, the KM team, commit to delivering this value to you, but we need something in return.

Here are our requests for you

1.  We need you to steer our program. Help us to understand what knowledge is strategic to the organisation, so that KM activities can fully support your own strategic agenda. Lets work together to make KM a core supporter of the business strategy.

2. We need your endorsement. We need you to be talking about the importance of knowledge. We need you to be asking the questions "Who have you learned from?" and "Who will you share this with?" Eventually we will be asking you to set clear expectations for KM in the organisation in teh form of a Knowledge Management Policy.

3. We need your example. As someone once said, "I cannot hear what you say, for the thunder of what you do", so you need to be acting, as well as talking. Get involved in KM. Hold your own learning reviews. Capture and share and build knowledge at senior management level.

4. We need you to reward and recognise wisely. KM requires a change in culture, and people will be very alert to how you recognise behaviours. If you reward and recognise the wrong things, such as internal competition, or the lone hero who "doesn't need to learn", or the knowledge hoarders who keep it all "in their heads", then our good work of culture change will be in vain. Recognise instead those who learn before doing, those who share hard-won lessons, and those who show bravery in admitting to mistakes from which others can learn.

5. We need you to be consistent in how you follow up expectations. The company will watch how you deal with the project that doesn't hold a learning review, or the expert who neglects their community. If you let them get away with bad KM behaviours, you have sent a strong message to the organisation; that you can refuse to be involved in KM, and nobody will make a fuss.

6. Finally, we need you to challenge us. We know the value of KM, and you need to challenge us to use it to make a real step-change in business deliverables.

Together, we can make a real difference through knowledge management.

Sincerely,

the KM team

KM and Value infographic

The infographic below has been produced by Ewa Stelmaszek of Knoco Poland, to illustrate the link between KM and value. 

We will expand on this topic tomorrow in the Knoco Newsletter, with an analysis of where value comes from, how it is measured, the metrics you can use, the scale of value generated, and other topics. If you would like to receive a copy of this newsletter, you can sign up here.

5 steps to Knowledge Management culture change

There are 5 generic steps to go through when introducing a Knowledge management culture. These are as follows.

1. Define the culture you want to develop. Don't define it in woolly terms - "we want a knowledge sharing culture" - but define it in terms of the attitudes and behaviours you wish to become the default within the organisation (you can define culture as a set of default attitudes and behaviours). These might be things like

• People are open about their successes and failures 
• Honesty is acknowledged as requiring courage and is rewarded
• People feel valued for how well they learn, rather than what they already know
• People’s default behaviour is to share knowledge with others 
• Collaboration gets you noticed and is rewarded, etc. 

2. Measure the culture you currently have. Again, measure specific beliefs, attitudes and behaviours. Measure leaders and knowledge workers alike. Measure what people think about their own behaviour, and what they think about others'. We have a KM culture survey which we can run for you, if you like, which measures 10 dimensions of a KM culture.
    
3. Identify the gaps between the existing and desired attitudes and behaviours.
    
4. Identify what is causing those gaps. Look at factors such as 

• The reward and recognition scheme
• How bonuses are awarded
• The messages leaders give
• The stories people tell
• The reasons why people get promoted
• The organisational policies (for example information security)
• The layout of the building
• etc

5. Address these factors in order of priority.

• Revise the reward and recognition scheme so knowledge seeking and sharing are rewarded rather than individual heroics
• Revise the bonus scheme in a similar way 
• Give the leaders new messages
• Tell new stories
• Promote different people
• Change or clarify the organisational policies. 
• Write a KM policy.
• Change the office layout if needed.

We can help you with this - contact us to find out more about our KM culture services.

13 things we can learn from communities of practice at Ericsson

Communities of practice were introduced in Ericsson in the early 2000s. Here are some lessons from their experience. 

Image from wikimedia commons

I am drawing on two sources here - this article by Christian van ‘t Hof, and a paper published by Anders Hemre entitled "Building and Sustaining Communities of Practice at Ericsson Research Canada", published in Madhan Rao's book "KM tools and techniques".

These two sources provide between them 13 lessons from the Ericsson experience.

1. Communities are built with “magnets” and “glue” - domain interest and content value attract people to the community, and then the relationships bond the members.
2. A low-keyed implementation approach leaves more room for adaptation and lowers the risk for “campaign fatigue". 
3. The role of the community leader is critical in facilitating, supporting, nurturing and guiding the process of networking. 
4. There are three types of users for a new system - early adopters, early rejecters and neutrals. Energy is better spent using the early adopters as pilot users helping to draw in the neutrals rather than trying to convince the non-believers. 
5. Recruiting the experts into communities requires special consideration. Top experts don’t always have the best social skills, they already know the topic ,and feel they don't need the community. If experts are reluctant to join, then the community should tap into the “second tier” of knowledgeinstead. 
6. Keep a balance between bottom-up and top-down communities, to both encourage new ideas and maintain focus on purpose and objectives. 
7. It is easy to participate in online communities but difficult to develop relationships and feeling of community. Make sure there are face to face events as well.
8. It is easier to get answers than questions. Once you get a question, 91% of the time it receives an answer. 
9. It is easier for people to respond to a question if notified by email 
10. It is beneficial to have a moderator who can follow up on unanswered questions, initiate community dialog, and keep the “pot boiling”. 
11. Discussions don’t tend to form long threads; they are rarely longer than 10 messages. The system was initally meant to stir lively discussions between experts, but instead added value through answering questions and solving problems.
12. Content value is critical and it is necessary to regularly purge  incorrect or obsolete information. 
13. Good community recruiting policies include recruiting people who are active in other discussion forums or  inviting someone to respond to a particular question.