Why leaders have to let go of the need "always to have the answers"

If leaders are to empower their knowledge workers, they have to let go of "always having the answer"

Image from wikimedia commons

The book "It's Your Ship: Management Techniques from the Best Damn Ship in the Navy" tells how Captain Michael Abrashoff took command of the USS Benfold and turned it from being the worst performing ship in the fleet, to the best.

One key factor he mentions is familiar to all of those wishing to instil a Knowledge Management culture, and that is the willingness of leaders to let go of the "need to know all the answers", and to start to make use of the knowledge of the organisation.

 As Abrashoff says

"Officers are told to delegate authority and empower subordinates, but in reality they are expected never to utter the words “I don’t know.” So they are on constant alert, riding herd on every detail. In short, the system rewards micromanagement by superiors— at the cost of disempowering those below..... 

"I began with the idea that there is always a better way to do things, and that, contrary to tradition, the crew’s insights might be more profound than even the captain’s. Accordingly, we spent several months analyzing every process on the ship. I asked everyone, “Is there a better way to do what you do?” Time after time, the answer was yes, and many of the answers were revelations to me. 

"My second assumption was that the secret to lasting change is to implement processes that people will enjoy carrying out. To that end, I focused my leadership efforts on encouraging people not only to find better ways to do their jobs, but also to have fun as they did them". 

What Abrashoff discovered was the difference between managing knowledge workers, and managing manual labourers. Knowledge workers generally know more about their work than their boss does.  They use knowledge to make decisions and take actions on a daily basis, and they know what works and what doesn't. The manager's role is not to be the arbiter of those decisions, even less to be the decision maker, but to empower and enable the knowledge workers with the tools they need to get the right knowledge to make the right decision. Often the right response from the leader is "I don't know the answer - why don't you go find out what others do, and learn from them".

This empowerment, and this leadership move from being a Knower to being a Learner, are components of the culture shift that KM brings about, and which in turn liberates the knowledge, and also the performance, of the whole organisation. This cultural shift may be harder in some national cultures than others. However the message is clear - 

If you are managing knowledge workers, you need to let go of "always having the answers".

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.

Revolutionising the productivity of the knowledge worker - part 2, automation

Yesterday I blogged about the challenge to revolutionise the productivity of the knowledge worker, and how the first step was the division of knowledge. The second step is the automation of knowledge work. 

Image from wikipedia commons

Automation was one of the factors that helped revolutionise the productivity of the manual worker.  

The blacksmiths hammer was replaced by the hydraulic press, the auger by the electric drill, the wheelbarrow by the forklift truck. Machine power augmented muscle power. Automation, combined with the division of labour, gave us the modern assembly line.

if we apply the same thinking to knowledge work, then automation is one area where KM has done well.

Perhaps we should say augmentation rather than automation. As Tom Davenport points out, smart technology is not yet replacing humans, but augmenting their power. Much as a hydraulic press augments the metal worker rather than replaces him, smart KM technology augments the knowledge worker, rather than replacing her. 

• Knowledge bases augment the knowledge worker's memory. Rather than keeping our own notebooks, or trying to remember details of a process or procedure, we can consign it to a knowledge base. And if this is a shared knowledge base, then we have access to the knowledge of many people, rather than just our own. 
• Search engines augment our power of recall. Without significant mental effort, we can retrieve a fact or an image or a process from deep within a knowledge base, thanks to the power of search, be it keyword search, semantic search or image search.
• Smart technology can also take the role of a mentor, and suggest knowledge to use when we need it (based on where we are in a process or a task), even before we ask for it.
• Technology can also augment our personal networks, allowing us to ask not just our immediate colleagues for help and advice, but hundreds or thousands of co-practitioners we may never have met.
• Technology can augment our ability to communicate, allowing us to hold virtual meetings across continents and timezones.
• Technology augments our ability to see patterns in vast quantities of data and information, to apply our knowledge to make sense of these patterns, and use them to support decision making. 

Automation/augmentation is an area where already great strides have been made in helping increase the knowledge workers' productivity. However this is not the only area that needs to be addressed, and tomorrow we will look at the third component, the Knowledge Supply Chain. 

Revolutionising the productivity of the knowledge worker - part 1, the division of knowledge labour

This week I would like to upcycle a series of blog posts from 5 years ago about "revolutionising the productivity of the knowledge worker" - a challenge set for us by Peter Drucker

Image from wikimedia commons

Peter Drucker famously said 

‘‘The most important, and indeed the truly unique, contribution of management in the 20th century was the fifty-fold increase in the productivity of the manual worker in manufacturing. The most important contribution management needs to make in the 21st century is similarly to increase the productivity of knowledge work and knowledge workers". 

That is the big challenge to the Knowledge Managers of this world - to increase the productivity of knowledge workers by a factor of 50. The good news is that we are half way there. The bad news is that we have a long way still to go.

I already provided a summary of this task in a previous blog post, but would like to amplify, here and over the next few days, on the four factors which we, as Knowledge Managers, can influence. And the first of these is the division of knowledge labour.

The manual worker equivalent

The division of labour was a huge step in improving manual worker productivity. This involved dividing manual work into tasks, as in an assembly line process, and the recognition that the manual worker did not need to make everything. They would have their task, work on their component, and others would make the rest.

My grandfather was a village blacksmith. He was a craftsman - he could make a set of wrought-iron gates, for example, which were a work of art. He would start with iron bars, and do all the work himself. The result was excellent quality, but it took a very very long time.

Nowadays iron gates are made in a factory. The quality may be less (though they are definitely fit for purpose, and in some cases factory quality is better than craftsman quality), but the cost is far less, and the productiviy is massively higher.

As Wikipedia says, referring to Adam Smith's famous example of the pin factory - 

"Previously, in a society where production was dominated by handcrafted goods, one man would perform all the activities required during the production process, while Smith described how the work was divided into a set of simple tasks, which would be performed by specialized workers. The result of labor division in Smith’s example resulted in productivity increasing by 24,000 percent (sic), i.e. that the same number of workers made 240 times as many pins as they had been producing before the introduction of labor division"

Division of knowledge labour

The knowledge equivalent of a craftsman is an expert. Much as a craftsman such as my grandfather would make the whole object himself, from raw materials, so an expert would hold all the knowledge in their head, from first principles to the final decision.  Many decades ago, if you needed knowledge to be applied, you called the expert. You got good results, the quality of decisions was good, but it may take a long time to find and deploy the expert.

Just as the transition from a craftsman economy to a manufacturing economy involves the division of labour, so different people make different parts, so the transition from an expert economy to a knowledge economy involves the division of knowledge, so that different people know different parts. 

The division of knowledge is the recognition that knowledge can be more effectively deployed and managed within a community or network, rather than held by an expert, and the division of knowledge work is the effective use of networked knowledge workers. Leaving knowledge in expert heads is seen as inefficient and ineffective.

In many organisations, this shift has happened. Knowledge work has become divided - people know as much as they need to know and no more, confident that they can find any extra knowledge when needed.  Juniors perform tasks, with the help of KM, which in the past were the domain of experts.  New hires answer customer queries, junior GPs address topics that used to be the purview of specialists, young lawyers do the work that partners used to do.  From being the "font of all knowledge," the experts become the "stewards of knowledge" on behalf of the community.

Division of intellectual labour is "work in progress" for KM - a movement that has started, but maybe can develop even further. By dividing the knowledge work, we avoid the need to rely on experts for every decisions, and massively improve the productivity of the knowledge workers, provided they have access to the knowledge needed for their component of knowledge work. How that knowledge is provided will be covered in tomorrow's post.

Division of knowledge labour massively increases productivity, but cannot be accomplished without Knowledge Management.

Who are the knowledge workers?

The knowledge workers represent one of your two main stakeholder groupings for Knowledge Management implementation. But who exactly are they?

Image from Creazilla
Public domain licence

Firstly we can eliminate from the group "knowledge worker" anyone who is purely a manual worker - someone who follows orders or preassigned inflexible procedures. Labourers on a construction site, fruit pickers in a field.  These are not the customers for KM.

However they could become knowledge workers.

Toyota led the way in showing that assembly line workers could become knowledge workers, if you involve them in analysing the work they do. Kaizen-style meetings provide a format where the manual workers can become knowledge workers, accountable not just for doing the work, but improving the way the work is done.

If we eliminate any manual workers that remain, we are left with a group we can call  decision makers.  These are people who use knowledge and judgement in order to make decisions and solve problems in the course of their work.  The better the knowledge they have access to, the better the decisions they will make, and the better their performance will be.

This definition of knowledge worker includes people such as;

• Engineers making design decisions
• Programmers writing code
• Doctors prescribing for a patient
• Sales staff deciding how to sell to a customer
• Lawyers trying to decide the best legal solution
• R&D scientists trying to develop new technology
• Government staff determining policies
• Aid and development staff trying to design and apply interventions
• Medical staff making decisions about patients
• Soldiers making decisions on the battlefield
• Maintenance engineers trying to decide how to maximise the utility of equipment

and so on.

Also, don't forget the managers

Then there is a group which is often neglected in KM initiatives - the middle and upper managers. 

Management also make decisions, and often very big decisions, with costly implications. They also need access to the best knowledge they can find, and if the KM program cannot help them they will need to hire in expensive external consultants. 

So the following are also knowledge workers;

• Project managers making decisions on major (and minor) projects
• Divisional managers making decisions about market penetration
• Sales managers deciding how to enter new markets
• Plant managers deciding how to optimise their plant
• Senior managers deciding how to set up new business
• Senior managers making decisions about acquisitions and divestment
• Technical managers, making decisions about developing organisational capability

and so on

One of our clients focused their KM applications at senior level, and likened this to "KM removing the thorn from the lion's paw". If you solve the lion's problems, the lion will always be on your side!

The biggest decisions are made at the highest level, and there the need for knowledge may be greatest and the application of knowledge can yield the best return. That's where some of the thorniest issues can be resolved through the application of Knowledge.  That's where some of your most influential knowledge workers reside.

How to address the knowledge workers in your KM program

Early in your KM implementation program, identify your customer base, and determine how best to support them.

1. Conduct a stakeholder analysis
2. Clarify who the knowledge workers are, at all levels
3. Get to know their knowledge needs
4. Ask how they would like KM to support them in their work
5. Find out their high-value knowledge
6. Determine the places where KM will add greatest value
7. Don't forget the middle and senior managers- solving their KM problems will often add more value than solving lower level problems, and what is more will gain you that much-needed senior support. 

Contact us if you need help in analysing your stakeholders - at all levels in the organisation.

How KM can help revolutionise knowledge work, as manual work was revolutionised last century.

Peter Drucker said that our task this century is to revolutionaise the productivity of the manual worker. Here's how KM can help.

Assembly Line, from Library and Archives Canada, via Flickr

Peter Drucker famously said that ‘the most important, and indeed the truly unique, contribution of management in the 20th century was the fifty-fold increase in the productivity of the manual worker in manufacturing. The most important contribution management needs to make in the 21st century is similarly to increase the productivity of knowledge work and knowledge workers. The most valuable assets of a 20th-century company was its production equipment. The most valuable asset of a 21st-century institution (whether business or nonbusiness) will be its knowledge workers and their productivity."

"Similarly to increase" implies a 50-fold productivity increase, similar to that seen in manual work.  That's a big challenge, but maybe knowledge management can learn from manual work about how such productivity gains are possible. 

The 50-fold productivity increase in manual work productivity that Drucker mentioned came through a number of factors;

1. The division of manual work into tasks, as in an assembly line process, and the recognition that the manual worker did not need to make everything. They would have their task, work on their component, and others would make the rest. As Wikipedia says, referring to Adam Smith's famous example of the pin factory - "Previously, in a society where production was dominated by handcrafted goods, one man would perform all the activities required during the production process, while Smith described how the work was divided into a set of simple tasks, which would be performed by specialized workers. The result of labor division in Smith’s example resulted in productivity increasing so that the same number of workers made 240 times as many pins as they had been producing before the introduction of labor division."
   
   
2. The elimination of waste effort, so that the work is done the simplest way, the easiest way, the way that puts the least physical and mental strain on the operator, and the way that requires the least time. 
   
   
3. Automation, so that machines can take much of the burden of labour that the human used to provide, and 
   
   
4. A supply chain for component parts, so that the worker, when they need a part, find it immediately to hand and do not need to go out and find it, or buy it, or make it. 

So how can we make similar productivity improvements for the knowledge worker?

We can improve the productivity of knowledge work in much the same way. 

1. Much as a manual worker no longer needs to do everything or make everything, a knowledge worker no longer needs to know everything. Some knowledge they keep in their heads, the remainder is made available to them through the knowledge management framework. So a knowledge worker, facing an unfamiliar task, no longer has to think "how should I address this task" and find out by trial and (costly) error, but can ask "how do others address this task" (or, even better, "what have we found is the most effective way to address this task").  In the assembly line, the manual effort is shared between many to make every product. In knowledge management, the learning and experience is shared between many to make every decision. Instead of the division of manual labour, we now have "the division of knowing". Everyone has their knowledge task, and the knowledge to conduct that task is freely available as a common asset.
   
   
2. The elimination of waste effort. It should be very easy for the knowledge worker to find the knowledge they need. They should not have to search a repository of jumbled documents, or trawl through a crowded twitter stream, or ask their manager, who asks his manager, who asks her manager ..... The intellectual work of sifting and synthesising knowledge should already have been done. 
   
   
3. This includes the automation of much of the knowledge-finding, through powerful search and indexing, through provision of one knowledge base and not many, through the ability to ask a network rather than asking individuals, through knowledge being pushed to the worker at time of need, and through the use of powerful AI tools. 
   
   
4. Finally knowledge management should provide the supply chain for the knowledge worker, and should be a lean and efficient system for delivering valuable actionable knowledge to the point and time of need. When the knowledge worker needs an answer or a process to follow,  they should find it immediately to hand and not need to go out and search laboriously for it, or make it up, or learn it the hard way.
   
   

It is through effective KM approaches such as these that we can approach Drucker's vision of increasing the productivity of the knowledge worker fifty-fold.

"KM rights and responsibilities" charter at Oxfam

What rights do your workers have in terms of access to knowledge? What are their corresponding responsibilities?

Intermon Oxfam by on Mover el Bigote on Flickr

Knowledge management is well developed in the aid and development sector, perhaps because knowledge, in this sector, as a more abundant resource than money. Oxfam have had a knowledge management program for over a decade and Knowledge Management was a main item in Oxfam's 2013 to 2019 strategic plan.

The rights and responsibilities charter below was presented by Oxfam at KMUK, and struck me as a great way to define the two-way contract between the knowledge worker and the KM system, listing both  "what's in it for me" and "what is expected of me in return".

I particularly like the distinction between "I can" (what's in it for me) and "I must" (what's expected of me)

Rights

I can

• Find other people easily from across Oxfam regardless of role, affiliation or location. 
• Learn about success and failures of others experience. 
• Find and Use data about successful program models and results 
• Find the most highly rated and used guidance materials 
• Find the most highly rated and use advice available within Oxfam or out 
• Access the time of others – regardless of role, affiliation or location
• Info on key trends and research. 

Responsibilities 

I must

• Update my profile information- make myself accessible, find-able 
• Share my program data – design, theory of change, core assumptions and risks 
• Share my evaluative data-especially MEL data, evaluations and learning on successes and failure 
• Rate the quality of learning guidance and use 
• Rate the quality of advice –written, virtual or face to face. 
• Comply with best practices standards 
• Work towards the strategic priorities of the Oxfam Strategic Plan.

Can you create a similar charter for knowledge workers in your own organisation?

The essential point of being a knowledge worker

A blog post appeared in the Huffington Post a few years ago entitled "you are more than a knowledge worker", which, in my view, completely missed the essential point of knowledge work. 

Carmen Iannacone: Hello I'm a knowledge worker.
 By Michael Edson on Flickr

The basic premise on which the blog post is constructed was that being a knowledge worker means "your worth at work is directly related to how much you [personally] know".  The author then went on to say that your personal knowledge alone is not enough, you need other things, such as Experience, Expertise, Eccentricity and Educability.

However the worth of a knowledge worker is NOT directly related to how much you personally know.  That is not the essential point of being a knowledge worker.

The knowledge worker differs from the manual worker in that their work involves the application of knowledge rather than the application of muscles, but that doesn't mean that the knowledge has to be held by the individual worker.

The knowledge worker *applies knowledge* rather than *holds knowledge in their head*.

Much as automation massively increased the productivity of the manual worker by giving them power way beyond their personal strength and dexterity, and by allowing them to share their strength and skill with that of others, so Knowledge Management massively increases the productivity of the knowledge worker by providing knowledge as a shared asset, something every worker can draw on and contribute to.   Knowledge is the knowledge worker's raw material, but that knowledge should be the knowledge of the whole company, not of the individual.

The skills of a knowledge worker include the skills of sharing and learning, as the blog author alludes to in the "educability" section. This is not an additional element to knowledge work - it is a core skill for someone who works with knowledge. It is the "learner" element of the knower-learner spectrum, and the blog author is assuming that a knowledge worker must be a "knower".

A great knowledge worker is a person who seeks and finds knowledge to apply at work, and then shares their own knowledge and experience with others. A good knowledge company is one that supports their knowledge workers by making knowledge a shared, accessible, re-usable and continuously improved resource, through setting up a KM Framework.

For a knowledge worker in a good knowledge company, your worth at work is directly related to how much you can learn, how much you can apply what you have learned, and how much you can share new knowledge with others. Not how much you personally know.

Why the "Working Teams" dimension is important in KM

We hear a lot about communities of practice and social networks in Knowledge Management, but we should not lose sight of the other dimension of the knowledge equation - the work teams.

Image from wikimedia commons

Work teams are often the way work gets done in organizations, and a team of knowledge workers is effectively a knowledge team. Any complete knowledge management framework needs to cover the team dimension, because teams create knowledge, and teams use knowledge.

Teams create knowledge

Knowledge is related to activity—you learn from experience, from ‘doing things’. In most of the companies to which Knoco consults, ‘things are done’ by teams. In the oil industry, construction industry, engineering, mining, television, etc, most of the big work is done by multidisciplinary teams, and therefore, the organisational unit for reviewing that work is the team.

Please note that although Knowledge  is related to activity, it actually comes from reflection on activity (see posts on the importance of reflection, and 6 benefits of reflective team learning). A team will not collectively create knowledge unless they reflect collectively. This will not happen unless you do it deliberately. Most team communications are action-oriented (What have we done? What needs to be done? What will we do next) rather than reflection-oriented (Why did these things happen? What did we learn? What can we improve?). To introduce reflection, you need to introduce reflection processes and methods; not just assume that will reflection will happen during normal team discourse.


Some of the more familiar methods for reflective Knowledge creation and capture within a team/activity/project environment are the after action review and the retrospect. These are processes for structured discussions between the team members to identify any new lessons and new knowledge which has been created during the activity or the project.

Teams apply knowledge

Teams create knowledge, but they also seek, re-use and apply knowledge. They need to learn from others in order to perform their tasks effectively. Team learning can be organised through the use of a Knowledge Management plan, and will involve processes such as Peer Assist where the team talks with other experienced practitioners to draw on their lessons.

Teams manage their own knowledge

Teams need to manage the knowledge they are creating, where it is specific to the team (knowledge which is generic, and applies to other teams, needs to be managed by the communities of practice). You may need to introduce team knowledge technology to help manage this knowledge.

Much of the Team technology such as Trello, Zoom, MS Teams etc are designed to manage activity, connectivity and work products, not knowledge. You probably need a team lessons log, and potentially a team blog and a team wiki as well, so long as the blog is used to summarise and share reflections and knowledge rather than to share progress and activity reports.

Communities of practice share knowledge

If the work teams create and apply knowledge, then the role of the communities of practice and the social media is to provide a mechanism to transfer this knowledge from one work team to another on a daily basis. 

Knowledge Management in a hierarchical culture

The best definition of a Knowledge Worker is "someone who knows (or learns) more about their job than their boss does".  So how does this work in a hierarchy?

Percentage of people in each country who agreed with the statement
"It is important for a manager to have precise answers to most of the
questions their subordinates may raise about their work".

The definition I use above means that the Knowledge Worker uses knowledge for their daily tasks. They do not blindly follow orders;  they use knowledge to develop approaches and strategies for delivering their objectives.  They are hired not just to do work, but to think as well. They make decisions for a living.

Knowledge Management aids the knowledge worker by providing them with the knowledge they need to do their job well and to make the correct decisions; this knowledge often having been developed through the collective experience of all the knowledge workers in the firm.

Managing a knowledge worker therefore is a different proposition from managing a manual worker. You cannot micromanage, you do not need to supervise; instead you need to give clear objectives and empower the knowledge worker to deliver the best solution.  Part of that empowerment is developing Knowledge Management Attitudes, Habits and supporting Framework, so the knowledge worker can always find the best knowledge to help them make the best decisions.

However if KM really is in support of "knowing more than the boss", and the Knowledge Management framework becomes the source of knowledge, rather than the boss being the source of knowledge,  then this can be really difficult in hierarchical cultures. 

The graph shown above is taken from the book "The culture map", and is based on work by Andre Laurent at INSEAD. Andre asked hundreds of European managers about leadership issues, and one of the questions he asked was  "Is it important for a manager to have precise answers to most of the questions their subordinates may raise about their work". In other words, "should a manager know more than their subordinates".

We can see the results above. Less than 10% of Swedes agreed with this statement, compared to nearly 60% of Spaniards.  I suspect that in some of the more hierarchical non-European cultures, such as China, Russia, the Middle East, Japan and India, the proportions supporting this statement would be even higher. In these hierarchical cultures, "being the boss" equates with "having the answers".  This is of course crazy in a world of knowledge work, where the experience and knowledge lies in the community rather than the leadership.

It would can be tough to be a knowledge worker in these cultures. Although you need to "add knowledge" to do your job well, your manager is convinced (or nearly 60% convinced in the case of Spain) that he or she should know best. Conflict is likely to arise between the knowledge worker's higher knowledge level and the managers perceived need to be the knowledge holder.

So how do we address this conflict? I would suggest five approaches;

1. Openly discuss the cultural issue, and the barrier this may cause to Knowledge Management, and therefore to the success of the knowledge-based business.
2. Discuss the new role of the manager, which is to set the expectations and goals rather than to provide the answers. 
3. Develop the Knowledge Management Framework which allows the knowledge workers to find the answers they need.
4. Educate the managers on the value of the KM Framework. Show them some examples and stories of the value it brings. Suggest to them that if a subordinate comes to them looking for an answer, their first response should be to ask "Have you used the KM system? What answers did you get?"
5. Make sure the KM Framework supports the managers as well as their subordinates. Managers are knowledge workers too; they also make decisions based on knowledge. If the KM system provides them with better knowledge, and if they can see the advantages this brings, then they are more likely to promote this for their subordinates as well. 

A  hierarchy is a good way to assign authority and accountability, but should not be assumed to represent the way knowledge is distributed.

Knowledge workers - suppliers as well as consumers of knowledge

Here's another characteristic of Knowledge workers - they supply as well as consume knowledge.

I blogged recently about what makes a Knowledge Worker, and suggested that a Knowledge Worker is someone who knows more about their job that their boss or client, and so is hired for what they know as well as what they do.  Also that the role of Knowledge Management is to give the Knowledge Worker access to the knowledge they need to perform their role.

However this flow of knowledge is not one-way. The KM framework should not only give the knowledge workers access to knowledge, it should also provide a means for the share their knowledge as well. The flow of knowledge is multi-way.

That's what distinguishes KM from Learning and Development. In L&D the workers are seen as consumers of knowledge, whereas in KM, the knowledge workers are both consumers and suppliers.  KM should allow the knowledge workers to share access to knowledge; both the knowledge that has been documented and collected, and the knowledge that the other knowledge workers still hold in their heads.

If the knowledge workers both supply and consume, then knowledge becomes collective property, with each knowledge worker both contributing and benefiting to the collective commons. This is both the outcome that KM looks to deliver, and the value proposition that you present to the knowledge workers. It is like a deal that you, as Knowledge Manager, strike with the knowledge workers 

"We will give you access to all the knowledge of your co-workers, to make your job easier and to save you time. All we need in return is for you to also share what you know".

"Knowledge Worker" - an illustration and definition

Peter Drucker introduced the term "Knowledge Worker" - but what exactly IS a Knowledge Worker?

Image from Wikimedia Commons

When Drucker introduced the term in 1959, in his book "Landmarks of Tomorrow", he was primarily writing about people working in IT - the programmers, systems analysts, academics and researchers.  However this was before the field of Knowledge Management was developed, and as Knowledge managers we often see the Knowledge Workers as one of our primary stakeholder groupings.

So we need to know who the knowledge workers are, and how they differ from other workers.

Here is an illustration that might help.

When my wife and I first moved into our current house, we employed a local gardener. He was a very nice fellow, very happy and cheerful, but he knew nothing about gardening.  

 He was very good if you gave him detailed instructions, and would work hard mowing the lawn or trimming the hedge. However anything that required decision or judgement, was risky. There was the day that he weeded out all of the newly-planted border plants. There was the day my wife left some house plants by the car to take into school, and an hour later found them all planted out in the garden. There were many other examples of small scale garden disasters, and eventually we realised that we would have to replace him, as both of us work full time and are not able to supervise a gardener to the level that this guy required.   

Now we have a new team of gardeners. They are highly knowledgeable. We can give them a broad direction, such as “tidy up this border” or “prepare this area for soft fruit”, and they will do it, often adding bits that we had never considered, or giving us useful advice along the way. Sometimes they will even say “No, we shouldn’t be doing that, that’s not going to work; we should do this instead”.
The new team costs more than twice as much, on an hourly basis, as the first guy. That’s because they are knowledge workers, and he effectively was a manual worker. 

The simplest definition of a knowledge worker is “somebody who knows more about their job than their supervisor/client does”. (Or perhaps I should have said "Knows, or can find out,").

 So instead of the client or manager providing the knowledge and the worker providing the labour (gardener number one), the client/managers provide the direction and they provide both the knowledge and the labour (gardening team number two).  The Knowledge Worker takes over much of the task-related decision making from the manager/client, applying their knowledge to make correct decisions.

Because a Knowledge Worker uses knowledge as a core resource for doing their job, Knowledge Management can increase the productivity of the Knowledge Workers by providing them better access to the knowledge resource.

So in our story, the first guy was not a knowledge worker, and we had to tell him in detail what to do, and sometimes how to do it. The current guys sometimes tell us what they should be doing, and always know better than us how it should be done. Also in this we can see the value of the knowledge, represented by the difference in the two hourly rates. The asset that the new guys bring is their knowledge, and we need to pay double the base rate in order to get access to it.

Being a Knowledge Worker is no longer the preserve of the IT staff. Anyone who makes decisions and judgments for a living can be a Knowledge Worker - an engineer, a doctor, an architect, an oil driller, or a consultant.

In fact, even a gardener can be a knowledge worker.

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

Revolutionising the productivity of the knowledge worker 2 - knowledge automation

Yesterday I blogged about the challenge to revolutionise the productivity of the knowledge worker, and how the first step was the division of knowledge. The second step is the automation of knowledge work. 

Image from wikipedia commons

Automation was one of the factors that helped revolutionise the productivity of the manual worker.  The blacksmiths hammer was replaced by the hydraulic press, the auger by the electric drill, the wheelbarrow by the forklift truck. Machine power augmented muscle power. Automation, combined with the division of labour, gave us the modern assembly line.

Automation is one area where KM has done well. Perhaps we should say augmentation rather than automation. As Tom Davenport points out, smart technology is not yet replacing humans, but augmenting their power. Much as a hydraulic press augments the metal worker rather than replaces him, smart KM technology augments the knowledge worker, rather than replacing her. 

• Knowledge bases augment the knowledge worker's memory. Rather than keeping our own notebooks, or trying to remember details of a process or procedure, we can consign it to a knowledge base. And if this is a shared knowledge base, then we have access to the knowledge of many people, rather than just our own. 
• Search engines augment our power of recall. without significant mental effort, we can retrieve a fact or an image or a process from deep within a knowledge base, thanks to the power of search, be it keyword search or semantic search. 
• Smart technology can also take the role of a mentor, and suggest knowledge to use when we need it (based on where we are in a process or a task), even before we ask for it.
• Technology can also augment our personal networks, allowing us to ask not just our immediate colleagues for help and advice, but hundreds or thousands of co-practitioners we may never have met.
• Technology can augment our ability to communicate, allowing us to hold virtual meetings across continents and timezones.
• Technology augments our ability to see patterns in vast quantities of data and information, and to apply our knowledge to make sense of these patterns, and use them to support decision making. 

Automation/augmentation is an area where already great strides have been made in helping increase the knowledge workers' productivity. However this is not the only area that needs to be addressed, and tomorrow we will look at the third component, the Knowledge Supply Chain. 

Revolutionising the productivity of the knowledge worker part 1 - division of knowledge labour

Image from wikimedia commons

Peter Drucker famously said that ‘‘The most important, and indeed the truly unique, contribution of management in the 20th century was the fifty-fold increase in the productivity of the manual worker in manufacturing. The most important contribution management needs to make in the 21st century is similarly to increase the productivity of knowledge work and knowledge workers". And it's our job, as Knowledge Managers, to make this happen.

That is the big challenge to the Knowledge Managers of this world - to increase the productivity of knowledge workers by a factor of 50. The good news is that we are half way there. The bad news is that we have a long way still to go.

I already provided a summary of this task in a previous blog post, but would like to amplify, here and over the next few days, on the four factors which we, as Knowledge Managers, can influence. And the first of these is the division of knowledge labour.

The manual worker equivalent

The division of labour was a huge step in manual worker productivity. This involved dividing
manual work into tasks, as in an assembly line process, and the recognition that the manual worker did not need to make everything. They would have their task, work on their component, and others would make the rest.

My grandfather was a village blacksmith. He was a craftsman - he could make a set of wrought-iron gates, for example, which were a work of art. He would start with iron bars, and do all the work himself. The result was excellent quality, but it took a very very long time.

Nowadays iron gates are made in a factory. The quality may be less (though they are definitely fit for purpose, and in some cases factory quality is better than craftsman quality), the cost is far less, and the productiviy is massively higher.

As Wikipedia says, referring to Adam Smith's famous example of the pin factory - "Previously, in a society where production was dominated by handcrafted goods, one man would perform all the activities required during the production process, while Smith described how the work was divided into a set of simple tasks, which would be performed by specialized workers. The result of labor division in Smith’s example resulted in productivity increasing so that the same number of workers made 240 times as many pins as they had been producing before the introduction of labor division."

Division of knowledge labour

The knowledge equivalent of a craftsman is an expert. Much as a craftsman such as my grandfather would make the whole object himself, from raw materials, so an expert would hold all the knowledge in their head, from first principles to the final decision.  Many decades ago, if you needed knowledge to be applied, you called the expert. You got good results, the quality of decisions was good, but it may take a long time to find and deploy the expert.

Just as the transition from a craftsman economy to a manufacturing economy involves the division of labour, so different people make different parts, so the transition from an expert economy to a knowledge economy involves the division of knowledge, so that different people know different parts.

The division of knowledge is the recognition that knowledge can be more effectively deployed and managed within a community or network, rather than held by an expert, and the division of knowledge work is the effective use of networked knowledge workers.

In many organisations, this shift has happened. Knowledge work has become divided - people know as much as they need to know and no more, confident that they can find any extra knowledge when needed.  Juniors perform tasks, with the help of KM, which in the past were the domain of experts.  New hires answer customer queries, junior GPs address topics that used to be the purview of specialists, young lawyers do the work that partners used to do.  From being the "font of all knowledge," the experts become the "stewards of knowledge" on behalf of the community.

Division of intellectual labour is "work in progress" for KM - a movement that has started, but maybe can develop even further. By dividing the knowledge work, we avoid the need to rely on experts for every decisions, and massively improve the productivity of the knowledge workers, provided they have access to the knowledge needed for their component of knowledge work. How that knowledge is provided will be covered in tomorrow's post.

Who are the knowledge workers?

The knowledge workers represent one of your two main stakeholder groupings for Knowledge Management implementation. But who exactly are they?

HA0510-079 by Highways England on Flickr

Firstly we can eliminate from the group "knowledge worker" anyone who is purely a manual worker - someone who follows orders or preassigned inflexible procedures. Labourers on a construction site, individuals on an assembly line and so on.  These are not the customers for KM.

However they could become knowledge workers.

Toyota led the way in showing that assembly line workers could become knowledge workers, if you involve them in analysing the work they do. Kaizen-style meetings provide a format where the manual workers can become knowledge workers, accountable not just for doing the work, but improving the way the work is done.

If we eliminate any manual workers that remain, we are left with a group we can call the decision makers.  These are people who need to use knowledge and judgement in order to do their work.  The better the knowledge we can supply them with, the better the judgements they will make.

This definition of knowledge worker includes people such as;

• Engineers making design decisions
• Sales staff deciding how to sell to a customer
• Lawyers trying to decide the best legal solution
• R&D scientists trying to develop new technology
• Government staff determining policies
• Aid and development staff trying to design and apply interventions
• Medical staff making decisions about patients
• Soldiers making decisions on the battlefield
• Maintenance engineers trying to decide how to maximise the utility of equipment

and so on.

Don't forget the managers

Then there is a group which is often neglected in KM initiatives - the middle and upper managers. 

Management also make decisions, and often very big decisions, with costly implications. They also need access to the best knowledge they can find, and if your KM program cannot help them they will need to hire in expensive external consultants. 

So the following are also knowledge workers;

• Project managers making decisions on major (and minor) projects
• Divisional managers making decisions about market penetration
• Sales managers deciding how to enter new markets
• Plant managers deciding how to optimise their plant
• Senior managers deciding how to set up new business
• Senior managers making decisions about acquisitions and divestment
• Technical managers, making decisions about developing organisational capability

and so on

One of our clients focused their KM applications at senior level, and likened this to "KM removing the thorn from the lion's paw". If you solve the lion's problems, the lion will always be on your side!

The biggest decisions are made at the highest level, and there the need for knowledge may be greatest and the application of knowledge can yield the best return. That's where some of the thorniest issues can be resolved through the application of Knowledge.  That's where some of your most influential knowledge workers reside.

How to address the knowledge workers in your KM program

Early in your KM implementation program, identify your customer base, and determine how best to support them.

1. Conduct a stakeholder analysis
2. Clarify who the knowledge workers are, at all levels
3. Get to know their knowledge needs
4. Ask how they would like KM to support them in their work
5. Find out their high-value knowledge
6. Determine the places where KM will add greatest value
7. Don't forget the middle and senior managers- solving their KM problems will often add more value than solving lower level problems, and what is more will gain you that much-needed senior support. 

Contact us if you need help in analysing your stakeholders - at all levels in the organisation.

Revolutionising the performance of the knowledge worker.

Peter Drucker famously said that ‘‘to make knowledge work productive will be the great management task of this (20th) century, just as to make manual work productive was the great management task of the last century". To find out how we might do this, let's look at how the productivity of manual work was revolutionised.

Assembly Line, from Library and Archives Canada, via Flickr

The 50-fold productivity increase in manual work productivity that Drucker mentioned came through a number of factors

1. The division of manual work into tasks, as in an assembly line process, and the recognition that the manual worker did not need to make everything. They would have their task, work on their component, and others would make the rest. As Wikipedia says, referring to Adam Smith's famous example of the pin factory - "Previously, in a society where production was dominated by handcrafted goods, one man would perform all the activities required during the production process, while Smith described how the work was divided into a set of simple tasks, which would be performed by specialized workers. The result of labor division in Smith’s example resulted in productivity increasing so that the same number of workers made 240 times as many pins as they had been producing before the introduction of labor division."
   
   
2. The elimination of waste effort, so that the work is done the simplest way, the easiest way, the way that puts the least physical and mental strain on the operator, and the way that requires the least time. 
   
   
3. Automation, so that machines can take much of the burden of labour that the human used to provide, and 
   
   
4. A supply chain for component parts, so that the worker, when they need a part, find it immediately to hand and do not need to go out and find it, or buy it, or make it. 

So how can we make similar productivity improvements for the knowledge worker?

We can do improve the productivity of knowledge work in much the same way. 

1. Much as a manual worker no longer needs to do everything or make everything, a knowledge worker no longer needs to know everything. Some knowledge they keep in their heads, the remainder is made available to them through the knowledge management framework. So a knowledge worker, facing an unfamiliar task, no longer has to think "how should I address this task" and find out by trial and (costly) error, but can ask "how do others address this task" (or, even better, "what have we found is the most effective way to address this task").  In the assembly line, the manual effort is shared between many to make every product. In knowledge management, the learning and experience is shared between many to make every decision.
   
   
2. The elimination of waste learning effort. It should be very easy for the knowledge worker to find the knowledge they need. They should not have to search a repository of jumbled documents, or trawl through a crowded twitter stream, or ask their manager, who asks his manager, who asks her manager ..... The intellectual work of sifting and synthesising knowledge should already have been done. 
   
   
3. This includes the automation of much of the knowledge-finding, through powerful search and indexing, through provision of one knowledge base and not many, and through the ability to ask a network rather than asking individuals. 
   
   
4. Finally knowledge management should provide the supply chain for the knowledge worker, and should be a lean and efficient system for delivering valuable actionable knowledge to the point and time of need. When the knowledge worker needs an answer or a process to follow,  they should find it immediately to hand and not need to go out and search laboriously for it, or make it up, or learn it the hard way.
   
   

It is through effective KM approaches such as this that we can approach Drucker's vision of increasing the productivity of the knowledge worker fifty-fold.

The essentials of being a knowledge worker.

A blog post appeared in the Huffington Post a couple of weeks ago entitled "you are more than a knowledge worker", which, in my view, completely missed the essential point of knowledge work. 

Carmen Iannacone: Hello I'm a knowledge worker. By Michael Edson on Flickr

The basic premise on which the blog post is constructed was that being a knowledge worker means "your worth at work is directly related to how much you [personally] know".  The author then went on to say that knowledge alone is not enough, you need other things, such as Experience, Expertise, Eccentricity and Educability.

However the worth of a knowledge worker is NOT directly related to how much you personally know.  That is not the essential point of being a knowledge worker.

The knowledge worker differs from the manual worker in that their work involves the application of knowledge rather than the application of muscles, but that doesn't mean that the knowledge has to be held by the individual worker.

The knowledge worker *applies knowledge* rather than *holds knowledge in their head*.

Much as automation massively increased the productivity of the manual worker by giving them power way beyond their personal strength and dexterity, and by allowing them to share their strength and skill with that of others, so Knowledge Management massively increases the productivity of the knowledge worker by providing knowledge as a shared asset, something every worker can draw on and contribute to.   Knowledge is the knowledge worker's raw material, but that knowledge should be the knowledge of the whole company, not of the individual.

The skills of a knowledge worker include the skills of sharing and learning, as the blog author alludes to in the "educability" section. This is not an additional element to knowledge work - it is a core skill for someone who works with knowledge. It is the "learner" element of the knower-learner spectrum, and the blog author is assuming that a knowledge worker must be a "knower".

A great knowledge worker is a person who seeks and finds knowledge to apply at work, and then shares their own knowledge and experience with others. A good knowledge company is one that supports their knowledge workers by making knowledge a shared, accessible, re-usable and continuously improved resource, through setting up a KM Framework.

For a knowledge worker in a good knowledge company, your worth at work is directly related to how much you can learn, how much you can apply what you have learned, and how much you can share new knowledge with others. Not how much you personally know.