How the Asian Development Bank is moving towards a "knowledge demand" model

In this YouTube video, Vivek Raman describes how KM at the Asian Development Bank is moving from a Push model (driven by knowledge supply) to Pull model (driven by knowledge demand) for its knowledge products and solutions. 

As Vivek says -

"Our challenge was complex: One, we needed to design a new methodology to string together all of ADB’s complex knowledge products and services for a country. Two, we needed to make sure this was not seen as additional work or burdensome by resident mission staff and actually, added value to their work. Three, and most importantly we needed to change government’s viewpoint that ADB is an active knowledge partner. So, for the methodology we decided to go back to the basics and approach it like a child’s problem. Nothing we designed was rocket science".

Vivek goes on to describe the development of consultative country knowledge plans, as a way of achieving a more pull-driven approach.

Read more about knowledge push and pull here, here and here

See more videos about KM at ADB

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

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

Image from wikimedia commons

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

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

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

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

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

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

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

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

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

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

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

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

How to map the knowledge "sticking points"

Knowledge transfer often requires several steps, and knowledge can get stuck along the way. But where are those sticky points?

I have often used the analogy of a Supply Chain when looking at knowledge transfer, with knowledge as a resource to be supplied to the knowledge workers on whose decisions the firm depends, in order to support them in making the best available decisions.

That knowledge supply chain can be very simple, in the case (for example) of a supervisor coaching their staff.  Or it can be complex, as in the case of organisational lesson learning. Where the supply chain is complex, involving many steps. it can be all too easy for the knowledge to get stuck or to run into quicksand along the way; never to reach the knowledge worker.

If we can map out the supply chain, we can find the sticking points, and un-stick the knowledge.

The figure here is reproduced with permission from a thesis dissertation by Catherine Barney, entitled "Cross-project learning in project-based organizations", and Catherine did just this exercise of mapping the knowledge supply chain.

Catherine was studying knowledge management and lesson-learning in a major European engineering company. As part of her dissertation, Catherine surveyed the company to measure employees' satisfaction with various steps (or "aspects") in the lessons learned cycle (an important component of the knowledge supply chain for this global organisation).

She mapped the chain as having 6 components

• Lesson identification through the lessons procedure
• Lesson validation
• Direct application of lessons
• Future application of lessons
• Lesson storage
• Lesson retrieval

Her lower diagram (above) is interesting. Every step of the process seemed to need significant improvement, but this need was smallest with the first step - lesson identification - and indeed the content of captured lessons showed the highest level of satisfaction. With every step after that, dissatisfaction grows. This could either be because this company (like many others) thinks the job is done once the lesson is "captured", or because inefficiencies along the chain combine to make each step progressively less satisfactory (in other words, poor verification on top of poor capture leads to even less satisfaction with application).

By the time you get to the storage and retrieval steps, almost everyone says that a large improvement is necessary.

It looks like lessons are entering the chain, but getting lost or stuck as they go along. If this company wants to improve their lesson supply chain, they need to focus not so much on lesson capture and validation, but what happens to the lessons afterwards, and how they are re-used.

Contact us for help in mapping the sticking points in your lessons chain.

Please take part in this new (short) survey - how Covid has affected KM

 Please take 5 minutes to reply to this short survey on how the Covid pandemic and accompanying recession has affected KM

Image from wikimedia commons

If you were involved in an organisational Knowledge Management program a year ago, at the start of the recession, please consider answering the short survey below, and let us know how things have changed in the interim.

https://www.surveymonkey.co.uk/r/generalaccess

• Maybe KM found a stronger purpose during Covid, and has been busier than ever
• Maybe the KM program was hit by the recession, and the budget was cut or completely eliminated
• Maybe KM changed direction
• Maybe you found things easier, or more difficult

It would be good to know!

The survey will take 5 or 6 minutes, it is between 4 and 11 questions depending on circumstance, and we will share the results in about  month time when we have collated all responses.

Your input would be very welcome.

Dejargonising Knowledge Management

Humans have a habit of combining concepts into "chunks". It helps us remember things more easily, but the jargon associated with "chunks" can confuse others when we try to communicate, if they don't have the same set of combined concepts. 

I am going to attempt to de-chunk and dejargonise KM in this blog post.

Jargon, by Tom Pickering, on Flickr

It's very hard communicating with people about technical things, especially in writing. We have to explain concepts, and if we start from first principle every time, then it takes a long time. When you are talking with, or writing for, other experts you can take short cuts by using shared technical terms (aka Jargon) to describe concepts, combined concepts, and even concepts about combined concepts.

A community of practice, for example, is a group united by jargon, with a shared conceptual model, and a terminology of their own which can be impenetrable to outsiders, and althrough experienced community members communicate easily through jargon, new members can rapidly become confused.  Indeed the term "community of practice" is already a piece of jargon which needs explanation to people outside the Knowledge Management industry. 

However for people who are not in the community of practice, jargon makes communication impenetrable.

Conceptual chunks

There is an excellent book by Stephen Pinker, the cognitive scientist and Harvard professor of psychology, called "The Sense of Style, The Thinking Person's Guide to Writing in the 21st Century". In this book, Pinker looks at good communication through writing, and examines the psychological barriers to writing well.  He talks about jargon, and gives this tremendous example of how people use conceptual "chunks" to described increasing levels of abstraction about a topic.

As children we see one person hand a cookie to another, and we remember it as an act of giving. One person gives another one a cookie in exchange for a banana; we chunk the two acts of giving together and think of the sequence as trading. Person 1 trades a banana to Person 2 for a shiny piece of metal, because he knows he can trade it to Person 3 for a cookie; we think of it as selling. Lots of people buying and selling make up a market. Activity aggregated over many markets gets chunked into the economy. The economy can now be thought of as an entity which responds to action by central banks; we call that monetary policy. One kind of monetary policy, which involves the central bank buying private assets, is chunked as quantitative easing. 

As we read and learn, we master a vast number of these abstractions, and each becomes a mental unit which we can bring to mind in an instant and share with others by uttering its name.

Without explanation, these conceptual chunks become impenetrable jargon, and many of us may have struggled by the time we get to "quantitatve easing". 

Do we do the same chunking with Knowledge Management?  Sure we do! We have our own jargon, very useful when communicating among our KM community, but not so useful for outsiders.

Can we de-chunk KM in the same way as Pinker did with quantitative easing?

Here is my attempt.

De-chunked KM

The mental resources we have, that we draw upon to make decisions and take actions, are knowledge. When we gain knowledge, this is known as learning. We can learn from our own experience, or from experience and knowledge shared by others. Sometimes this sharing is done through the medium of records such as books, videos and so on. Such records, from which people can learn, are sometimes called codified knowledge. (Sometimes people call this explicit knowledge, although this term is not well defined nor used consistently).

When one person helps another to learn, either by teaching, coaching or advising them, by learning with them, or by creating records from which others learn, this is called knowledge transfer. Knowledge transfer is sometimes divided into the behaviours of offering knowledge to others (knowledge sharing) and looking for knowledge from others (knowledge seeking). Formal knowledge transfer in a classroom setting is known as teaching or training, while a broader approach to routine and systematic knowledge transfer within an organisation is known as knowledge management. 

When knowledge transfer is scheduled and structured as one or more discrete activities, these structured activities are known as a knowledge management processes. There are many such possible processes, each with their own name and their own structure. People have developed these processes and structures to make knowledge transfer more effective in a particular context.

Where knowledge transfer is helped through the use of specific technology, this is referred to  knowledge management technology. There are many such possible technologies, each with their specific function.  Some help you share knowledge, some allow you to seek for and find knowledge

Where there are people with a defined role to play in making sure that knowledge management works properly, these people are said to have knowledge management roles. There are many such possible roles, each with their specific accountabilities.  Some ensure the KM processes happen, or work well, some support the technology, some take care of the codified knowledge.

There are many things that the leaders of an organisation can to to promote, support and sustain knowledge management, and these things are collectively known as knowledge management governance. 

Perhaps the most important role for leaders is to promote and support a feeling or attitude among the organisation's members that knowledge, and knowledge management, are important, and thereby to promote and support the behaviours of knowledge seeking and knowledge sharing, using the knowledge management processes, technologies and roles. These attitudes and behaviours are referred to as a knowledge management culture.

Where an organisation has a set of KM roles, processes, technology and governance, where the parts are linked and work together, this is known as a knowledge management framework.

Designing and introducing a KM framework to an organisation is called knowledge management implementation. One document commonly used to frame and steer implementation is the knowledge management strategy. Once implementation is complete, knowledge management can be sustained by a knowledge management policy.

And if you are a knowledge manager, the framework, implementation, strategy and policy are your job.

6 things Knowledge Management can learn from Safety Management

I often argue that safety management is a good analogy to knowledge management. Here are 5 things KM can learn from safety.

Image from wikipedia

Safety management and knowledge management are close analogues. 

Both are management systems focused on intangibles and on behaviours. The main difference is that introducing safety management, especially in industries such as engineering and construction, has been widely successful. Introducing knowledge management has been much more hit-and-miss. 

There is therefore a lot that KM can learn from safety management, for example the 5 things below.

1. Behaviour change and culture change are possible.

The success of safety management relies on a change in attitudes towards safety among employees and contractors. The attitude has to change from "there are always risks, we can't really be safe, it's up to me how much risk I can personally accept" to "all risks can be minimised, we should really be safe, it's up to me to help improve the safety of the whole organisation". The fact that safety cultures are now widespread in many industries shows that a culture change like this is possible.

The KM culture change is a similar change in attitude, from seeing knowledge as something personal, to seeing knowledge as something that affects the whole organisation. If we can change the safety culture, then we can change the knowledge culture. Safety gives us a culture-change blueprint we can follow.

2. Leaders and senior managers need to be strongly involved in the behaviour change.

Safety culture goes hand in hand with safety leadership. Leaders are "the keepers and guardians of the attitudinal norms". A safety culture starts with leadership; leadership drives culture, which in turn drives behaviour. Management support encourages accountability and the recognition that safety is everyone’s responsibility.  Without the support of leadership, the safety culture is temporary.

The same is true for the Knowledge culture. Management support encourages accountability and the recognition that knowledge is everyone’s responsibility.  Without the support of leadership, the knowledge culture change will be temporary.

3. Intangibles need a management system or framework.

Wikipedia describes a safety management system as

...a businesslike approach to safety. It is a systematic, explicit and comprehensive process for managing safety risks. As with all management systems, a safety management system provides for goal setting, planning, and measuring performance. A safety management system is woven into the fabric of an organization. It becomes part of the culture, the way people do their jobs.

There are many such systems in place in different industries, and most of them contain elements such as the ones below

• Policy policy
• Organisational roles, responsibilities and accountabilities
• Processes for identifying, reporting and fixing safety risks (processes such as Hazids, near miss investigations and so on) investigation and audit)
• Audits and measures.

As far as KM is concerned, you could replace the word "safety" with "knowledge" in the wikipedia text above and it would make sense (if you remove the word "risk).  KM, like safety management, requires a system or a framework (I prefer the term Framework as "knowledge management system" is often interpreted to mean an IT system). The knowledge management framework would even contain similar elements - a KM policy, KM processes, KM roles, KM measures and audits. We might add "KM technology" as technology has more of a role to play in KM than it does in safety management. 

4. Even when the behaviour change is implemented, you can't relax.

Safety culture needs to be sustained. You don't eliminate the Health and Safety department once your safety record has improved, and leaders don't stop asking for accident statistics once they feel "the job is done". The safety job is never done, it requires constant vigilance, otherwise the culture can revert to how it was before.  Even when safety accountabilities are embedded within the projects and departments, there still remains a safety function, accountable for the safety management system itself.

KM will need a similar accountable sustaining function, even when the KM framework is fully embedded. We cannot assume that the KM team will do themselves out of a job - the job will never stop. At the very least they will need to pass the job on to someone else.

5. For the management system to really drive culture change, it needs to affect people's careers. 

Part of the reason why the safety culture has taken hold so well is that for many organisations, safety has become a non-negotiable.  If people do not behave safely, they know their job is at risk. The safety policy is a mandatory document, and compliance is mandatory.

Knowledge management may need to take the same hard line. We already see this in some organisations. The first words in the NASA KM policy are "compliance is mandatory". And as Bob Buckman wrote, "The people who engage in active and effective knowledge sharing across the organization should be the only ones considered for promotion."  If we believe that KM adds big value to our organisation, then KM should also become a non-negotiable.

6. You can even use similar metrics.

The primary difference between the two disciplines is that safety is more visible and more measurable. This makes it easier to implement. However we can even start to learn from the way safety is measured, which is through the reduction of safety incidents such as "lost time" incidents (when someone loses work hours through injury) or "near misses".  We can start to look for lost knowledge incidents, where people should have had access to knowledge but didn't, and so repeated a mistake or ignored a proven practice. We can even look for knowledge near misses, where someone found a critical piece of knowledge, but only by luck or chance. If we can eliminate these, then we have implemented successful KM, as well as adding value to the organisation.

So there are 6 ways in which you can treat KM like you treat safety management. Hopefully you can get KM to succeed in the same way as safety.

Quantified KM Value story #143; $10 million per year at Grant Thornton

The latest in my continuing series of KM value stories.

This one comes from this interview with Balaji Iyer; head of KM for Grant Thornton INDUS. 

Balaji states that 

"KM has positively impacted both the top line and bottom line for the firm. Just a conservative estimate of the value the KM programme adds over a normative five-year period is over $50 million in revenue and savings. Our KM programme has hit all the right notes in terms of improving speed to market and talent, vastly improving our internal efficiency play, significantly enhancing the employee experience, and driving innovation at an accelerated pace. And, we believe we are just getting started". 

"As an example, our tax technical research capabilities have resulted in multiple clients wins, grossing over millions of dollars. Our recently-launched knowledge product is the Tax Client Update tool (T-CUT) — a methodology that provides an automated agenda, populated with nationally reviewed technical updates for quarterly meetings with clients and prospects. It has contributed significantly to revenue generation".

For more quantified value examples from other organisations, see here.