Wednesday, 1 July 2020

How G2 got knowledge sharing to work

Here is a very interesting article from G2 about how they finally made knowledge sharing work, after failing twice.


The article, by Deirdre O'Donoghue, is a very interesting read. They tried to introduce structured knowledge sharing three times, and only succeeded at the third attempt.  What was different about that lucky Third Time?  Please note, the article is only about knowledge sharing, which as we know is just one component of Knowledge Management.

Firstly - what failed?


Lunch and Learns failed. 
I am not a great supporter of lunch and learns (see my article "Lunch and Learn? No thanks, I am trying to give it up") and they did not work for G2. As Dierdre says,

"People wanted knowledge shares to be standardized – not random. They also didn’t like sacrificing their lunchtime for learning. Instead, employees wanted to see that G2 leadership valued knowledge sharing enough to take time out of the actual workday".

Friday afternoon "sharing time" failed.
"A few of these sessions were successful because people came eager to learn and share. But Friday afternoon is a difficult time to focus, and everyone, including me, shifted focus from sharing work knowledge to sharing what their weekend plans were".

Finally, what worked? 


The solution that worked for G2 was a regular schedule, within office hours, of  knowledge sharing sessions, and a site where the shared knowledge  (in the form of presentations) could be found and referred to later. According to Dierdre, this works because it is;

  • Consistent. A consistent timeslot, a consistent format, a consistent length of presentation. 
  • Relevant. "Ensure that you aren’t just trying to fill the knowledge share time. Instead, really focus on what would bring value to the team. "
  • Transparent. "After the presentation ends, the work doesn’t stop. Create a space using knowledge management software for employees to access the slides after the presentation. That way, if they need a refresher, they don’t have to wait on someone else for the information. They can easily click the link to re-learn pertinent knowledge".




Tuesday, 30 June 2020

Which is the winning strategy - copying or innovating?

The question of whether innovation or copying is a more effective social learning strategy was tested a few years ago in an online tournament. The result may surprise you. 



Day 187
Originally uploaded by pasukaru76
Over a decade ago, the European Commission sponsored a research project called Cultaptation, to study the success of social learning strategies. This involved researchers from four universities in three European countries: Sweden, Italy and Scotland. It was coordinated by Stockholm University, where researchers from several departments formed a multidisciplinary “Centre for Cultural Evolution”.

The project explored social learning strategies by setting up an online tournament, with a generous proize,  to test out which strategy would be successful. The competitors were software "agents" who developed a repertoire of actions to survive in a changing landscape, and the contest looked for agents whose chosen learning strategy gave them the greatest survival rate. The learning strategies were based on variables such as the choice between

  • exploiting (continuing with actions in the current repertoire),
  • observing (learning from the behaviour of others), 
  • and innovating (trying something new).


The competition had a clear and outright winner, as shown in the plot below and described in the competition results paper.


This winner was DiscountMachine, which used the following strategy:

"Our creature does three major things: First it estimates/calculates, what we believe to be all the pertinent parameters of the simulation as well as a few other quantities that we believe to be useful.... Second it uses some of these parameters to estimate the expected payoff for performing each action in its repertoire. Once it has a best exploit chosen from its repertoire it compares the value of Exploiting to the value of Observing...... Lastly a machine learned function, takes into account N_observe and the estimates on the reliability of observing and P_c to adjust the value of Observing accordingly. Our creature then chooses whichever action has the higher perceived value, Observing or Exploiting. As a side note our creature only Innovates when it has an empty repertoire and observe doesn't work, which typically is only on the first turn of a simulation".

In other words, Discount Machine analysed carefully, all the time, whether to Exploit  (using its current best approach) or to Observe and learn from others, but it almost never Innovated.

An Article on the competition in New Scientist Magazine made the following observations:
"It seems a successful strategy rests primarily on the amount of social learning involved, with the most successful agents spending almost all their learning time observing rather than innovating"

"Avoiding spending too much time learning either socially or individually was
just as important. Between a tenth and a fifth of their life seemed to be the
optimal range. If they did more learning than that it seemed that life was just
passing them by."

"Successful strategies were also good at spacing out learning throughout the agents' lives. The winning strategy, Discount Machine, stood out because it did just this. It seems packing all your learning into the early part of your life is not a great idea - we need to keep updating our knowledge as we go along".

"You don't need any clever copying rules. You can just copy anyone at random. Other individuals are doing the filtering for you. They will have tried out a number of behaviours and they will tend to perform the ones which are reaping the highest rewards."

"To become the winner of the tournament you .... have to weigh up the relative costs and benefits of sticking with the behaviour that you have, versus inventing a new behaviour, versus copying others. That requires assessing how quickly the environment is changing, as this gives you an idea of how quickly information will become outdated".

"In variable environments (the winner) placed a higher value on more recently
acquired information and discounted older information more readily".

"Another attribute of the most successful strategies is that they are parasitic. This is the essence of social learning - somebody has to do the hard graft to find out how to do things before other people can copy them, so it only pays to learn socially when there are some innovators around. Indeed, in contests where (the winning) agents were able to invade the entire population, they actually ended up with a lower average pay-off than they did in contests where the conditions allowed some agents with more innovative strategies to survive, so providing new behaviours to copy".

Implications for Knowledge Management


For the knowledge manager, this is really useful and interesting experimental input. Given the emphasis on innovation you often see, it is good to be reminded of the value of copying as an effective competitive strategy. I remember one senior engineering manager telling me that his principle was "No Versions 1.0". He never wanted to be the guinea pig for new technology - innovation is risky, and sometimes the best strategy is to let others take the risks, and copy the survivors.

The need to adjust strategy depending on the variability of the environment is also interesting, suggesting that the variability of the knowledge context can affect the strategy needed to deal with it.

The ideal learning percentage is also an interesting statistic, also the fact that learning seems to be something that needs to happen constantly, rather than just at the start of your career.

The final learning point for me from all of this is that if we are looking at internal practices rather than competitive practices, then an organisation needs a knowledge management strategy that is strong on internal copying, leavened with a proportion of innovation.  If a team in an organisation meets a challenge, then (if they follow the DiscountMachine approach) they would look at their existing practices and compare them with practices elsewhere in the organisation.

  1. If their existing practices are as good or better, they should use the "Exploit" approach, and follow these existing practices. 
  2. If another team has a better practice, they should use the "Observe" approach, and copy the other team's practice. 
  3. Only when there is no existing knowledge that will sufficiently meet the challenge, should they use an Innovate approach.

This was the winning strategy for DiscountMachine, and it may well be the winning strategy for teams within an organisation.



Monday, 29 June 2020

4 flavours of KM - which one do you work with?

The more time I spend in the field of KM, the more I see certain brands of flavours of the field which share a common name (knowledge management) and common principles, but can use very different roles, processes and supporting technologies.


Image from wikipedia
Below are the main flavours I see, together with some of the common elements you find within their KM frameworks. Sometimes different flavours are seen in different divisions within the same organisation - Practice-flavoured KM in the project department, Product-flavoured in the Engineering department, customer-flavoured in sales and marketing. These different flavours of KM can use very different processes, technologies and roles - even within the same organisation.

Please let me know via the comments section if you have an additional flavour to add to the mix.

1. Practice-flavoured KM


This is the brand of KM which I was brought up on, in the early stages of my 28-year KM career.

This flavour of KM focuses on know-how and on practice and process improvement to support increased operational effectiveness and efficiency. You see this brand of KM in the military, the oil sector, the construction sector, charities, and other organisations focused on "doing stuff". 

Practice-flavoured KM is based around communities of practice, best practices, learning from experience, and process innovation, supported by community collaboration software, wikis and process documents such as Standard Operating Procedures.

Engineering-product-flavoured KM


This flavour of KM focuses on capturing and reproducing the expert knowledge of product design and manufacture, primarily in industries such as the car industry, the aerospace industry, defence contractors and so on. It's aim is to make expert design knowledge available, in order to increase quality and reliability in future products. It often uses knowledge-based technology to support computer-aided design.

The components of engineering-product-flavoured KM include knowledge engineers, knowledge acquisition programs (for example using the MOKA methodology), concept mapping and A3 diagrams, supported by a Knowledge Based system or expert system such as ICAD.

Document-product-flavoured KM


This flavour of KM focuses on creating knowledge-based document products to customers, primarily in areas such as the legal industry, education, aid and development, and many areas of government. It's aim is to provide the best knowledge and advice to customers and clients, through access to a wide and up-to-date knowledge base.

The components of document-product-flavoured KM include researchers and analysts, evaluation programs, library staff, and communities and networks focused on specialist areas of interest (specific client industry groupings, specialist legal advice areas and so on). Supporting technology is usually provided by excellent document and information management, and portal technology. AI and semantic search can help.

Customer-flavoured KM


This flavour of KM focuses on supplying knowledge to customer-facing staff, or even providing self-help knowledge directly to customers. It's aim is to build a strong customer base through effective customer support. You see this brand of KM in the retail sector, financial services, and media companies.

Customer-flavoured KM is based around communities of brand and communities of product, customer relationship management integrated with KM, and the development of knowledge articles within a knowledge base (of which there are many commercial examples). Chatbots can be used to support customers directly.


When seeking analogues, be aware of these different flavours, because the KM solutions do not always map across from one to another. 

Friday, 26 June 2020

What is KM governance, and why is it important?

Nowadays I talk about the four legs of the Knowledge Management table being Roles, Processes, Technologies and Governance.  But why do we need the extra leg? What is the purpose of KM governance?



I have seen many examples of organisations with what look like very good Knowledge Management systems which are not being used.

For example, they might have defined accountability for capturing knowledge from projects, they might have a defined process for lessons capture meetings, and they might have a top range lessons management system, and yet only a trickle of lessons are entering the database, and even fewer are actually re-used.


So what is missing, when a system is in place but is not used?


You could say "culture" or "behaviours" - but both of these are outcomes of something else, namely governance. To understand what else is needed, let's think about what makes people adhere to other systems at work. For example, what makes people follow the (sometimes onerous) safety procedures, or the security procedures, or the time writing procedures?

It's three factors:

  • They know they should follow the procedures
  • They know how to follow the procedures, and
  • They know if they don't follow the procedures, there will be consequences.

These three elements are the elements of governance, and apply to every management system, at work or at home. If these governance elements are in place, the behaviours will follow, and the culture will develop. If there is no governance, then KM remains an optional process, and who has time for optional activity nowadays?


To take a trivial example, if you wanted to get your teenage son or daughter to take over the task of mowing the lawn, for example, you would


  • Firstly be very clear with them what you expected them to do (and when, and how often, and to what standard), 
  • Secondly you would show them where the lawnmower is, and show them how to use it safely, and 
  • Finally you would check that they really have done that they were asked, reward good performance and not reward sub-standard performance. 


Without the clarity of expectation and explanation, they would most likely claim that they weren't sure what to do and so not do it, or else they would half-do the job, leaving the edges untrimmed and the grass clippings all over the lawn. If you don't give them the lawnmower and show them how to use it, they wouldn't be able to get started anyway, and if you didn't check up on them, the likelihood is that they might be distracted by more urgent but less important activities such as the PlayStation, or TikTok. Those three elements - clarity of expectation, the tools to do the job, and monitoring – make sure the job gets done.

We need similar governance elements for Knowledge Management to make sure the KM task gets done, despite the distraction of more urgent (though often less important) work activities. We need:



  • A set of clear corporate expectations for how knowledge will be managed in the organization (for example a KM policy), including accountabilities for the ownership of key knowledge areas, and the definition of corporate standards for Knowledge Management;
  • Training and support in the use of the Knowledge Management framework, including training in how to perform roles, how to follow KM processes, and how to use KM technology; 
  • Monitoring, measuring or auditing the application of KM, to make sure that people are delivering on their accountabilities, and applying the system in the way that they are expected to: to identify the need for new interventions to improve the KM system, and to ensure a continuous improvement in the ability of the organization to manage strategic knowledge.


That's Knowledge Management governance, and that's why we need it, because without it the chances that people will actually use your KM system are as remote as your teenager voluntarily mowing the lawn.



Contact Knoco for help in developing your own KM Governance system

Thursday, 25 June 2020

The 10 principles behind successful KM strategies

I blogged last week about the 5 basic principles behind successful Knowledge Management. Let's take that one step further, into the principles behind a KM Strategy.



When Stephanie Barnes and I wrote our book "Designing a successful KM Strategy" we included a chapter on the ten principles behind KM strategies.  These are not just principles about KM, they are principles about how KM should be introduced, so they go beyond the 5 principles in last week's blog post.

Here are our 10 principles.



1. KM implementation needs to be organisation-led; tied to organisation strategy and to specific organisation issues. This is the fundamental behind KM implementation - the number one success factor (if present) and  a common reason for failure (if absent). 



2. KM needs to be delivered where the critical knowledge lies, and where the high value decisions are made. Knowledge Management needs to focus, and to focus on business-critical or business-strategic knowledge. This might be at operator level (the operator of a plant, the driller of a deepwater well, the pilot of a passenger aircraft) or it might be at senior management level.


3. KM implementation needs to be treated as a behaviour change program. Failure to
realise this is failure reason number one for KM programs.  


4. The endgame will be to introduce a complete management framework for KM. Unlike a KM toolbox, a Knowledge Management framework is a joined-up system of roles, technologies, processes and governance. The ISO standard for KM, ISO 30401:2018, describes the framework as a "Management System".


5. This framework will need to be embedded into the organisation structures. If you don't embed it in the business, KM wont survive. KM roles need to be embedded into the organigram, processes into the high level working process, technologies into the core technology set, and governance into the organisational governance structure. Without this, Km remains separate and optional. Many of the high profile failures of KM are due to a failure to embed.



6. The framework will need to include governance if it is to be sustainable. Governance is the combination of structure, expectation, support and monitoring that any management discipline requires if it is to be applied systematically.



7. The framework will be structured, rather than emergent. I explain this here.



8. A KM implementation should be a staged process, with regular decision points. Don't rush in and try to implement KM in one go. Take your time, stage the process, and learn as you go. Treat implementation as if you were launching a start-up, and make sure you have a viable business model.



9. A KM implementation should contain a piloting stage. This is crucial both to test the framework, and to create the social proof you will need for the culture change program. This also allows agile development of the KM framework, informed throughout by user feedback.



10. A KM implementation should be run by an implementation team, reporting to a cross-organisational steering group.  In other words, just like any other change program or project!  Choose the team wisely - they have a difficult job to do.

These are our 10 principles. Many of these are embedded within ISO 30401:2018; the ISO management systems standard for KM. Numbers 1 through 7 will be satisfied if you follow the guidance within the standard. 8, 9 and 10 address the structure of the implementation rocess itself which is outside the scope of the standard. 

Wednesday, 24 June 2020

3 ways to estimate the value of lessons learned

Many organisations attempt to assign value to lessons in a lessons management system, and there are three ways you can do this. 


A screen sub-panel from the lessons management hub
showing value assigned to lessons

Assigning value to lesson-learning has three main advantages;
  • It reassures the people using the system that there is value in lesson learning. A panel on the front page of your lessons management system, such as the one shown here, reassures people logging into the system that sharing and re-using lessons is a valuable thing to do.
  • Lessons can be high-graded according to value, with the most valuable lessons getting highest priority.
  • It reassures management that there is value in lesson learning, and makes them think twice before axing the lessons management team and closing down the system.
However there are also counter-arguments;
  • Assigning value to lessons can be subjective (see below)
  • Value is yet another piece of metadata that needs to be added when documenting a lesson

If you decide to go down the path of assigning value to lessons, you can estimate this value in three ways;

  1. You estimate a projected value, where you look at the impact the lesson had on the project where the lesson was identified (measured through lost time, saved time, wasted cost, saved cost etc), and then you forecast  that forward by estimating the frequency of recurrence. Imagine a new way of working was developed which saved a project $100k on a particular activity. Imagine that activity is repeated in other projects a total of 10 times a year. If you document that new way of working as a lesson, and/or embed it into project procedures, then the projected value of that lesson is $1 million per year ($100k times 10, assuming all the future projects re-use the lesson). This of course is only an estimation - maybe the activity is repeated only 5 times, or 20 times. In some cases it might save $50k, in others $200k.
  1. You record an actual value, where the lesson is re-used (either directly, or through embedding into process) and you can then measure the improvement that results. This is more accurate than the projected value, but it sometimes can be difficult to isolate the impact of one lesson when many lessons are applied together.  The reporting is often anecdotal - "We started our project by reviewing and adopting all the lessons from the past. The project was delivered in X time/cost which is  saving of Y compared to the benchmark". This approach was used by the Ford Best Practice replication system, where manufacturing-plant contact who received a lesson needed to report what had been done with this knowledge in their local plant and, if they applied the lesson, what value it has added.
  1. You record an aggregate value, by looking at the improvement in results over time.  There are several examples on this blog of the aggregate improvement that comes through learning and re-use of knowledge, for example in Trinidad offshore platforms, Oil wells in Oman, Nuclear power stations in Korea, and jumping frogs in California.

If you can, assign value to lessons. This reassures both managers and workers that lesson-learning is a good investment of time and effort.

Tuesday, 23 June 2020

Which are the most commonly-used elements of KM governance?

As part of our three global surveys of Knowledge Management professionals in 2014, 2017 and 2020, we asked the participants to select from a list the Knowledge Management governance elements that had in place in their organisation. 

The results are shown here.  

Most of the survey respondents reported at least one element of Knowledge Management governance, with the most common being the Knowledge Management Strategy  (reported by 62% of the people who responded to this question).




Having a defined KM approach was second highest, followed by KM reference materials, to allow this approach to be followed.

It is also interesting to see a Knowledge Management policy being applied in 35% of the cases.  KM policies are quite hard to find online - but there must be a few of them out there.

Please do not think that because a governance element is low in the list, that it is not important!

 We would suggest that all these elements are important, with the exception of having a separate KM incentive system (see here for more on KM incentives). It's just that some are more commonly applied than others, often because people do not realise the value these elements bring.

The diagram below shows how the usage of these KM governance elements varies as the KM program matures from the early stages (blue), through "well in progress" (red) to fully embedded (green).


Firstly it is seems that the big difference - the biggest jump - is between the early stagers and those who are well in progress. This represents either the adoption of KM governance needed for progression, or the lack of progress of those who do not have those elements.

Those organisations where KM is embedded have an even greater application of all of the KM governance elements, the top 4 being KM strategy, Knowledge Management framework, KM training and KM reference materials. The biggest proportional difference in usage is the KM success stories, which tend to be collected as the KM initiative progresses.

At Knoco we would suggest that some of these governance elements should be developed within the first year of your KM journey, notably the strategy, the framework, the business case, the vision and the high level champion. Others such as the success stories and the network of champions in the business should be the next target, while the KM policy, training, metrics and reference are late-stage governance items.

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