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Friday, January 13, 2017

6 reasons why After Action reviews are such a great tool.

After Action reviews are one of the core tools in Knowledge Management - but what makes them so powerful?


After Action Reviews (AARs) are like the Hammer in the Knowledge Manager's toolkit - one of the most basic and most important tools.

They are applied in many organisations around the world as part of their Knowledge Management Framework.  They are focused review meetings, relatively short in duration, designed to help the team become conscious of their own knowledge, so they can act on that knowledge as work progresses. It is like "learning on Tuesday to perform better on Wednesday". In addition, the learning can be transferred to other teams, but this is generally a secondary role.

 This process was developed by the US Army, who use it as their main knowledge-gathering process. It does not go into very great analytical depth, and so is useful for reviewing short-turnaround activity, or single actions. It is short and focused enough to do on a daily basis, perhaps at the end of a meeting or at the end of a shift. After Action review consists of a face-to-face team discussion around 5 questions:


  • "What was supposed to happen'?" 
  •  "What actually happened?" 
  • "Why was there a difference?" 
  • "What have we learned?" 
  • "What will we do about it?" 

So what makes AARs so valuable? Here are 6 reasons (and you can find 6 more reasons here);


  1. AARs are a conversation about knowledge. They are not progress reviews or individual evaluations, they are conversations with the sole purpose of discussing new knowledge and new learning. The very act of holding an AAR is an acknowledgement that knowledge is important.
  2. AARs are high bandwidth.  Face to face conversation is far and away the best method to surface shared knowledge and to discuss it. 
  3. AARs are culture change agents. People find that it is possible to open up and to share knowledge in a group session, with no risk and no comeback. 
  4. AARs are instant feedback. As people share their knowledge, they can see it being transformed instantly into actions and improvements. Instead of their knowledge vanishing into a black hole, they see immediate results.
  5. AARs are quick and efficient. They can take as little as 15 or 20 minutes, but may have a big cumulative effect. 
  6. AARs lead to action and to change.  Or at least, they should do. Question 5 is the key here - "What are we going to do about it"? AARs are successful to the extent that they lead to change and to action. If they are just talking shops - if all they do is lead to bullet points on a flipchart - then they are a waste of time. AARs should be used to drive changes and improvements in the way a team, department or organisation works. 

If you can apply AARs as part of your KM Framework to regularly drive improvement and change, then you have made full use of this simple yet powerful tool. 



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Interesting enough.

"I don't think that what I do is interesting enough" is a concern often expressed when I suggest people share more on their organisation's social network about what they do. Even, perhaps especially, people at a senior level worry that the stuff that fills their days is boring.

Firstly, what feels routine and boring to them can be fascinating to others. Things that feel unimportant can be significant. Small details can reveal insights. Good descriptions and shared stories can reveal aspects of them and how they see the world that even those who work closely with them have never seen.

Secondly, if their posts really are boring, maybe they should do something about it! Part of the value of writing posts is the self reflection it affords. Holding up a mirror to our lives, revealing what we do and why. Having this discipline makes us more thoughtful, more aware of what is happening around us. If we don't like what we see we can choose to change.

These principles apply more generally. Here on the public social web much is made of the trivial nature of many of the updates people share. But they needn't be trivial. Detail can be revealing, what is routine can have meaning. Well written posts have power whatever their topic. I've always liked the phrase "intensity of the mundane" (which I think I first heard from Rob Paterson). We consistently underestimate this intensity.

The day to day needn't be insignificant. Poets know this. We could learn from them. We can be more interesting than we think if we try.



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Tuesday, January 10, 2017

The structure of a lesson in a KM system

I blogged yesterday about Garbage In, Garbage Out in KM systems, and the need to feed the system with high quality lessons. But what is a high quality lesson?


Based on a figure in the US Army handbook,
"Establishing a lesson learned program"
In this blog post I won't go into the whole quality issue, but focus on one point - the structure of a lesson; what it should contain. 

Many organisations use the After Action review process to discuss and identify lessons, or it's big brother, the Retrospect. These processes are a structured discussion and analysis of learning points, and involve discussing the following points:

  • What was expected to happen?
  • What actually happened?
  • Why was there a difference?
  • What is the learning for the future?
  • What action should we take to embed the lesson?

This logical flow ensures lessons are based on observations (particularly observations where the actual outcome deviated from the planned outcome), on insights derived from root cause analysis, on reframing the lessons as advice for the future, and on moving this advice towards action.

Lessons should be documented in the same way and following the same struture as these review processes.

Each lesson should contain:

  • A description of the intended outcome of the activity or issue being discussed;
  • A set of observations of the actual outcome, based wherever possible on ground truth, evidence an measurement;
  • Insights of the root causes behind the observations;
  • Advice for how the root causes can be tacked in future, either to repeat a positive outcome or avoid a negative outcome;
  • Actions to embed the advice in policy, process, standard operating procedures or guidance.
By using this structure, each lesson then becomes a stand-alone document which can be read and understood in isolation. 

The US Army adds a side branch to the lesson structure as shown above. There are cases where the solution to the root cause has already been implemented, and no advice for the future is needed (the advice has "already been taken". The US Army call this a Best Practice rather than a lesson. 


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Saturday, December 31, 2016

Top 10 KM blog posts of 2016

Thank you for your support for this blog in 2016 - here is a review of the year, and our Top 10 posts


Support for this blog has been steady during 2016, though with a drop in weekly readership stats around May.

 The most popular posts from 2015 are listed below. If you missed any of them, then why not have a look now!

 1. 5 points of difference between Knowledge Management and Information/Content management
Still the confusion remains between Information Management/Enterprise Content Management and Knowledge Management. This blog post describes 5 points of difference and 1 point of overlap.

 2. How a Knowledge Supermarket helps the knowledge customer to find what they need
Your knowledge base should be less like a teenagers cupboard, and more like a supermarket. This post explains how.

3. 5 steps to Knowledge Management culture change
There are 5 generic steps to go through when introducing a Knowledge management culture. These are decribed in this blog post.

4. Implementing Knowledge Management as a project
Does KM have to be a project? This blog post argues that it does.

5. How to explain the concept of a Knowledge Management Framework
We know that Knowledge Management requires a management framework, rather than a silver bullet technology. But how do we explain what a framework is?

6. Don't fix knowledge problems with information tools
Knowledge and information are not the same, so why do we try to solve Knowledge problems with Information tools?

7. Why there is no silver bullet for Knowledge Management
There is no silver bullet for Knowledge Management, because KM is a management system with many component parts, all of which need to be in place.

8. Knowledge is social, not personal
There is a school of thought that knowledge lies only in the minds of individuals. This blog posts argues that reality is both more complex than this, and more interesting.

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

10. Cutting the Knowledge Management jargon
Humans have a habit of combining concepts into "chunks". It helps us remember things more easily, but the jargon associated with "chunks" confuses people when we try to communicate, if they don't have the same set of combined concepts. This blog post attempts to de-chunk KM.

 In addition - 

The most visited post this year was an old post from 2009 entitled "What is a Lesson learned", which has had over 36,000 pageviews to date.

The 2016 post with the most "+1"s was one on the topic of The best thing to do with uncodified knowledge

The 2016 post which received the most comments, was this post on 3 questions that determine whether you need KM


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Thursday, December 22, 2016

Don't wait for knowledge to be volunteered - go ask.

One of David Snowden's principles is that "Knowledge can't be conscripted, it can only be volunteered". However waiting passively for voluntary contributions is the wrong way to populate a KM repository.


I Know The Answer!
Originally uploaded by ngader
Knowledge can't be conscripted, it can only be volunteered, and often it won't be volunteered until you ask.

This is an outsome of the problem of the Unknown Knowns. Often people don't don't realise they have learned something, until they are asked about it, or have the chance to discuss it.

Sometimes you find organisations who have set up a system whereby people are required to identify lessons or new knowledge themselves, and then to add them into a knowledge repository. I am not a huge fan of volunteer systems like this; I don't even like them for collecting innovation suggestions. I think you capture only a small proportion of the lessons this way, because people are not aware that they have learned anything, and if they are aware, they often discount the learning as "not important". Also, self-written knowledge are often superficial, because there hasn't been the depth of dialogue and questioning to get to the lesson.

I am not arguing for forcing people to share knowledge, but I am suggesting that you don't wait for the volunteers to come to you. Instead you give people scheduled facilitated conversation-based opportunities where they can become aware of what they know, and which provide a safe and encouraging environment for them to volunteer the knowledge when asked.

There are two main approaches for doing this; reactive, and scheduled.

The reactive approach requires someone to identify particular successes and failures from which to learn. The failures can be obvious, such as HSE incidents or significant project overruns, and many companies have mandatory processes for reviewing these failures. But how do you spot the successes? Maybe you can use your company benchmark metrics, and pick the best performing units for review. Perhaps you could work with the knowledge from the manufacturing plant that never had an accident, as well as from the one with frequent accidents. Maybe you can look for the best sales team, and look to learn the secrets of their success. Or maybe you can do both successes and failures - I did a very interesting study not long ago for an organisation that measures staff engagement using the Gallup survey. We picked the ten top scoring sales teams, the ten bottom scoring teams and the ten teams which had shown the most improvement over the previous year, and interviewed the team leader and a team member of each one, to pick out the secrets of successful staff engagement.

Another organisation we have worked with uses global consultants and Technical Directors to identify opportunities for learning and knowledge transfer. They travel the world, reviewing activity at different centres, and will identify good practice which needs to be repeated, as well as opportunities to learn from mistakes.

An alternative approach, common within project-based organisations, is to schedule learning reviews and knowledge exchange within the activity framework. These could be


  • After Action Reviews on a daily basis during high-intensity learning, or after each significant task 
  • Peer Assists early in each project stage, or during project set-up
  • Retrospects (or some other form of Post Project review) at the end of each project stage, or at each project review gate
  • A Knowledge Handover meeting at the end of a project, to discuss new knowledge with other projects
  • A Technical Limit meeting during the detailed planning stage, to bring in knowledge from people with detailed experience
  • A Retrospect (or some other form of review) at the end of a bid process, when the company knows if the bid has been successful or unsuccessful.


There are many advantages to the scheduled approach. Firstly, success and failure are components of every project, and if every project is reviewed, lessons may be identified which can avoid the big mistakes later on. Secondly, if lessons identification is scheduled, it becomes a clear expectation, and the company can monitor if the expectation is being met. This expectation is common in many organisations, thought the rigour with which the expectation is met seems to vary. Finally, by scheduling and facilitating the learning dialogue, you can uncover the knowledge that nobody knows they know, until they start to discuss it.

Don't rely on people volunteering their knowledge spontaneously - instead set up scheduled processes which provide a request and a context for volunteering. 


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4 Great Ways to Conduct Peer Assists: Transferring Knowledge Effectively

    In an earlier blog post  I described a framework for Knowledge Transfer and explained that the choice of knowledge transfer process differs depending upon 1) what transfer problem the organization is trying to solve, and 2) the type of knowledge (e.g. explicit, implicit or tacit) that needs to be transferred to solve that problem.

    In this post, I want to focus on one row of that frame work; “Adapting what has Screen Shot 2016-12-21 at 1.56.55 PMbeen learned in one team for team members in another context.” I use the term “adapting” in the label of that row because always what a team has learned in one situation cannot just be copied to a different context, it has to be adapted.

    Following are four examples where team members, with in-depth experience, assist a team that is facing a difficult problem. Although it is unlikely that any of these examples will fit your exact context, I’m hoping one or more will inspire some new ideas about how peers can assist each other in your organization. In each of the four examples I bold the problem the Peer Assist is addressing. Peer Assists are specifically designed to transfer tacit knowledge, so in all of the examples it is primarily tacit knowledge is being transferred, that is, knowledge that is drawn from the Assisters’ own wealth of experience in similar situations. But in several of the examples both implicit knowledge and explicit is transferred as well.  I start with a British Petroleum (BP) example that was my first introduction to Peer Assists while I was conducting research for my book, Common Knowledge.   

 

Peer Assist at British Petroleum

    Helen is the team leader for British Petroleum’s Exploration site, called Barden. The site is located in deep water in the North Sea.  Helen has four people reporting to her, two geo-physicists, a geologist, and a petroleum engineer. The team has spent several months collecting and analyzing a great deal of data about the possible well site off the coast of Norway. The team is at a point where they need to make a decision as to how they will proceed. Should they commit to a rig that would allow them to know for Image2
 sure that there is oil under the deep water at this site? Should they make firm commitments to their partners in the exploration license to protect their investment in the hoped for oil?  These are important decisions because of the money involved; sinking a rig, for example, can cost up to 200 dollars a minute!

    Helen’s team has decided it would be useful to call a Peer Assist. They wanted to bring the latest learning that has occurred at other deep water sites to the table to help them make the best possible decision. Helen and her team identify fifteen possible BP colleagues, from other parts of the world, who have experience with the kind of issues facing the Barden team. She makes the calls and finds some are too busy on other projects, but she locates six people from her original list, three from the Norway office, one from Scotland, one from South Africa and two from London. They have agreed to meet on Wednesday, one month from now, in Stavanger, Norway to spend the day. 

    On the meeting day, Helen starts by defining what her team wants from the Peer Assist. She lays out their objectives for the meeting. The Assisters have all received a packet of material to read through in advance. The walls of the conference room, where Helen’s team and the Assisters are meeting, are covered with geological pictures of the ocean bed, seismic lines, and charts. More are spread several layers deep on the tables around the room. After Helen finishes her introduction the Assisters ask some clarification questions about the objectives. Then Helen introduces Knut, the geologist, who begins to talk through the data on the wall charts, offering his interpretation of it. Before long everyone is up looking more closely at the wall data. There is a lively discussion, among all the participants, about the implications of what they are seeing.

Seismic     After a coffee break, Martin, another team member, is introduced and he begins to show the data for seismic velocity. Again, within minutes the whole group is back on their feet examining the charts.  The discussion flows back and forth with the Assisters, asking each other technical questions about the data and often challenging each other’s responses. 

    After the lunch break, Helen says that they have finished explaining the data they gathered. The Assisters return to the original objectives, asking questions for clarification in light of what they have just heard. One of Assisters notes that: “I’m uncomfortable with the discussion because there are some strategic decisions that need to be made before we can give our opinion on whether to drill the well.”  The group decides they need to develop criteria for drilling the Barden well. Collaboratively the two groups develop these criteria, gaining additional insight as they talk through each point.

    About three o’clock Helen says she would like to excuse herself and her team to give the Assist team a chance to talk through the response they want to make. As the group gets down to work on their recommendations there is an animated exchange. The member from Scotland suggests a new technique they have just developed west of the Shetlands that could provide useful additional data on a prospect like Barden. He offers to send the specifications for that process and to spend some time helping the Barden team go through it the first time.  The discussion is technical but it is very open and lively. It is obvious that the members are interested in this situation and want to be of help.

    About five o’clock the Barden team returns to hear the ideas of the Assist team. The spokesperson for the Assist team thanks the Barden team for giving them a chance to work on such an interesting problem and notes they have all learned from the exchange. A verbal report is given with the promise of a more formal written report later. As the verbal report proceeds the Barden team asks a few clarification questions, but mostly they listen to the thoughtful ideas the Assisters are providing.  When the report is finished, Helen says that the report is very clear and notes that it has given her team a great deal to think about as they move toward the decisions they must make.  She acknowledges that the Barden team was nervous about whether it was too early in their investigation to call for a Peer Assist, but she is now convinced that the timing was right, because her team can take the recommendations into account before they are fully committed to a course of action.

    The day ends with a dinner at a local restaurant. The dinner is relaxed and people have time to talk through how the Peer Assist went. The dinner is a way for the Barden team to express their gratitude to those who came to lend their knowledge. The Barden team is not obliged to take the Assisters’ recommendations and interestingly the written report will be sent only to the Barden team members, no report is sent to their bosses, because this is an assist from their peers, not a formal review.  

 

Police Crowd Safety in the EU

In Europe football matches too frequently end in death or injury to fans, often from fights and as often from trampling or suffocation in the stadium. After such a tragedy, there is sometimes an investigation by the government, which can even end in firing the police chief. But such investigations have not resulted in making events safer – they seem aimed at culpability rather than help. 

 In 2005 the Netherlands police made a suggestion to the European Union Police Cooperation Working Party (PCWP) that the police from all the EU countries begin to conduct Peer Review Evaluations in order to reduce the death or injury to football fans. This was agreed to and for three years such evaluations were conducted.  Evaluation is the wrong word in our nomenclature, because these reviews were Police in crowd conducted only at the request of the commander when a football match was to be held in his city - so I will reference them here as Peer Assists.  If requested, a team of six, made up of four police chiefs from other countries and two researchers, would travel to the city where the match would be held, arriving on the day before the match. The Host commander would have thought though a list of what observations would be helpful to him. The Host commander and the Observation team together would then make a plan for the next day. The day of the match the Observation team, in pairs, would observe and conduct interviews according to the plan. Some might observe an area where the “away team” were scheduled to exit their buses, others might observe how the fans moved in and out of the stadium stands, still others might observe the interaction at the local bars. The Observation pairs would not interfere or try to control what was happening - that was the job of the local police. The Observation pairs were there only to observe what occurred and to try to understand why it was occurring - both good and bad.

    On the day after the match the Observation team would meet to discuss what they had seen and to prepare a draft report. In the weeks following, the report would be finalized then sent to the host commander for his use.  He could share it with others or keep it private, although most choose to share it with their officers and many with the whole community. The police chiefs, who participated as observers, learned as much as the Host commander and could then implement the "best practices" in their own cities.

    These Peer Assists occurred over a three-year period; twenty in all were conducted. An EU manual on crowd safety resulted from the Peer Assists. And many of the ideas were also embedded in local police training programs. Later, the practices that were learned about crowd safety at the football matches were extended to other types of crowd events, for example, concerts, protests, and the Queen's birthday.

    While working with the Police Academy in the Netherlands, I interviewed one of the initiators of the Peer Assists at the EU. He proudly reported that there had not been a football death in the EU in the 3 years since the report had come out.  

 

Mars Inc. Sales Force

    In 2004 Mars Inc., the company known for its candy, identified a challenge in the newer markets in the developing world.  These were markets where the bulk of consumer spending occurred in small local shops, unlike the European/US model of large supermarkets.  The challenge was to achieve a step-change in the number of small retail outlets which sold Mars products in order to drive a rapid increase in sales in these markets. The challenge covered twelve markets, in which there were approximately 12 million shops, and 3.5 billion potential consumers of Mars products. The Mars Global Practice Group (GPG), which was comprised of the Sales Directors of the twelve markets, was given this challenge.

    To address the challenge the GPG met every six months, face-to-face, hosted by one of the twelve markets. The meetings were focused on sharing, learning lessons, and discussing. There were no formal presentations - numbers and details were covered outside the meetings. Instead the meetings were based around activities designed to encourage the GPG to share its lessons and to build a knowledge base of successful processes and principles.

    One day of each meeting was spent as a Peer Assist with the attendees from the other eleven markets working with the salesforce of the market in which the meeting was being held. The day began with a briefing about the local market and its structure, including learning about the top three challenges which the local business Mars store inside unit was currently facing. Then the GPG members would divide into smaller groups to spend the day with an experienced local sales associate, each group observing in local retail outlets. At the end of the day the GPG would reconvene to give detailed feedback on 1) what they saw as working well in the market, and 2) how to build on the successes they saw. They also offered their top ten ideas on how to address the challenges, based on lessons and experience learned in their own markets. In this way the Host market received positive confirmation of their success and how to build on it, plus around 30 ideas and improvement suggestions targeted at their key challenges, based on lessons from proven, practical experience elsewhere in the world.

    In the five years this network existed, sales in the small retail channel in the twelve markets trebled and the percentage profit more than doubled, adding around $250 million to the bottom line. (Milton and Lamb, the Knowledge Manager’s Handbook 2016)

 

USAID – Introducing Expert Patients into Health Facilities

            In 2011, the USAID Health Care Improvement project (HCI) in Tanzania wanted to introduce expert patients into health facilities to address patient self-management for HIV in order to shift many of the tasks from overburdened healthcare professionals. Expert patients are people living with a chronic disease who are successfully managing their disease, and who provide support and services to other patients in facilities and at the community level.

    Having not done this type of work before, the team from Tanzania decided to visit the HCI team in Uganda, who had already been working with expert patients, so that they could learn from Uganda’s experience. The team was made up of the Chief of Party, four Quality Improvement Advisors and the Knowledge Management advisor. When the team arrived in Uganda, they went with the Uganda team to a facility to discuss with the clinic staff and expert patients what they had been doing Screen Shot 2016-12-21 at 3.04.50 PM and how they made it work. They saw that the Ugandans were using expert patients as a conduit between communities, facilities, and patients and they   asked about the systems Uganda had put in place to make that happen.

    When the Tanzania team returned home, they were able to make a number of adjustments to their plans and communication tools based on the Ugandan's experience. Additionally, after the visit, the Uganda team realized they had learned more about their own work through explaining it and answering the Tanzania team’s questions. In addition, the Tanzania team showed them some patient self-management tools they had developed which the Ugandans were able to adapt for their own use.

    In August 2013, another technical exchange visit was held, this time with the team from Uganda visiting the team from Tanzania. Similar to the first visit, they went on site visits together. While on this visit there was a growing recognition that while the two countries had different health systems, there were many similarities, for example, the Ugandan team saw certain registers that could be adapted and used in Uganda to help their work. Dr. Humphrey Megere, Chief of Party in Uganda, said, “We realized that we have resources in Tanzania that we can tap into. We can call on them for help.”

    As a result of these exchange visits, the two countries started working together to develop patient self-management guidelines for health workers. Additionally, the next year when the project in Uganda was asked to begin work to improve the quality of services for orphans and vulnerable children, something Tanzania had been involved in for a number of years, the Ugandan’s called upon their neighbors to provide them with experience and guidance, for which they were happy to oblige. (Based on a report by Kate Fatta, URC 2012)

Summary

   These four examples differ in many respects. Two are corporate examples, BP and Mars; one is an international development example, Uganda/Tanzania; and one a government example, the Police Chiefs.  BP, the Police Chiefs, and Mars, all three brought together assisters from several different teams or locales, while the Uganda/Tanzania exchange was one intact team meeting with another intact team. The Police Chiefs, Mars and Tanzania examples were site visits, where observation was critical to gain an understanding of the context, while the BP example was not so much observation as it was looking at data.

    As varied as those examples are, they all follow a set of principles that make Peer Assist useful, particularly for the exchange of tacit knowledge:

  • A Peer Assist is initiated by the Receivers because they have a specific real world problem that they want help with – teams are not told to have a Peer Assist, rather they choose to do so.
  • The Receivers are in charge. They decide what help they want and who they want to receive that help from – it is their agenda.
  • Peer Assists meetings are face-to-face and usually last a day or more. The format is primarily conversation, and the knowledge that is generated is created in the exchange between the Assisters and the Receivers.
  • The Assisters are given the time to learn enough about the Receiver’s context to be able to adapt their knowledge to the new context.
  • There is mutual learning - both the Assisters and the Receivers learn and gain from the exchange.
  • What is learned does not become an evaluation of the Receivers, or a judgement - the only purpose is to assist the receivers.
  • The meeting is between two groups of team members, that is, it is not a team learning from one expert. When the two groups come together for a Peer Assist, participants who are in different roles are able to ask questions related to their own role.   

    As the Framework for Knowledge Transfer illustrates, Peer Assist is only one of many ways to transfer knowledge.  But for team to team transfer it is one of the most effective. If you try it you don’t have to call it “Peer Assist,” you can give it your own name, but the principles outlined above are useful guidance for success.



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Knowledge management matters more to you than to your organization

I gave a talk on Saturday for ChicagoLand PMI about why knowledge workers needed to develop strategies and the supporting habits and practices to manage and develop their know how across organizations and across time. If you’re interested you can find a copy of my slides on Slideshare.

Knowledge management as buzzword and practice originated in solving organizational problems. That’s where the big, obvious, problems are as well as the budgets. But the roots of the problem lie in changing nature of work and careers at the individual level.

My father worked for three organizations in his career; I’ve worked so twenty so far and the number is likely to climb. Some might argue that this reflects either a severe case of ADD or a general inability to hold a job. Regardless, the trend is real; knowledge workers will work for more organizations and have shorter tenures at each. Organizations worry about the knowledge retention problems this creates; I’m more interested in the knowledge management problems it creates for individuals. I am aware of a handful of people who are also thinking about this; Harold Jarche, Luis Suarez. If you know of others, I would love to hear about it. 

The nub of my concern is this. You cannot rely on your memory and the experience it encodes. You also can no longer rely on having access to the institutional memory and artifacts of any one organization to supplement your limited human capabilities. You ought to be thinking about and planning for how you will accumulate knowledge and expertise over time. What personal infrastructure should you be building that can travel with you? How should you adapt your work habits and practices to simultaneously deliver value to your organization and enhance the value of your personal knowledge base? What new practices and skills do you need to add to your repertoire?

The post Knowledge management matters more to you than to your organization appeared first on McGee's Musings.



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Thursday, December 15, 2016

A new focus for my blog: the new social learning

In 2005 I started this blog around communities of practice. It was a great way to investigate, learn and share my steep learning curve about communities online. I still love to work with communities (facilitate the LOSmakers), but somehow my work has become much wider.  I have been writing about many things which interest me, though mostly about learning and learning technologies. Going back to my first blogpost I became nostalgic about the clear focus I had. I decided to think through a new focus and I found it in the term: the new social learning. It is wider than communities of practice, though communities would still fit in as one of the learning interventions. I call it the new social learning (coined by Marcia Conner and Tony Bingham) not to confuse it with the fact that all learning is in fact social. It is funny when I read the book some years ago, I didn't like the term at all.

My key interest is in how the way we learn is changing because of the internet and all social technologies and which new forms of learning evolve. When I worked in Chile, Mali and Ethiopia I was basically inventing everything by myself with a few key colleagues. I used to carry certain pages from books around. I had supervisors, but they were not all very interested and even if they were interested they were only interested in the progress, but couldn't help me with all my practitioner questions. Now I am inspired by so many practitioners from all over the world.. Through the 100 blogs I read, Twitter and LinkedIn groups.

Here's a video I made in the beginning of this year interviewing people at the learning and technologies conference. Answers include - is has become self-directed: it not about what you know but about what you can find out; where, when and through what means we learn is changing; dealing with information overload become important, we can instantly find out what we need to know, and the question of whether we will even be learning if artificial intelligence can take over?


The new social learning

My questions to explore are:
1. How does the knowmadic learner think, work and reflect? and what are the new challenges? What are the differences amongst different generations?
2. What is the impact of new social technologies? What are new technologies like learning record stores and what can you do with those technologies?
3. How does learning in (online, open) networks work? Changes as a result of technological changes?
4. What are new learning interventions? Experimental or effective?
5. What are practical examples of social learning in organizations?

In short my categories will be:
  • Knowmadic learner
  • Social technologies
  • Networked learning
  • New learning interventions
  • Practical examples
Sounds very structured isn't it? I hope this will also help you to make a decision to follow my blog or not. It will give me inspiration to look with curiosity for developments I see online or experience myself. 



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Friday, December 02, 2016

Enough

"How often should I post?" is a question I am often asked. It came up again recently when I was working with a very busy chief executive who clearly saw posting on social media as a burden and I was there to encourage them to have a go.

Another question I am often asked, invariably in a judgemental tone, is "How much time do you spend on all this stuff?" to which my reply is "Enough".

Enough to build and maintain connection with other people. Enough to work out what is happening around me and in my own head. Enough to help others interested in doing the same thing.



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Thursday, December 01, 2016

How to practice storytelling while getting real work done

Twenty years ago, psychologist Anders Ericsson conducted research on what it takes to build expertise. Mere practice is not enough. If practice is all it takes to be great, taxi drivers would be the best drivers in the world. Ericsson discovered it takes a special type of practice to build better skills.

He called it deliberate practice.

Inspired by Ericsson’s research, we began incorporating deliberate practice into our story programs a few years ago. It was clear to us that merely attending a storytelling workshop was not enough for someone to change their behaviour. Sustained effort was needed, and ways of staying motivated to practice the newly acquired storytelling skills.

How to practice storytelling.
Now all our training modules include a six-month deliberate practice program, to help embed what people learn in the face-to-face elements of our sessions. It’s a mixture of online, teleconference and video coaching. We’ve seen tremendous results, but there is a particular challenge to overcome in truly embedding these new skills in a workplace.
For years, Anders Ericsson’s research could only be found in journal articles and weighty tomes such as The Cambridge Handbook of Expertise and Expert Performance. Then his work became famous thanks to Malcolm Gladwell’s 2008 book Outliers, especially the 10,000-hour rule (Gladwell penned this snappy but slightly inaccurate aphorism to remind us that it takes about 10,000 hours practice to be an expert in something).

Yet the general public only heard a small part of Ericsson’s thinking – like Gladwell, they missed some of the important features of deliberate practice.
Earlier this year, Ericsson and co-author Robert Pool brought these ideas to the public’s attention by publishing Peak: Secrets from the New Science of Expertise, which tells you what you need to do to practice deliberately.

The essential features of deliberate practice are fourfold

  • You must be motivated and willing to exert yourself to improve.
  • Practice tasks should be designed to build on pre-existing knowledge and skills.
  • You must repeat the same or similar tasks.
  • You should receive immediate and informative feedback.

 

Let’s focus on the last point. Clearly, feedback, and by extension coaching, are vital for successful practice. But the problem with most workplaces is that people rarely have time to attend practice and get feedback from a coach. So how can you find ways to practice while getting real work done?
Here’s what we suggest when we teach storytelling to sellers (something similar was mentioned in Peak). Just before a seller gives a presentation to prospects, they should share with their colleagues how they’re going to use the opportunity to practice and improve their storytelling. For example, to begin with, this might be as simple as saying, ‘I’m going to tell two stories in my presentation’.

As they progress, the seller can make their goal more challenging: ‘I’m going to make my story quite visual so the audience really feels like they’re there’.

After the presentation, the seller’s colleagues give feedback on what they liked and what could have been done better. In this way, the seller’s storytelling skills will keep improving – though only as long as they keep challenging themselves. Feeling challenged is an important indicator that learning is happening. If what you are doing is a breeze, chances are you’re not learning.

Practice storytelling and it becomes more natural

I used to teach eight-year-olds how to play basketball. For many kids, it was their first experience of the game. One vital skill they had to learn was the lay-up. The way I taught them was to get each child to stand to the right of the basket (if they were right-handed), hold the ball in their right hand and rest it against their right ear. Then I’d ask them to push the ball from their ear up into the basket. At first the kids found this difficult but very quickly they started to get it.

When they could do that, I’d get them to take a couple of steps back and then step towards the basket start with their right foot, then left foot, then shoot. When they got that, I’d ask them to repeat the drill while taking a few bounces before their steps. Pretty soon they could all do lay-ups. Each stage of the learning process felt clunky to them to start with, but before long it all felt natural.

We aim for a similar progression of learning with our storytellers. They have to be willing to feel clunky at first, knowing it will feel natural soon enough.
You won’t get better at storytelling by simply talking about it. True, stories are memorable and meaningful, and yes, they each have a beginning, a middle and an end, but discussing this is virtually useless in building the skill of storytelling.

You only get better by telling stories and getting feedback, ideally where it really matters – in the workplace.
As a sidebar, if someone purports to be a storytelling expert but they don’t tell any stories, don’t waste your time with them. If you want to know when stories are being told, check out our story spotting framework

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Friday, November 18, 2016

KM Opps, Realities & Challenges #KMWorld

KMWlogo_Stacked_Session Title and Description: KM Opps, Realities & Challenges

New opportunities, new realities, and some old challenges.

Forces transforming “knowledge” and “knowledge sharing” include globalization, the information tsunami, on-demand expectations, flexible talent models, and cognitive technologies. This is the new reality of business and the enterprise, but the strategic choices we make to deliver knowledge at the point of need are not so different and represent new opportunities to familiar challenges.  Jooste discusses cognitive  technology, how millennials are remaking organizations and may be KM’s best new hope, “reinventing failure,” stopping knowledge from walking out the door, brain science and future scenarios for KM – disruption, design thinking, indifference or

Forces transforming “knowledge” and “knowledge sharing” include globalization, the information tsunami, on-demand expectations, flexible talent models, and cognitive technologies. This is the new reality of business and the enterprise, but the strategic choices we make to deliver knowledge at the point of need are not so different and represent new opportunities to familiar challenges.  Jooste discusses cognitive  technology, how millennials are remaking organizations and may be KM’s best new hope, “reinventing failure,” stopping knowledge from walking out the door, brain science and future scenarios for KM – disruption, design thinking, indifference or appification?

Speakers: Adriaan Jooste, CKO, Deloitte Advisory

[These are my notes from the KMWorld 2016 Conference. I’m publishing them as soon as possible after the end of a session, so they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I’ve made any editorial comments, I’ve shown those in brackets.]

NOTES:

  • Experience.  “Experience is what you get when you don’t get what you want.”
  • Knowledge Management Waves and Tsunamis. KM has gone through waves — moving through one industry to another. However, now we face a tsunami in the workplace:
    • The sheer amount of information leads to cognitive overload. Cognitive overload leads us to narrowed focus, which hampers creativity.
    • Rob Cross reports that for the average worker, requests to collaborate have gone up by 80%. (This is taken from a recent Rob Cross podcast.)
    • Email is growing worse; it is not going away
    • We suffer from inefficient processes.
  • KM Disruption. How have we handled disruption? How are we handling current and potential disruptive forces?
    • moving from storytelling to books
    • moving from books to computers
    • moving from computers to websites
    • incorporating AI
    • distributing content managers around the world
    • sharing knowledge globally across international organizations
    • search — no one in the room believes that their enterprise search is within 30% as good as Google
    • mobile and tablets — only a handful of people in the room believe that their organizations have good mobile apps
    • analytics and Big Data —  no one in the room has incorporated analytics or big data in their KM efforts
    • blockchain — one or two attendees in the room are investigating this but no one in the room is using blockchain for KM.
    • flexible talent models — working with colleagues who are not always employees
    • virtual reality or augmented reality — why can’t your KM system be like Pokemon Go?
    • cognitive computing
  • Most promising Cognitive Technologies. Deloitte is working on several innovative programs using the new technologies listed below. In fact, Deloitte has won awards for using these innovative tools in one of the most conservative aspects of their business: audit. For more information on this, see the Deloitte MOOC on cognitive technologies.
    • Natural language processing
    • Computer vision
    • Machine Learning
    • Text Mining
    • Robotics
    • Speech Recognition
    • Sensing and Shaping
  • The impact of Cognitive Computing on KM. Cognitive computing will disrupt business and we will see its impact on knowledge management. Don’t be misled into believing that this is an “edge” technology. It is here and it is being used to powerful effect by market leaders.
  • Globalization. Deloitte’s clients want access to standardized services globally but they still value local creativity and responsiveness to their local context.
  • Millennials are our best hope for KM.
    • Their natural bent is toward sharing
    • They want work-life balance
    • They tend not to stay in one place long. So Deloitte focuses increases speed to competency. And then, when they move on, Deloitte has a program that treats them as “colleagues for life.”
      • Deloitte has built “Deloitte University” to train their employees — particularly their millennials.
    • They like rewards and recognition — they particularly want recognition for work well done.
    • They care about doing well by doing good.
    • They like having the latest technology.
  • KM Success depends on Behavior Change. KM has many of the same characteristics as lifestyle choices (e.g., exercising, sleeping, eating properly, etc.). You need to make the change, and hten make a commitment to sustain that change and to work continually on improving your outcomes. Success requires information, support, and feedback. Therefore, use what we know about brain science to improve the rate of behavior change.  For example, if you receive positive feedback when someone uses content you have contributed, then your brain gets a little opioid hit. This encourages you to contribute more.
  • KM and Innovation. KM should support innovation. But it isn’t just about enabling innovation more, it is really about increasing the rate of adoption of innovation.
  • KM Lessons learned at Deloitte.
    • Governance is fundamental to good KM.
    • Your KM program must be tailored to your organization’s context.
    • Invest in a formal knowledge management approach
    • Continually make the business case — daily
    • KM is an evolutionary process
    • Point solutions are a double-edged sword
    • Technology is not a panacea for KM ills
  • Moving your organization from a negative to a positive view of KM.
    • KM is “the thing that must not be named.” — if you have any KM, it is hidden within a quality or other program (e.g., six sigma, project management, etc.)
    • Active resistance — These people do not think KM is useful. These active resisters can be extremely effective missionaries once they are won over. So focus on them. And, in the process, you will learn the most and sharpen your game.
    • Passive resistance
    • Indifference
    • Benevolent neglect
    • Active support
    • Essential to organizational success and survival — this the optimum
  • Optimistic Future of KM.
    • no email
    • no website — just use apps
    • designing thinking builds knowledge into every step of every process your people do
  • The Three Pilot Rule
    • do one easy pilot so you have a quick win
    • do a tough pilot so you learn
    • do a pilot that will make senior leadership pay attention and then sign the checks you need

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Thursday, November 17, 2016

Be Agile Not Fragile #KMWorld

KMWlogo_Stacked_Session Description: To be agile in knowledge management, and to innovate, Garfield suggests the following principles: identify three key business objectives, focus more on helping people use processes effectively, improve decisions, actions, and learning, connect people to each other so they can help each other at the time of need, implement, improve, and iterate. To avoid being fragile, steer clear of these traps: maturity models, best practices, metrics for the sake of metrics, certification, tool rollout and adoption, personality tests, corporate speak and more! Sure to spark an interesting discussion so don’t miss this session.

Speaker: Stan Garfield, Knowledge Manager, Author Implementing a Successful KM Programme; Founder, SIKM Leaders Community

[These are my notes from the KMWorld 2016 Conference. I’m publishing them as soon as possible after the end of a session, so they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I’ve made any editorial comments, I’ve shown those in brackets.]

NOTES:

  • Fragile things typically are:
    • Large
    • Overly optimized — they are too smart for their own good; they are obsessed with standardization and efficiency
      • this works if everything goes according to plan
      • BUT things rarely go exactly according to plan — Randomness is the Rule (not the exception) — in the face of random errors or problems, the fragile system cannot cope with the variability
    • Brittle — they don’t have the innate ability to fend off stress
  • Fragilistas:  these are people who try to eliminate volatility.
    • Helicopter parents try to make life as safe as possible for their children but in the process they deprive their children of the ability to learn how to cope with variability and randomness.
  • How to avoid becoming a Fragilista? Avoid these behaviors
    • Maturity models and benchmarking: it’s good to learn from others but don’t try to conform to a rigid model.
      • Seth Godin: “Benchmarking against the universe actually encourages us to be mediocre, to be average, to just do what everyone else is doing.”
    • Best Practices suggest that the ideal has been achieved. Rather it’s better to look for (and then adapt for your context) “proven practices” that fit your environment.
    • Metrics for the sake of metrics — avoid tracking every random thing. Make sure there is a business reason for tracking something.
    • Certification — taking a one-week class in KM is not enough to be a KM expert. Focus on learning not on certification.
    • Tool Rollout and Adoption — don’t fixate on rolling out tools and then “driving” adoption. The better approach is to start with understanding the needs of the organization rather than finding a use for the tool you have purchased.
    • Personality Tests — each person is unique, not an oversimplified archetype. Why do we need this categorization? What is the practical use?
    • Corporate Speak — don’t use buzzwords, insider jargon, or corporate lingo. Refuse to use them —  use words and expressions that are widely understood if your intent is to communicate clearly.
    • Do as I say, not as I do — you must practice what you preach.  Your senior management must lead by example. (And the KM team must lead by example too.) People will closely observe the actions of leaders and mimic them. Therefore, model the desired behaviors.
    • Secrecy — don’t give lip service to transparency while continuing to operate in a closed manner. Communicate frequently, truthfully, and openly.
    • Mediocracy — man organizations have leaders have little (if any) talent and skill who nevertheless are dominant and highly influential. Leaders should serve their people and  treat them with respect.
  • Unfragile behaviors
    • people can’t find information
    • People are reluctant to ask for help in public
    • organizations want to push information out
  • How to Move from fragile to agile?
    • Make content easy to find
      • let users tag content to indicate “I reused this document” or “I found this document helpful”
      • figure out what documents are most important to your organization and force those to the top of the search results
    • Assist people when they ask for help
      • make it easy to figure out where to ask a question
      • train people to ask questions in community spaces
    • Use the power of pull
      • don’t force content on others
      • make your content/tool so attractive that people are eager to opt in
  • What would a “self-healing” KM system look like? (Question from Christian de Nef)
    • Simplicity
    • Mobility — easy to switch from one platform to another
    • Knowledge systems that do not rely on technology

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