conversation matters

How to Increase the Flow of Knowledge Across an Organization

The most effective way you can increase the flow of knowledge across an organization is to connect  organizational members to each other.

By connect I mean, “I know what you are currently working on and what problems you are facing” and you know that about me. It means, if I need help, I know what questions I might be able to ask you about. I also know how I might be able to help you, for example, when I come across something I know you are interested in. 

I’ll give you a personal example. I have a good friend - we both like reading mysteries. I recently came across a great site. Here is how it works, if I type in the name of an author I like, the app generates a map of other authors that people, who also like that author I typed in, regularly read! I quickly sent my friend a link to the map.

You have to know what another person is interested in, to know what to share with them.

Connected also means there is a sense of trust between us, so that I know you will respond if I ask for help and that you won’t think less of me for not knowing the answer. The two main reasons employees give for not asking for help is 1) they don't want to bother the other, imagining they are too busy and will be irritated by the request, or 2) they don't want others to think they are not competent! Both reasons are less relevant when employees are connected because asking and sharing are ways to maintain the connection between people. It signals, I am aware of you and am interested in your success. 

The short way to think of the strategy I am suggesting is, Connection before Content, that is, before you can exchange content productively, you need to have built a connection.

That is true at several levels in an organization. For example, at the level of a project team.  Hackman, who is probably our greatest authority on teamwork, explains that before a project begins, the leader needs to bring the team members together – in person, when that is again possible. Hackman suggests pairing up team members and asking each to write out what they think the goal of the project is and then discuss what they wrote with each other, in order to come to some kind of agreement. Secondly, he has each one of the pair interview the other about what experience they bring to the project that will help the team reach their agreed upon goal. And finally he has each person introduce their partner to the rest of the team, explaining what skills and experience their partner brings. Team members need to know who has what knowledge if they are going to to make the best use of the team’s resources to solve problems.  Connection before content.

It is equally true at the department level, where again each member needs to know both the tasks and the experience of their colleagues to work most effectively. One way department members can gain that knowledge is to start department meetings with a "check in" during which each members reports on what they are currently working on. That allows others to offer help, as well as, to coordinate. You may recognize this as an Agile practice of holding 15 minute morning meetings. Connection before content.

And it is true for a community, where there are lots of ways to build connections, e.g. “working out loud circles,” Communities of Practice, having robust profiles up, brown bag lunches, your department offering fresh coffee and donuts at 10 each morning for any department they need to stay connected with.  Connection before content.

As we all know, relationships deteriorate over time if they are not renewed. So even if a group has met before, taking a few minutes before a meeting to reconnect reestablishes the relationships and trust that increases knowledge flow.

I realize that these examples raise the concern that one-to-one is a slow way to proceed and that we should be thinking about how to scale knowledge. But if every employee is engaged in one-to-one exchanges, then the whole organization is learning. Moreover, they are getting knowledge that pertains directly to their work, not something that they might possibly need to know sometime in the future.

The idea that you can scale knowledge sharing by posting something that everyone in the organization will learn from is a bit of an illusion, as The World Bank found out when they studied readership in 2014. The published report examined how frequently posted policy reports were downloaded or cited - not just by the 10,000 bank employees, but by everyone. About 13 percent of policy reports were downloaded at least 250 times while more than 31 percent of policy reports were never downloaded and almost 87 percent of policy reports were never cited. (Which World Bank Reports are Widely Read, Doerte Doemeland and James Trevino, 2014)  Those numbers suggest that we should question the value of relying solely on publishing to share the organization's knowledge.

That said, every company needs to publish explicit knowledge like policies, SoPs, processes, etc. But if a company wants knowledge to reach employees when they need it, they need to focus on Connection before Content.  

KM Metaphors that Could Expand Our Practice

Lately, I’ve been reading Schön (1979) about the power of generative metaphors. He views metaphors “as the basis for how we make sense of the world. In his view, metaphors serve our understanding of the world by drawing out similarities, and assigning meanings to a situation by making connections.”

The seminal work on metaphor is Lakoff and Johnson’s Metaphors We Live By. I remember reading it in college, and its impactful ideas have stuck with me ever since. Lakoff and Johnson explain that metaphors guide much of our thinking in ways of which we are often totally unaware.  “The essence of a metaphor is understanding and experiencing one kind of thing in terms of another.” They use the example of the common metaphor, argument is war. We are all very aware that an argument and a war are different things.  Nevertheless, we structure, understand and talk about argument in terms of war:  

• He attacked every point in my argument.
• I’ve never won an argument with him.
• His criticisms were right on target.
• You disagree? Okay shoot.
• If you use that strategy, he will wipe you out.

Applying the terms of war to argument influences how we think about arguing and even how we act when in an argument. For example, we attempt to win, rather than focusing on understanding the other’s perspective. Thus the metaphor argument as war influences how we engage with one another. Lakoff and Johnson argue that a metaphor is not just a choice of words; it is how we think. Metaphors are useful to us to construct and explain our ideas, but at the same time, they limit us. For example, using the metaphor, argument as war, blinds us to the possibility that there is another way to engage those with whom we disagree. (see the Public Conversation Project on how to talk with someone on the other side of an issue or Better Angels on how Reds and Blues can interact with each other.)

Schön provides this organizational example, “if we say that an organization is fragmented then it follows that what is needed is more integration. But a fragmented organization might be seen, alternatively, as composed of ‘semi-autonomous units.’” By employing the metaphor of fragmentation, a tacit image arises of the organization as something broken, something that once was whole and needs to be made whole again. Schön argues that by becoming aware of the metaphors we use, “we can do a better job of problem setting, which can make people in organizations perform creative leaps into seeing old problems in new ways.” 

Re-reading the literature on metaphor led me to think about the metaphors we use for knowledge management. KM professionals primarily use the metaphor knowledge is an object. Regarding knowledge as an object implies that those objects, much like books in a library, can be collected and stored where others can find them and can take what they need when they need it. The knowledge as an object metaphor has resulted in KM setting up repositories, lessons learned sites and wikis – the modern forms of libraries.

One of the most prominent KM practices is the idea of sharing those important objects across the organization. Knowledge sharing is often depicted in graphic form as an object in one person’s head with lines drawn to the head of another. Sharing itself is a metaphor and a positive one. It seems like something we all ought to do. After all, we were taught as children to share our objects, such as toys, treats, pets. And indeed, the sharing metaphor has been useful to KM in that it prompted us to set up CoPs, where participants could easily learn what practices others employ as well as what tools they use.

Although undoubtedly helpful, the metaphor of knowledge as an object has also limited how we implement KM. It has resulted in KM primarily focusing on existing knowledge that can be collected and shared, but it has made us blind to the critical knowledge that Leonard calls “deep smarts” or Polanyi called tacit knowledge; knowledge that cannot be transmitted through a quick response to a CoP question or in an online document. It also results in us not taking into account the fluidity of knowledge, that is, that what we “know” is continually growing and changing within our minds, as well as within our teams and organizations. (see my post on Transferring Expertise)  

We could add to the metaphors we use to think about knowledge; seeing knowledge not as an object, but as construction, something that is continually assembled and reassembled within the mind of individuals based on input from their own experience, what they read and what they hear and see from others. If one of our metaphors were knowledge as construction, then we would encourage greater focus on individual reflection and on teams coming together to learn from their actions jointly. We would increase the interaction of employees across internal boundaries. We  would emphasize ways to bring people together to assemble new knowledge collectively – not just brainstorm (another metaphor) but to build further understanding of a situation or a problem, perhaps to jointly reframe an issue. The metaphor of knowledge as construction would give us a whole new vocabulary we would think about building, producing, assembling, reassembling, creating and  reframing knowledge rather than just collecting and sharing existing knowledge.

As KM professionals, we have inherited the KM metaphor of knowledge as an object from the past. If we now want to grow KM to be more relevant to the complexity that organizations face, we need to both become aware of the metaphors that we are currently using, and think clearly about the metaphors we could use to expand the role of knowledge management. 

 

SharePoint Can’t Learn

I am just back from KM World and was amazed that so many of the presentations were about how some organization has implemented SharePoint.  SharePoint has become so ubiquitous that, at KM World, Knowledge Management seems to have become equated with implementing SharePoint repositories and communities!

I want to push back a little on that. Learning in an organization happens when teams or workgroups take the time to think together about what is occurring within their purview and then to consider what needs to be changed or strengthened – when they have human-to-human conversations aimed at improving their own work. Only after they have reflected together and figured out what they need to do next, is it useful to seek out the ideas of others. A document in a SharePoint repository or a question/response on a community forum can certainly spur the imaginations of team members about what might be possible. But help is most useful when a team has identified a problem. Without the first step of reflecting on what is needed, documents are just “nice to know.” A document in a repository is not knowledge any more than a book on a shelf is knowledge. Knowledge is created and resides in the minds of human beings.

Even when a document in a repository is a good match for a team’s need, a second kind of human-to-human conversation is required for learning to take place. A team does not learn from reading a document about what some other team has done. The successes of others have to be translated to fit the tasks and culture of the receiver’s environment. Copy and replace never works!  When the receivers of new ideas function within a context that is different from the one the document was written about, translation is required.

Although the receiving team can do some translation on its own, they lack the knowledge of the reasoning behind the actions of the other team, for example, what they tried that did not work, what they thought about but did not execute on and why. There is so much more a team knows than they can put in a written in a document or an online response to a question. (We know more than we can write!) Translation is most effective when it is a conversation between those that wrote the document and those that want to use that knowledge. Through conversation the receiving team can learn what conditions made the other's success possible, for example, the level of team experience, size of the team, management support, time frame, and culture. Human-to-human dialogue is invaluable in figuring out how to modify what the originating team did so that it could work in a different environment. Joint translation is a learning process that significantly benefits the receiving team. But, as often, it is also learning for the originating team because in explaining what they did, they come to a more complete understanding of their own work.

At the next KM World, it would be great to hear presentations on how teams figured out what they learned from a project and how they thought through what changes they needed to make on the next project, based on that learning; how often they reflected on what they were learning and who they involved in those discussions; in what ways those reflections changed the way that they worked.  It would be great if KMer’s focused on innovations in learning from experience, rather than just getting reports into SharePoint. It would be great to find out how a team talked through what they hope to learn on the next project, as well as the outcome they wanted to achieve. That way they could continually improve their work processes and get better at what they were doing.  It seems like we have become so focused on “sharing” that we have forgotten that KM is primarily about learning.   SharePoint Can’t Learn, only humans can.

Three Books Every KM Professional Should Read

Much of the very helpful research and theory that under lies our field of KM is produced in the related disciplines of Organization Behavior, Organization Learning, Group Dynamics, Computer Science, and Organizational Psychology.  Following are summaries of three such, highly acclaimed, books that have recently been published.  They are:

• Teaming: How Organizations Learn, Innovate, and Compete in the Knowledge Economy, 2012, by Amy Edmondson, a Harvard Professor of Organizational Learning.

• Critical Knowledge Transfer: Tools for Managing Your Company’s Deep Smarts, 2015, by Dorothy Leonard, Walter Swat, and Gavin Barton. Dorothy Leonard is Professor Emeritus at Harvard Business School.

• Social Physics: How Good Ideas Spread: The Lessons From A New Science, 2014, by Alex Pentland, Director of MIT’s Human Dynamics Laboratory and the MIT Media Lab Entrepreneurship Program.

Teaming

Edmondson’s book, Teaming is one of the best knowledge management books I’ve read, although I don’t think she ever mentions the term knowledge management in the book. The book is not limited to teams, rather she uses the term “teaming” as a verb, to talk about a way of organizational functioning. The major take-away from the book is that an organization needs to move from focusing on “organizing to execute” to “execution as learning”. To do this employees must make use of learning behaviors, such as, asking for help from other members, discussing differences of opinion openly rather than privately or outside the group, revealing their own errors to the group, and several more.  The organization must provide the routines (opportunities) during which employees can use those behaviors.  Those routines vary with each organization described in the book, but examples included retrospects, planning meetings, soliciting feedback from customers, strategic conversations, and surgical team meetings that occur before an operation.  Edmondson clarifies that team members will only exhibit learning behaviors when they feel psychologically safe and explains in detail how psychologically safety comes about. The book is rich with examples of teaming, including the Beijing Olympics, Children’s Hospital and Clinics in Minneapolis, NASA’s space shuttle program, Intermountain Health Care, and many others. The book also includes findings from Edmondson’s own research much of which has been conducted in health care venues. It is a must read for anyone serious about helping an organization learn. 

Critical Knowledge Transfer

In her book, Leonard is not addressing the transfer of all knowledge in an organization, rather she is focused on “critical knowledge,” expertise that is largely undocumented and is in the heads of employees, particularly employees considered experts who have vital knowledge that is likely to leak out of the organization during transitions. Leonard categorizes knowledge into three levels, explicit, implicit and tacit, explaining that each must be transferred differently. This book is primarily about the last two.

Explicit knowledge can be transferred through written documents and community Q&A.

Implicit knowledge is that knowledge which an expert can articulate, but only with the help of skillful elicitation techniques. Those techniques require training and experience to develop.

Tacit knowledge, that which even an expert may not be aware of, is transferred through the learner’s observation of an expert, followed by supervised practice and coaching. Leonard calls this process OPPTY (for Observation, Practice, Partnering and joint problem solving, and Taking responsibility). She explains that OPPTY works best when knowledge is transferred, not to novices, but to “near experts”.

The book has advice for managers in terms of how to determine what knowledge is critical to transfer. Leonard says, “First you have to be confident that you understand what know-how, skills, and other capabilities underlie your company’s success.”  She devotes three chapters to the various techniques to elicit and capture knowledge, make sense of it, and then massage it into a form that can be transferred, with lists of knowledge elicitation questions for each. This is an in-depth look at knowledge transfer from one the great experts on the topic.

Social Physics

Pentland describes social physics as “a quantitative social science that describes reliable, mathematical connections between information and ideas on the one hand, and people’s behavior on the other.’ He builds on Bandura’s theory of social learning, “the fundamental assumption that learning from examples of other people’s behavior (and the relevant contextual feature) is a major and likely dominant mechanism of behavior change in humans.”

Pentland found that he can study patterns of information exchange in a social network without any knowledge of the actual content being exchanged, and using that data, can predict how effective a network is, whether a small team or a large organization. The data is gathered by means of mobile sensors, embedded in badges that employees wear. The sensors can track where employees go, how long they are there, even the tone of the conversation – but not the conversation itself. In one such study Pentland found that 50% of the variation in performance across groups and tasks can be explained by:

• The large number of ideas: many very short contributions rather than a few long ones.
• Dense interactions: continuous, overlapping cycling between making contributions and very short (less than one second) responsive comments (such as, “good,” “that’s right,” “what?” etc.) that serve to validate or invalidate the ideas and build consensus.
• Diversity of ideas: everyone within a group contributing ideas and reactions, with similar levels of turn taking among participants.”

And 35% of the variation in a team’s performance can be accounted for by the number of face-to-face exchanges among team members. From Pentland’s research, he concludes: 

• It is not simply the brightest who have the best ideas; it is those who are best at harvesting ideas from others.
• It is not only the most determined who drive change; it is those who most fully engage with like-minded people.
• It is not wealth or prestige that best motivates people; it is respect and help from peers.

He concludes that leaders need to focus on changing the connections between people rather than focusing on getting individual people to change their behavior.  His findings are ideas that KM has been saying all along, but Pentland has the data to prove it. This book provides evidence that being in relationship with others in a team or organization improves the flow of knowledge.

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 been 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
 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.

    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 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 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 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.

Knowledge Transfer: When to Use What Method

Transferring knowledge from one part of the organization to another is at the heart of knowledge management. But a general call to encourage more knowledge sharing or transfer is not very effective because there are many ways to transfer knowledge. You need to be sure that you are investing in the best method for what you want to accomplish. There are two questions that influence the choice of method.  

1. What is the transfer problem you are trying to solve? For example, do you want to:

•     transfer the knowledge that has been learned in one project to other projects?
•     transfer the knowledge of a retiring expert to his/her successor?
•     transfer the knowledge gained from a critical event, such as the loss of a contract?

2. What type of knowledge do you want to transfer?

• Explicit – is “know what,” the facts and algorithms that can be written down so others can both understand and make use of the knowledge. Examples are SOPs, job aids, and well-documented process steps.
• Implicit – is ‘know how” A professor or a book can teach you the “know what,” but “know how” is learned through experience. A skilled interviewer can ask the right questions to make the “know how,” that is in someone’s head, explicit enough that others could use it, for example, the rules of thumb the person uses, insights about a difficult client, short cuts to use in fixing a troublesome machine, etc.
• Tacit – is deep knowledge, what a person knows, but often can not articulate; it is what is often referred to as judgment.  Tacit knowledge can only be learned through observation of a master or being coached by a master. Examples of tacit knowledge are, what makes one speaker engaging and another less so, how a conductor acts to get the best from an orchestra, what a skilled facilitator does to help a group reach agreement.

Attached is a abbreviated version of a Knowledge Transfer Framework I have built for working with my own clients. It starts in Column 1 with a list of knowledge transfer needs that I frequently hear from clients. Column 2 lists the type of knowledge associated with each need. Column 3 outlines how that type of knowledge can be harvested and Column 4 outlines how it can be transferred to others.

Harvesting knowledge is only the first step in knowledge transfer. Once it is harvested there must still be a process in place to make it available to those that need it. An if it is tacit knowledge there needs to be an additional process to assist those that need it to internalize it.  However, in the most efficient and well designed transfer processes, harvesting, making available, and internalizing can occur simultaneously.

 

 

 

 

 

 

 

 

 

Think Knowledge Innovation Instead Of Knowledge Transfer

The African Rice Center* has been very successful in transferring knowledge about how to process rice in a way that makes it more nutritious and has less breakage. In a study conducted in Benin, 92% of the 600 women farmers took up a new process for parboiling rice. That is an amazing percentage for the transfer of knowledge. But the real story is the remarkable way they accomplished the transfer.

I should note that in Benin parboiling rice is a major economic activity and generates income for women and girls. So an improvement in the process can result in a significant economic gain for women farmers.

The traditional method women farmers used to prepare the rice, was to soak the rice (paddy) for 12 hours, then drain and cook it in a small amount of water in the bottom of the pot. Unfortunately that allowed the paddy at the top to not be entirely steamed while the paddy at the bottom would be completely cooked. After cooking they then dried the paddy on the ground in the sun for some days. This traditional process resulted in an uneven product to mill and was often mixed with sand and stone from lying on the ground.  Consequentially the rice was harder to cook and brought in less money when sold than would more evenly steamed rice, that had been dried with a different technique.  

The African Rice Center had been using a conventional way to spread new agricultural practices, which was to teach farmer women to adopt a ready-made research output. And that is how they initially taught women farmers to parboil rice, using a ready-made perforated aluminum pot. To learn, the
women farmers came to the Center for a two-day community workshop during which experts from four local NGOs demonstrated how to parboil the rice using the perforated pot, as well as, learning techniques for washing and drying the rice. The typical uptake of that training was about 18%, which isn’t bad, but the African Rice Center knew that it was too slow to reach all the women farmers who could benefit from the better practices taught in the workshop.

The Transfer Story

The African Rice Center decided to try video to transfer the knowledge, thinking video could be easily distributed to more people. But they didn’t just make a video of the training they had been doing. Instead they developed the video using a participatory method they called Zooming-in and Zooming-out.

Zooming–in started with visiting communities where they listened to the learning needs of villagers. They especially paid attention to the words people used when talking about parboiling rice. They searched among the communities for local innovations in parboiling rice. Then rural men and women played an active role in identifying the ideas and principles that would be in the video and in preparing the video script. Finally the Center made a draft video showing the women farmers using their own innovations and describing what they were doing.

Zooming-out was about showing the draft video to more communities, which spurred even more innovations, which were then also incorporated into the video. The Center was also able to modify places in the draft video where the ideas were not clear. The video was then ready to be viewed.  Over time the video was translated into twenty African languages and was shown throughout central Benin in many different age meetings and markets, and was also distributed through partners of the National Agricultural Research Center.

 

After a period of two years, the Center conducted a study to assess how effective the video had been in transferring this improvement. The study included 600 women farmers in central Benin, that were divided into five categories, based on the extent of their exposure to the new way of parboiling rice; 1) those who only had the conventional training, 2) those who only saw the video, 3) those who saw the video and had the conventional training, 4) friends and neighbors who had neither training, but were able to observe what others were doing, and 5) those who had no new information about how to parboil rice.

The following chart shows the percent of women who changed their practice and innovated a way to parboil rice using local materials, as well as those who took up the associated practices (click on the chart to make it bigger) 

As I read about this amazing result, I puzzled about why it was so successful and I drew several conclusions - you will probably think of several more and I'd be interested in your thinking.

The data in row 3 show that watching the video increased the probability that the women farmers would innovate a solution for parboiling the rice, over the conventional training. The same is true in row four, reducing vapor loss by stuffing a cloth between the two containers. Video appears to stimulate more innovation that conventional training. 

• One possible explanation is that the video gave the women farmers an understanding of the principle behind how to parboil the rice with steam, which the conventional training did not convey. Understanding the principle made it possible for the women farmers then to use local materials to innovate a way to prevent the rice from touching the water, for example a pot with sticks in the bottom. 

• Another possible explanation is that seeing women like themselves in the video, rather than observing NGO workers, or males in the conventional training, made it seem to the women more likely that they could figure out how to parboil their rice without the cost of buying a perforated pot.

• The data also suggest that new users may understand a principle better if they can see the principle in action, rather than just hearing or reading about it.

• If those conclusions are correct, then the video was effective because it lead to innovation, not because those who viewed it copied exactly what was shown in the video.

• That conclusion is supported by the data in rows one and two of the chart, “removing dirt from the rice” and “washing rice two and three times.” Both practices were nearly as effective by conventional training as by video. I conclude that was because no innovation was necessary to add these steps to the traditional practice of the rice preparation.

These conclusions can be generalized to other situations in which knowledge needs to be transferred, because nearly always a practice has to be modified to fit a different context. Too often what is said (or thought) by those that are being asked to take up the knowledge is, “We are not like them, so it won’t work here.” And they are not to be disparaged for such thinking - they are right, it will not work as it is presented. 

1. Understanding the principle behind a practice is critical for the necessary innovation of the practice to occur.
2. All too often the principle is not clear, even to those who are presenting the practice to others. For example, it would be easy to mistake the practice of rice processing as being about having a perforated pot and tarpaulins on which to dry the rice.  There is an inclination in most presentations of successful processes to describe the practice as "what we did." 
3. New users are more likely to borrow a practice from others if they are able to identify with the others. The video depicted people “like self” which the conventional training did not.

*Espe ́rance Zossou, Paul Van Mele, Simplice D. Vodouhe,and Jonas Wanvoeke, The power of video to trigger innovation: rice processing in central Benin, International Journal of Agricultural Sustainability 7(2) 2009, Pages 119–129

Pay it Forward: Making the Transfer of Knowledge More Effective in Developing Countries

I want to propose what may seem to some a radical goal for the international development agenda: The most impactful way for knowledge to serve development is for every successful, local, intervention to “Pay it Forward” to another facility or region. For example a team of originators in a region that has reduced HIV, “Pays it Forward” by taking what it has learned to another region to help that region accomplish what the originating team has learned to do. A city that has successfully reduced E.coli in its water “Pays it Forward” by sending a team of originators to a sister city where the water is still causing disease.

The current way knowledge transfer (or spread as it is often called) is attempted is that the funder (e.g. the agency, foundation, NGO) of the intervention, builds into the contract, that those providing the technical assistance to the originators have the responsibility for spreading the intervention after it has shown to be successful. 

But that practice is flawed for two reasons. First, technical assisters typically obtain the knowledge of what happened through interviews. Interviewers can obtain the explicit knowledge of the originators, but
much of what the originators will have learned while doing the implementation is tacit, which by definition, the originators are unable to articulate.  Tacit knowledge is available when the person who holds that knowledge is embedded within a context where the knowledge is needed. Secondly, using the technical assisters to transfer the knowledge takes the success away from the originators and makes it the success of those that provided the technical assistance. “Paying it Forward,” as described above, acknowledges the success of the originators. The originators, being present in the new situation, can transfer both their explicit and their tacit knowledge to others. Calling on their tacit knowledge they can make adaptations to the new context.  Moreover, the act of calling on their tacit knowledge, strengthens and sustains that knowledge within the originators. “We learn when we teach.”

Agencies, foundations and NGOs can support “Paying it Forward” by providing the funding to pay for the time and travel of the originators to work with another facility or region. And technical assisters can help by identify sites that need the knowledge the originators have gained. 

There is a lot of talk a lot about South-to-South, but it is not South-to-South as long as the technical assisters take on the task of transfer. It is empowering when implementers put down the role of helpee and take up the helper role.

We actually already know a great deal about how to “Pay it Forward” from regions that have twinned or groups who have conducted peer assists and site visits across regions and countries.  We have learned through the example of Positive Deviance, as well, that those embedded in the problem are best able to transfer the knowledge gained. 

Technical Assisters are necessary to bring evidence based practice, to facilities and regions, but they have proven to be poor at transferring how that practice was implemented. Transfer remains the biggest challenge improvement projects face. The answer is to quit attempting to spread something that technical assisters can’t know enough about, rather to provide the financial support for those that accomplished the intervention to spread it.

How to Grow a Knowledge Sharing Culture

How to grow a knowledge sharing culture – a culture where people expect to share their knowledge with others and willingly ask others for help when they need it. In other words, a culture of generalized reciprocity – that wonderful term that means we help another without expecting a direct return from that person, but with confidence that others will help us when we have the need.

If you are a startup- you probably had that culture from the beginning. The really difficult question is how to turn a culture around when the existing norm is, “I’m too busy looking out for myself to worry about others”

I can start to answer that question by saying what doesn’t work; mandating sharing, relying on slogans, bribing rewarding employees with points or dollars for sharing, a performance review that says you must have X number of posts or contributions. I get asked the culture question a lot by managers that have already tried and failed with all of the above.

The answer is found in the term “grow.” What is being grown is an internalized belief, “that we are all better off if we help each other.” The way people come to that belief is to experience it. A cultural grows over time- so the necessary action is to continually create opportunities where organizational members can experience a culture where they are better off because they are all helping each other.

The simplest way to do that is that every time there is a meeting, conference, retreat, or even a dinner, take the opportunity to hold a brief knowledge sharing exchange. It can be as simple as going around the table at the beginning of a meeting and asking each person to spend two minutes saying what they need help with, or talking about something new they think might be of use to others. Call it “Gives and Takes.” Or use one of my favorite ways, speed consulting, or a round of story circles, or reciprocity circles.  

The knowledge sharing can take as little as 15 minutes or if it is a daylong meeting it would be worth spending an hour. But for whatever time period, everybody in the room is in a temporary culture where they are learning with and from each other. I’m not talking icebreakers, I’m talking about creating a design where people get real help on an issue that is important to them. Maybe they don’t learn all they need to know in that brief period, but the offer is made and accepted.

We only learn how to function within any culture by experiencing it. You can read a description about the culture of China or Costa Rico, but to understand it you have to be in it. So in an organization, take every opportunity that presents itself to have everybody in the room experience getting help from others. When that kind of experience occurs, people begin to think to themselves, “Hey these people are a lot like me, same issues, same concerns,” or “I’m going to buy that guy a cup of coffee so I can find out more about what how he is doing that.”

Creating the experience one time isn’t nearly enough – but if you continually put people in a temporary culture of knowledge sharing, the culture will change!  

Stay tuned for more ways to create a knowledge sharing culture. Next time I’m going to write about how to build a knowledge sharing culture through the practices of the third era of KM, e.g. collective sensemaking and Working Out Loud. And after that about implementing a different kind of training that creates a culture of reciprocity.

But the simplest to implement is the one I’ve written about here - starting every meeting with knowledge sharing whether it’s a team meeting, project meeting, staff meeting, or department meeting. If there are too many people then divide them up into smaller groups and do the same thing. Starting a meeting this way sends the message loud and clear, “knowledge sharing is critical to our business.”

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Transferring Expertise: The Best Way to Move Tacit Knowledge

One of the really tough nuts to crack in KM has been how to transfer the knowledge of experts to those less skilled. Organizations have made a lot of attempts. One of the early attempts was made by the World Bank, who video-taped (this was very early when it really was tape) interviews with experts from around the world, for example, a very experienced road construction engineer in Pakistan or a long-time education expert in Brazil. The Bank ended up with an impressive video library, which unfortunately, very few people ever bothered to look at. I’ve seen organizations conduct lengthy exit interviews with retiring experts, as well as, engaging in more scientific attempts to identify and then get down on paper, (or a mind map) that 10% of an expert’s experience which made that expert extraordinary. You probably have your own stories of failed attempts, lists of Best Practices, cases, banks of stories….

Even given a long history failed attempts to "capture" expertise, we just can’t seem to get past this idea that an expert’s mind is like a filing cabinet where we can just wisk out a file and hand it over to someone else.

If we are going to crack this nut, we need a better image – a more accurate way to think about how experts create and store the knowledge they use. A more accurate image would then allow us to think of better ways to transfer that knowledge to others.

The image I have found most useful is to think of an expert’s mind as a box of Lego pieces. That image rings true because neuroscience tells us that experts, as well as  the rest of us, store what we learn, not as lessons or answers, but as fragments or bits and pieces located throughout our minds. The expert has accumulated those pieces over years of working on problems. Every piece represents an experience the expert has had, both successful and unsuccessful.

When faced with a new problem or task the expert considers the elements of his current context and then begins to look for pieces in his box that relate to this new task as well as the current context. Having recalled some of those relevant past experiences he begins to “construct” a solution. The operant work is “construct” – meaning he combines those experiences in the moments of facing the problem. As he draws on those experiences he is also thinking about the context in which each occurred and comparing that context to of the one he is currently facing.

Like Lego blocks, those same experiences can be put together in different configurations.  If he were to face the same problem next week he might construct a quite different solution because during the week he has added more experiences to his box.  What differentiates an expert from someone who is simply competent is both the number of experiences he has had and the range of those experiences - so that when he begins his search for relevant “Lego pieces” he has more and more varied pieces to choose from. Ashby’s* law of requisite variety at work!

Let’s turn to a real life example. This example is from Julian Orr’s study of copy repair technicians. Orr explains that the repair technicians, in a given geographic area, often meet at the same restaurant for lunch. Orr describes a meeting where Alice, who has a problem she wants some help with, shows up for lunch. She has no faith in the diagnostics that are in the manual about the problem she is facing. The diagnostics tell her to change the board, but she has changed the board numerous times and has come to believe there is a deeper problem, which is causing board after board to fail, and she knows that the diagnostics do not consider that possibility.

“Alice brings with her copies of a log from the machine that is troubling her in the hopes that others will get interested in the puzzle. Most of the conversation over lunch is between she and Fred. Fred says he can’t go with her [to look at the machine] but begins to tell her how he would approach the problem. … Fred starts to tell her about running the noise test, and then says she probably cannot do it if the machine will not run at all. … He tells her about testing the communication lines. After she checks the communication lines, [he explains] she should follow the procedures the book specifies for that error code. Another technician, Bill, asks Fred if the manual specifies testing the communication lines the way Fred has just described; [Fred acknowledges] the book only says to check them but Fred prefers more rigorous testing. [Alice] knows his suggestions are based on experience, that they are things he has found to do to shortcut the diagnostic procedures.”*

Fred’s response to Alice goes far beyond what can be written in any manual. The exchange arises out of a real problem that Alice is confronting and to respond Fred must draw on his wealth of experience related to that type of problem. Bill’s question to Fred, about what is in the manual, causes Fred to draw together different bits of his experience to respond to Bill. As he is explaining, Alice is listening not only to his solution but also to how he thinks about solving such problems. In this way Alice is building her own base of experience from which to draw.

Given how expert knowledge is developed an effective transfer process would have these properties:

• allows the learner to observe the expert in action  
• involves real problems, not hypothetical
• expands the learner’s base of experience
• provides a venue in which the learner can question the expert’s actions and equally important probe his reasoning
• the learner’s brain is actively involved, not just listening but engaged in problem solving

See, Do, Teach

 See, Do, Teach is a knowledge transfer process designed to incorporate the needed learning elements to quickly develop expertise through an intensive, immersive period of learning over a month or more.  

Think of an employee, maybe a testing engineer, a salesperson, or a facilitator, who is competent, but falls short of having the expertise the company needs to replace those retiring. Now imagine that learner shadowing an expert as that expert goes about his normal work. Watching what the expert does, what he says, how he interacts, and his tone of voice. Maybe the learner sits in the back of the room in meetings, inconspicuously taking notes, or perhaps looks over his shoulder as the expert makes a difficult calculation.  Then imagine, over coffee or lunch, the learner asking the questions that have been puzzling him, “How did you decide today was the right time to give the client a call?”  “Why did you start the meeting with that question?”   “How did you decide that tolerance level was acceptable?”  And from the answers, begins understand not only what to do, but how to think about choosing those actions.

See Do Teach is a three part series of engagements between an Expert and a Learner. The See Do Teach process transfers tacit knowledge more effectively than written documents because the learner repeatedly observes the behavior he or she is expected to emulate.  

1. See - A Learner shadows a high level Expert over a period of time as he or she interacts with problems, clients or issues. Following each engagement, the two hold a structured debrief – where the Learner asks questions to understand  the “why” behind the actions of the Expert. Both learner and expert receive training in how to ask questions that draw out tacit knowledge and ways to provide reasoning.   

2. Do – The Learner now does the interacting with the problems, client or issues over a period of time, all the while being shadowed by the Expert.  Again following each engagement the two hold a debrief.  It is not enough to copy the action of someone else, it is also necessary to understand why that specific action rather than some other.

3. Teach – When the Learner and Expert confirm competence has been developed, the Learner takes the role of Expert and a new Learner is assigned to shadow him or her. Teaching the skills to another embeds the knowledge more deeply, helping it to become increasingly tacit.

Now expand that image of the Expert to 5 or 20 Experts all participating in See Do Teach, each with a shadow.  Imagine how quickly expertise could grow as each shadow becomes fully qualified as an Expert and ready to continue expanding the pool of experts.

See, Do, Teach is observational learning, a proven process based on the Social Learning theory of Bandura*, the organizational learning theory of Argyris, and reflecting my own experience working with The Leader Challenge in CompanyCommand*. Those who work in healthcare will recognize observational learning as a standard method of transferring knowledge whether in the operating room, or the ER. How many times have you noticed a young resident, standing in the back ground as a medical specialist examines you? 

Before you do another exit interview or elicitation, think about that box of Lego blocks.  

Please contact me if you want to know more about See Do Teach.  

 

Bibliography

* Ashby’s law of requisite variety - “the internal diversity of any self-regulating system must match the variety and complexity of its environment if it is to deal with the challenges posed by that environment” Ashby, Ross. 1956. An Introduction to Cybernetics. Chapman & Hall.

* Orr, Julian. 1996. Talking About Machines. Cornell University Press,

* Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall.

* Argyris, Chris. (1993) Knowledge for Action. Jossey-Bass 

* Dixon, Nancy, Nate Allen, Tony Burgess, Pete Kilner and Steve Schweitzer. (2005) CompanyCommand: Unleashing the Power of the Army Profession. Center for the Advancement of Organizational Learning, West Point

Part II “We Know More Than We Can Say: How to Use Tacit Knowledge

 

In Part I, I explained why “we know more than we can say” including, 1) how our brains store knowledge, 2) how we create knowledge 3) the values and relationships that are involved in tacit knowledge.  I gave examples of situations in which knowledge workers, who understood something very deeply, were unable to clearly articulate what they knew to others, although they were themselves able to act on their deep knowledge.

If, as these examples illustrate, you can’t just write it down, the question remains, "How do we make use of our tacit knowledge?" In this post, Part II, I suggest two important ways that can occur. The first is to draw on someone’s tacit knowledge for an answer to a pressing question or problem. And although we may never fully know the deep understanding that forms the basis of their response, we can take action based on their advice. I suggest two pathways that are useful when there is a pressing question or problems

The second way to make use of the tacit knowledge in the organization, is to grow it in employees so they have the capacity to solve complex problems themselves and here again there are multiple pathways to this end.   

I - Drawing on the Tacit Knowledge of Others

There are two ways to draw on the tacit knowledge of others. The first assumes an individual has a question or problem he or she needs some help with, the second assumes a larger issue, perhaps a team that is starting a new project and needing to draw on the collective knowledge of those in the organization to plan or develop a strategy for it.

1. An individual with a question or problem   

The first way is to hold a conversation with a colleague or expert (the source) to draw on his/her tacit knowledge. Email won’t work because the source will have to spend some time learning about the asker’s context in order to draw on patterns within his/her experience that fit that context. A face-to-face conversation is optimal because it allows the give and take that Hans described or that we saw Fred engaged in with Alice. A conversation could certainly begin with an email, or a question asked in a CoP, and then continue over coffee or, if simple enough, by phone. But here we run into the issue of values and relationship. To be willing to invest conversation time, the responder has to have a sense of who the asker is. This, of course, is where building a network is critical; having met the individual face-to-face at a network meeting, or being a part of a community where people are committed to helping each other, increases the likelihood that the responder will expend  the necessary time and energy.  

Rob Cross and Lee Sproull conducted a study in 2004 that looked at the benefits that accrued to people who had a conversation with a colleague about a relatively ambiguous issue each was facing.  These seekers were project managers in a large consulting firm. They had access to first-rate company repositories of best practices, case examples, reusable work products, methodologies and tools, discussion forums and expertise databases.  In spite of such tools, overwhelmingly they preferred to take the issue they were wrestling with to a colleague.

Cross and Sproull conducted in-depth interviews with each of these project managers to explore what they learned through the conversations they chose to have.  Then they sorted the responses into five categories, which I outline here. I’ve also embedded my own thinking related to the categories- so they are not pure Cross and Sproull.

Answers:  Not surprisingly the seekers got answers to the questions they asked. Some of the answers were factual in nature, but more often what was asked for and received was procedural or methodology based. The seekers were looking for the application of facts or principles in order to develop a solution.  

Meta Knowledge:  This category was about where to go to get more information on the issue, or conversely where not to go because a certain report was out-dated, or superficial. Also in this category was the identification of specific work products and the names of other people who could be helpful, along with an introduction. Meta knowledge is incredibly useful, but only if the source knows enough about the issues the seeker is facing, in order to sort through possibilities based on, 1) the seeker’s level of expertise (absorptive capacity) and, 2) the applicability of the meta knowledge to the seeker’s specific situation.

Problem Reformulation: This occurred when the source suggested a different way to look at the problem or issue, a way that might even have invalidated the original question. Problem reformulation tended to broaden the thinking of the seeker or to approach the question from an entirely different angle. Also in this category was helping the seeker become aware of potential unforeseen consequences of specific actions, as well as increasing awareness of issues that were likely to be particularly sensitive.

To gain meta-knowledge and/or problem-reformulation requires the source to be willing “to understand the problem as experienced by the seeker and then shape her/his knowledge to the evolving definition of the problem” and is best served by the give and take of conversation.  And as Cross and Sproull point out, to provide meta knowledge also demands a strong enough tie with the source so that he or she is willing to invest the necessary time in the seeker’s issue.

Validation:  This is assurance that the approach the seeker is taking, is on course. And it is the expression of appreciation for the seeker’s thinking behind his or her planning. Validation builds the seeker’s confidence and allows him or her to move forward with greater certainty and perhaps even be more self-assured when approaching a client. Validation also provides seekers the certainty that they have done enough background work, saving the seeker the time it would take to gather further data.

Validation has an emotive content that comes across most fully through the facial and tonal cues we pick up in face-to-face conversations.  Like most feedback, validation provides greater assurance when it references specifics rather than generalities. For example, “Great plan” is less validating than is, “The logic of your argument is well sequenced which adds to its face validity.” But to offer that level of specificity takes in-depth understanding on the part of the source.

Legitimizing: Legitimizing is the expression of approval by a person in authority or with known expertise, which the seeker can then use to influence others. As with validation, legitimizing can save the seeker time by reducing the amount of proof or data that may need to be collected before the client is willing to act. It also serves to head off arguments others might raise.

The greatest benefit of an exchange with a colleague is that it produces five categories of responses, not just the answer. So much more is available from conversation, e.g. an unexpected insight, a sense of affirmation that inspires the seeker to new heights or equally useful, having to confront a realization that he or she has been trying to avoid; deepening the relationship with a colleague; or the introduction to a collaborator the seeker would never have discovered on his or her own; and on and on.  

2. A Team or Group Requesting Help on Broad Issues Such as a Plan or Strategy

Here the technique is to bring together a group of colleagues that can provide multiple perspectives on an issue. We often think of this as a Peer Assist, that is, drawing on the knowledge of peers who do similar work. But just listening to others present, as happens at most conferences, does not constitute a Peer Assist because to make use of the tacit knowledge of another requires an in-depth conversation and that does not happen in presentations, even with Q&A tacked on at the end.  Nick Milton tells this story about a Peer Assist in South America.

"A company had moved into a South American country through acquisition. They had taken over a chain of local dealers, and needed a business information system up and running. The vendor said, 'This will take you 10 months'. Management said, 'We need it in 6 months if we are to capitalize on this acquisition.' Although the implementation of a business information system was new to that country office, it was not new to the company. Offices in Eastern Europe and the Middle East, had done this sort of thing recently, a team in the head office were working on standard processes for business systems, and there were several vendors who offered these systems. The country office decided to tap into this knowledge through a [face-to-face] 2-day Peer Assist. They held video interviews with the participants to develop a shared context in advance, and built a careful agenda of knowledge sharing and solution creation.

An email from the country manager afterwards confirmed that they had benefited from applying the knowledge management principles, starting with the peer assist, which produced a much improved project plan, reducing the time-scale from 10 to 4 months. Examples of processes/procedures and technical templates were lifted from Poland and Russia to start the project off. External benchmarking suggests that the costs would have been up to $500,000 higher without the knowledge transfer. So a direct benefit of $500,000 was realized, with the additional indirect benefits of accelerating proper governance by 6 months compared to the original vendor estimate."

A second example of a type of Peer Assist comes from Healthcare. 

In 1987 the US government started requiring Medicare to publicly report hospital death rates in all regions of the country. One of the figures reported was on bypass surgery, one of the most frequently performed surgical procedures.  For the hospitals in the Northern New England region the reported death rate was 4.3 per hundred operations.  The cardiac surgeons in the hospitals began to realize that there was great variability among individual hospitals, ranging from 2 to 9 deaths per hundred patients. Up until this time surgeons would have been aware of their own death rate, but would not have known how it compared to others – after all some deaths are not preventable, no matter how skilled the surgeon. 

The surgeons in the five largest hospitals in the region took this information very seriously and voluntarily created a study group to do something about it. The action they decided on was to observe each other operating on patients and after each operation meet to discuss the case.

Because of these many “peer assists,” between 1991 and 1993 the death rate across the region fell from 4.3 to 3.3 deaths per hundred operations, resulting in 74 fewer deaths in that two-year period than what the trend line would have predicted.   By the end of the study in 2002 the death rate had fallen to 2.1 percent across the region, which translated into 811 fewer deaths.  

In both of the examples the requirement is conversation and in the last, observation as well. In the Peer Assist examples, multiple perspectives were involved because the receivers needed more than an answer, they need a deeper understanding to guide many actions they would take in the future.

 

II Developing Tacit Knowledge in Others

What organizations have learned, through twenty years of attempting to transfer an expert's broad base of tacit knowledge to less experienced others, is that it is not possible. They have found, what we already knew as parents attempting to transfer our own life experience to our children, that everyone has to develop tacit knowledge for him or her self. And that our role as parents is, 1) to provide as rich an experience base as we can, through such events as, travel to different environments, engagement in activities from cultural arts to sports, opportunities to try out new ideas and even to fail and learn from those failures, and 2) to offer coaching, most importantly our own, but also through competent teachers, sports coaches, counselors, etc. that provide a broader perspective and new ways of understanding the world.

So the second way to draw on tacit knowledge is to grow the tacit knowledge of employees, so they have the capability to solve problems themselves. Organizations need to offer, 1) opportunities for experience and 2) structures through which coaching can occur.  These two elements would sound familiar to any HR person, but to grow tacit knowledge these elements must be designed based on what we have learned about 1) how our brains store knowledge, 2) how we create knowledge, and 3) the values and relationships that are interlinked with tacit knowledge and that were elaborated in Part 1 of this article.   

1. Experience and reflection

People learn from experience, when 1) they have to opportunity to try different ways of doing things and 2) they have the time and opportunity to reflect on what they did.  To develop tacit knowledge these two actions must be paired. Little learning results from experience without reflection, likewise reflection is empty without new experiences that serve to test the knowledge that reflection has brought forth. 

The opportunity to try different ways of doing things occurs both at the individual and the group level. At the individual level it means employees have the opportunity to try out their own ideas for improvement or innovation. In some companies this is labeled “empowerment,” but whatever the label, it means employees are able to make use of their own judgment in determining what actions to take.

A well known example is the 3M Corporation that has encouraged deliberate experimentation by offering employees at all levels 15% of their work hours to develop and test their own ideas.  The 15% program has generated some of the company’s best selling products such as, post it notes, clear bandages, optical films that reflect light and painter’s tape. 3M’s successes inspired Google to offer 20% time and that has been as fruitful, producing Gmail, Google Earth, and Gmail Labs.

But experimentation does not need to be individual to build tacit knowledge. Teams that have the flexibility to test new ideas, with members offering their own thinking and the reasoning behind that thinking, serves equally well to build tacit knowledge.  What does not build tacit knowledge is for a team or an individual to be told what to do, without the ability to impact those instructions and with little understanding of the reasoning behind the decisions.  In such situations, neither success nor failure will yield tacit knowledge in the participants.  

The second half of the pair is reflection. Experience is gained, not through one occurrence, but over enough occurrences that patterns begin to emerge across all of the actions taken. Reflection requires thinking back on the actions taken, the reasoning behind the choice of action, the context in which the action took place, and the outcomes that resulted from the actions, many of which are unintentional. While experience is inevitable, learning is not.  To learn from experience requires deliberate reflection. 

Reflection is most effective when it is done in the company of others who are involved in the same kind of work.  When we summarize what happened for another, we begin to understand it better ourselves.  We learn when we talk.  Each practitioner functions within a somewhat different context, and responding a bit differently. Consequently the learning of each practitioner is unique. When those practitioners reflect together on their actions, “creative abrasion” (Leonard) occurs, which leads to greater understanding in those engaged in the conversation. 

The relationship between cause and effect is always complex. Most of the outcomes of a team’s actions have multiple causes and it takes the thinking of the whole team to tease cause and effect relationships out. A group discussion moves the knowledge each individual holds into a group or public space where it can then be integrated and made sense of by the whole team. The team then draws on the shared knowledge the next time it takes action.

The US Army took reflection to a new level when, in the 1970’s, it instituted the After Action Review (AAR) to be conducted at every level following any engagement. In each AAR session the army drew out three levels of lessons: 


1. Lessons for the platoon (or battalion or company) that would lead it to take more effective action the next time it was engaged in a similar maneuver - typically a facilitator wrote these lessons on a flip chart for everyone to see. 


2. Individual lessons that each soldier learned, that would lead him/her to act more effectively the next time that soldier was involved in a similar maneuver - each soldier carried a pocket notebook to write these lessons down during the group meeting


3. Lessons that could be generalized for the use of others – a subset of what was learned in the meeting was sent to the Center for Army Lessons Learned (CALL) to be made available to other platoons.

Formalizing lessons learned, as the Army did, is useful because, teams don’t often take the time to pause and think through, “Now what did we learn out of that experience?” “What would we do differently next time?” Consequently teams frequently find themselves making the same mistakes over and over again. Even for individuals, the reflection process is more effective when it is formalized, for example, keeping a journal or a holding a regularly scheduled conversation with a colleague or mentor who can help the individual think through the lessons.

Coaching

According to Nonaka and Takeuchi, “The key to acquiring tacit knowledge is experience. Without some form of shared experience it is extremely difficult for one person to project her or himself into another individual’s thinking process. The mere transfer of knowledge will make little sense, if it is abstracted from associated emotions and specific contexts in which shared experiences are imbedded.”  

Leonard describes a top consultant who was asked where and how he learned his skills in closing deals with clients. 

“‘I had an excellent teacher,’ he replied. He explained that when he joined the company, an elder statesman in the firm had asked him to set in on clients meetings. ‘You don’t have to say a word,’ the older consultant told him. ‘Just listen and learn.’ The junior consultant rightly took that directive as more than a suggestion and sat at the back of the room. After each client meeting, he and the older consultant discussed what had occurred. ‘I learned more from those briefs,’ he said, ‘than in four years at my prior company and two years of business school.’”

The US Army has long used coaching as a critical part in the development of military officers. Nate Allen, one of the founders of CompanyCommand, an on-line community for Company Commanders, describes the Leadership Challenge as a “simulated, Cognitive Leadership Challenge. A platform where Soldiers can construct solutions to various scenarios presented to them by their peers and/or predecessors.”  The challenge is a short video of a soldier presenting a real situation he or she has faced - one in which there was no clear-cut or obvious answer. For example a U.S. Army Platoon Leader serving in Iraq describes this situation in a video:

“We were headed out to a pretty easy mission. My front truck reports that there’s a dead body under a car in the middle of the road. He was on the ground. He had been in his car and he had been shot. At that point, the gunner from my lead truck noticed a double-decker bus that had stopped. And there was a guy up on the top deck who appeared to have a blue video camera, and he was just hanging out the window video-taping us. Our rules of engagement permitted us to engage anybody video-taping an attack. I looked down my sight and noticed the same thing. The gunner looked through binos and noticed the same thing. He asked me, ‘Hey sir, can I go ahead and shoot him?’  

The viewer is then asked, What are the considerations? and  What would you do?  After answering the viewer then reads a set of 3-5 sample responses and is asked to rate each. Follow his response, the viewer can then read the responses other viewers have written.  Before the final step views are provided resources that broaden their understanding, such as army manuals, interviews with other soldiers in a similar situation and news articles.  Finally the viewer sees “the rest of the story” of the original video. Viewers can then make changes to their original answer and participate in a threaded discussion with their peers about the issue.   

This sequence of experiencing a realistic but ambiguous situation described by someone much like the viewer, planning an action, and exposure to others’ thinking, develops the tacit knowledge of the viewers. The situation is one in which the viewers recognize they will likely find themselves in the future. They are required to envision a course of action and then to learn what others would do in that same situation, but more importantly they learn the why of others thinking, a tactic that broadens their own view. When they have the opportunity to review their original response, 40% percent make changes, a strong indication they have broadened their tacit understanding.

Borrow Forward is an example of the development of tacit knowledge that comes from Kaiser Foundation Health plan (KFHP) and Kaiser Foundation Hospitals (KFH). The health care system employs a form of Process Improvement called “adaptive design” that requires employees from a unit, for example the emergency room, to work together as a team. Alide Chase, Senior Vice President of Quality and Service, explains the joint experience each team has before beginning their Process Improvement (PI) training.

Before each new team begins their PI training, they engage in “Borrow Forward.” A team of 4-5 persons from, for example the Emergency Department, makes a visit to an Emergency Department in another location that has already successfully implemented adaptive design. The visiting team goes in a state of inquiry. Each visiting team member shadows his/her counterpart for 2 to 3 days. Before leaving, the visiting team holds a meeting with those they shadowed to talk with them about the observations and insights they experienced. This is a reflection meeting in which both parties learn. The visiting team articulates their insights which helps them clarify what they learned for themselves and the host team gains new understanding of their own processes by seeing those processes from a new perspective. 

After their return, the visiting team begins their PI training and implementation. They hold weekly meetings to reflect on the actions they have taken and the results achieved. Borrow Forward provides a shared experience from which they derive shared meaning, and provides a lens through which they are able to think about their work.

 A final example comes from the consulting world. Leonard describes the way SAIC, a consulting firm that works primarily with the US government, prepares  “knowledge consultants.”

“Knowledge consultants learn their trade from more experienced consultants through first observing the expert help a client learn a particular knowledge management process, next practicing the skills by leading a client session and receiving feedback from the coach, and then teaching the skill to another consultant.  This process is one of SAIC’s most useful knowledge transfer tools not only in-house, but also for coaching clients. The knowledge consultants take their clients through the same “see one, lead one, and teach one” processes of learning.

Coaching can come from many quarters. The first example is a typical one, where a mentor helps a junior consultant gain tacit knowledge.  The second example of the Army’s on-line peer coaching is very carefully crafted sequence of steps, the third involves a team conducting an in-depth observation and the fourth, is the well known process of “see one, lead one, and teach one.” In each, coaching involves observing, conversation and doing.

Summary

In Part I, I described the research basis for why it is difficult for people to write their tacit knowledge down; 1) that our brains store what we have gained from experience in bits and pieces and then reconfigures those elements when faced with a problem or question, 2) that we create knowledge by finding patterns in our experience, 3) that values and relationships impact our willingness to share our tacit knowledge with others and their willingness to trust that knowledge. 

In Part II, I offered two ways to make use of tacit knowledge, given that it is not effective to ask people to write it down. The first was to call on the tacit knowledge of others when faced with a problem or question and to probe for understanding through an in-depth conversation with them – one in which the resource has the time to understand the context of the asker. The second way was to develop tacit knowledge in others which occurs through 1) providing opportunities for employees to initiate actions and reflect on those actions, and 2) providing opportunities for coaching from experts and more often, and more usefully, from peers. 

 

 

We Know More Than We Can Say: The Paradox of Tacit Knowledge - Part One

“We know more than we can say” is a popular phrase heard at KM conferences and quoted in the many KM blogs. It is quoted to encourage attending to tacit knowledge, rather than exclusively focusing on explicit knowledge.  But those quoting the phrase seldom go beyond referencing it to Polanyi, providing little explanation or reasoning for why, if we know it, we can’t just write it down.  

In this post I want to offer the “why” behind the phrase and give some examples. The answer lies in, 1) how our brains store knowledge, 2) how we create knowledge, and 3) the values and relationships that are interlinked with tacit knowledge.  

How Our Brains Store Knowledge

What we learn from experience is stored, not in the form of answers, but in bits and pieces of the experience we have accumulated, sometimes over years. What we think of as tacit knowledge is really the human ability to draw on our past experiences to respond to new problems or questions.

When a colleague asks a question, the responder pulls together the bits and pieces from different parts of past experience to construct an answer. The operant word in that sentence is “construct.”  The responder constructs an answer in the moment of responding. Responders do not “know” the response they will give until faced with the need for it. Karl Weick, the well-known organizational theorist, affirms this idea when he says, “How do I know what I think until I hear what I say?”  

Weick describes a situation in a neonatal unit in which the nurse draws on her experience to diagnose that a baby is in a critical situation.

“I took care of a 900-gram baby who was about 26 or 27 weeks…who had been doing well for about two weeks. He had an open ductus that day. The difference between the way he looked at 9 a.m. and the way he looked at 11 a.m. was very dramatic. I was at that point really concerned about what was going to happen next. There are a lot of complications of the patent ductus, not just in itself, but the fact that it causes a lot of other things. I was really concerned that the baby was starting to show symptoms of all of them.

You look at this kid because you know this kid, and you know what he looked like two hours ago. It is a dramatic difference to you, but it’s hard to describe that to someone in words. You go to the resident and say: “Look, I’m really worried about X, Y, Z,” and they go: “OK.” Then you wait one half hour to 40 minutes, then you go to the Fellow (the teaching physician supervising the resident) and say: “You know, I am really worried about X, Y, Z.” They say: “We’ll talk about it on rounds.” 

When asked about the meaning of  “X, Y, Z,” the nurse begins to describe the items she noticed and finally gives up because she feels it is not possible to identify all the individual symptoms that she drew on.

The fact that the kid is more lethargic, paler, his stomach is bigger, that he is not tolerating his feedings, that his chem strip (blood test) might be a little strange. All these kinds of things. I can’t remember the exact details of this case; there are clusters of things that go wrong. The baby’s urine output goes down. They sound like they are in failure. This kind of stuff. Their pulses go bad, their blood pressure changes. There are a million things that go on. At this time, I had been in the unit a couple or three years.

Her last sentence is significant, indicating as it does, that she has three years of experience dealing with premature babies to draw on to reach her conclusion.  In this interview she is being asked, in effect, to make her tacit knowledge explicit for the interviewer and her giving up on that effort illustrates the difficulty in “just writing it down” or in this situation, even being able to say it fully.

The nurse was able to diagnose what was happening to the baby, but was  unable to convince the physicians she spoke with that there was a problem. She explains,

I talked to a nurse who had more experience and I said, “Look at this kid,” and I told her my story, and she goes: “OK.” Rounds started shortly after that and she walks up to the Attending [Physician in charge of patient] very quietly, sidles up and says: “You know, this kid, Jane is really worried about this kid.” She told him the story, and said: “He reminds me about this kid, Jimmie, we had three weeks ago,” and he said: “Oh.” Everything stops. He gets out the stethoscope and listens to the kid, examines the kid and he says: “Call the surgeons.”

Another researcher who has studied the sharing of tacit knowledge is Dorothy Leonard, who wrote Deep Smarts.  She says, “…Deep smarts are based on first-hand life experiences, providing insights drawn from the tacit knowledge that has built up over time.  Deep smarts are as close as we get to wisdom about managing. There is no way to transfer this wisdom, all the packets of knowledge, all the lightening-fast associations, all the rich details that a single word or phrase calls up from the long-term memory in the brain of a person with deep smarts. Rather, wisdom must be re-created.” 

She tells the story of Dr. Eleanor Mobilia, a leading expert in fitting specialty contact lenses for people with cornea diseases. Dr Mobilia died before she had fully trained a protégé to take over her practice.  “Dr. Eleanor Mobilia’s career spanned 50 years. She had conducted decades of research on contact lenses and had fitted thousands of patients.  [Her] protégé, Dr. Janet Rand, reflected on the difficulties of re-creating Dr. Mobilia’s deep smarts:

There are a lot of different scenarios for the shape of the cornea due to how the eye heals. They are like snowflakes. Everyone heals differently, so it’s a very inexact science. Dr. Mobilia had fitted thousand of eyes of each shape and she knew the type of lenses that would best be tolerated. I'm sure she had a plan for how to fit patients with really irregular corneal transplants. But most of her knowledge there was lost.  After she passed away, I had a transplant patient with an eye that was so flat lenses would just fall off. Nothing I tried worked. I'm sure Dr. Mobilia knew by looking at some patients, this is impossible, and not even try fitting them until they had further surgery.”

This story illustrates that even when an effort is made to transfer tacit knowledge from one skilled practitioner to another, even working side by side, only portions of that knowledge is actually transferred.

Another researcher is Julian Orr, who in the early 1990’s studied how copy repair technicians went about their work of diagnosing and solving the problems of the machines they were trying to repair. He conducted an amazingly detailed study of the use of tacit knowledge.  He explains that the repair technicians, in a given geographic area, often met at the same restaurant for lunch. Orr describes a meeting where Alice, who has a problem she wants some help with, shows up for lunch. She has no faith in the diagnostics that are in the manual about this problem. The diagnostics tell her to change the board, but she has changed the board numerous times and has come to believe there is a deeper problem, which is causing all these boards to fail, and she knows that the diagnostics do not consider that possibility.

Alice brings with her copies of a log from the machine that is troubling her in the hopes that others will get interested in the puzzle. Most of the conversation over lunch is between she and Fred. Fred says he can’t go with her [to look at the machine] but begins to tell her how he would approach the problem. … Fred starts to tell her about running the noise test, and then says she probably cannot do it if the machine will not run at all. … He tells her about testing the communication lines …  after she checks the communication lines, [he explains] she should follow the procedures the book specifies for that error code. Another technician asks Fred if the manual specifies testing the communication lines the way Fred has just described; the book only says to check them but Fred prefers more rigorous testing. [Alice] knows his suggestions are based on experience, that they are things he has found to do to shortcut the diagnostic procedures.” 

It is in these luncheon meetings that tacit knowledge is shared. Fred’s response to Alice goes far beyond what can be written in any manual. The exchange arises out of a real problem Alice is confronting and Fred is drawing on his tacit knowledge to address that specific problem. But, as he is explaining Alice is listening not only to his solution but also to how he thinks about solving such problems. In this way Alice is building her own tacit knowledge.

Orr explains that the luncheon meetings of copy repair technicians, are not recognized by the corporation. The corporate view is that knowledge and skill are a matter of individual competence, which is gained by attending training, reading journals, and/or listening to lectures.  The technicians, however, know that training is only the beginning of developing knowledge. The deep knowledge they need is developed through experience that happens while doing the work, so they willingly use their lunch hour to tap into the tacit knowledge of their more experienced colleagues.

Creating Knowledge

In each of the stories, what the experienced practitioners are doing is finding patterns in their past experience that fit the current situation. A physician, software engineer, or policeman encounters many different situations, perhaps 15-20 times a day. And over months and years they begin to “pattern recognize,” that is, to step back and think to themselves, “I’ve seen this situation before and usually this is what is going on.” Leonard puts it this way.  “Armed with this broad-based knowledge, the expert becomes increasingly aware of, and sensitive to, meaningful patterns in a sea of information.”

In his book, Sources of Power, Gary Klein recounts this incident of a fireman recognizing a pattern:

It is a simple house fire in a one story house in a residential neighborhood. The fire is in the back, in the kitchen area. The lieutenant leads his hose crew into the building, to the back, to spray water on the fire, but the fire just roars back at them. “Odd,” he thinks. “The water should have more of an impact.” They try dousing it again, and get the same results. They retreat a few steps to regroup. Then the lieutenant starts to feel as if something is not right. He doesn’t have any clues; he just doesn’t feel right about being in that house, so he orders his men out of the building…  As soon as his men leave the building, the floor where they had been standing collapses.  Had they still been inside, they would have plunged into the fire below.

It was only after persistent questioning during an interview, that the Lieutenant is able to name the pattern that led him to the decision that saved the lives of his men. Like the nurse in the neonatal unit, his explanation is offered as only a part of the pattern he detected;  “For example, the room was hotter than he would have expected from a small fire, and the fire was very quiet. He unconsciously deduced that there must be an unsuspected basement beneath the living room, and that was where the main fire was; he then “intuited” that his men were in danger.”

The story of the nurse in the neonatal unit illustrates the difficulty of transferring the recognition of a pattern to another. Jane tried twice to explain to physicians in the area that the baby was in trouble, and each time was summarily dismissed. It was only when the more experienced nurse related Jane’s concern to a physician who was just starting rounds. That physician took the time to see the pattern for himself. The tacit knowledge of the more experienced nurse was seen as more credible, which leads to the third element, values and relationships.

Values and Relationships

Constructing knowledge from past experiences is hard work as we saw with Fred, who first thinks of the noise test as a solution to Alice’s problem and then, realizing that won’t work, tackles the problem from a different angle, the communication lines. Sharing tacit knowledge is not about the source recalling the answer, rather it is about the source constructing an answer.  How hard the source is willing to work to construct an answer has to do with the relationship the asker has with that responder.  In Fred’s situation, he has some interest in Alice’s development as a technician because she is a member of his team and there is a norm that the more experienced Techs help bring the newer people along.  In order for responders to be willing to put in time and energy they need to view the asker as, 1) someone who values their information, 2) knows enough to be able to use it, and 3) that the problem being presented is worth their time and effort.    

I was studying knowledge transfer at Erickson in Sweden. As I interviewed technicians I kept hearing Hans’ name come up as the person to go to if a technician had a question about the computer language C++. Finally I checked with someone, “So Hans must be the resident expert on C++?” and was quickly told, “Oh no, the resident expert is Joachim, but he’s not very good at explaining. Now Hans, he can really help you understand how C++ works with our switches.”

Later when I interviewed Hans I told him that I kept hearing his name as the person a technician should seek out if they want to understand C++. I asked him how he got that reputation. Modestly, he said, “Well, I’m not sure how I got the reputation, but I’ll tell you how I try to help people who come to me with a question. Is that what you want to know?” I agreed it was what I was after. So he explained, “When a technician comes to my office he usually starts by explaining what he wants to know about. But before I try to answer his question, I ask a few questions to see how much he already knows about C++. Then I ask a few more questions to find out what he’s planning to do with the information. By that time I’ve formulated an idea about where to start and what I need to say. And we just go from there, talking back and forth.”

During this same study, I heard a number of inexperienced software engineers complaining about Joachim. The complaint was that Joachim ignored their questions or was rude when they tried to ask them.  When I asked others about this, I got a chuckle in response, “We save Joachim for the really tough problems, the ones no one else can figure out.  If he answered all the newbies questions he wouldn’t have time for the work only he can do.”  This quite sensible response, illustrates the need for the responder to believe that the person asking the question knows enough to be able to take in the answer. Clearly, from Joachim’s perspective, inexperienced software engineers did not.

What Hans was doing is also what a skilled medical diagnostician does, that is, try to fully understand the context before answering the presenting question, and that takes time.

The knowledge we learn from experience is very personal. In a study  conducted by Constant, Kiesler, and Sproull they found that employees considered any product (including documentation) they had produced for their organization to be the property of the organization and therefore should be freely offered to others. However, the knowledge they gained through experience, they considered their own property and although they were willing to share it, they did so only when they felt that the asker was interested and would do something with it. They explain.

“One major distinction people seem to make is between tangible information such as written document or a computer program, and intangible information embodied as human memory, knowledge, experience, or skill such as ability to type, ride horses, or fix a software bug. ...People do not view expertise as simply a commodity but … view it as part of themselves. Hence, expertise more directly reflects on their identity and self worth.”

This study helps us understand why relationships and values are so important in the transfer of tacit knowledge. It what I know if part of my identity and self worth, I would be careful about how and with whom I shared it. It speaks to Block's counsel, "Connection before content."

Summary

To summarize the answer to the my question, "why can’t we just write it down?"

• It is possible to write down the answer that a responder provides to a specific question or problem, as we often see in communities of practice. So in a sense the responder has written down his or her tacit knowledge, but the answer is in response to a specific situation. If the responder were to be asked a question with a slightly different context, the answer would be different. In fact if the responder were to be asked the same question a week later, it is very likely that the answer would be different because the experience of the responder has grown and therefore the responder has new bits and pieces to draw upon. 
• To ask someone to write, record, or otherwise document their tacit knowledge is like asking them to respond to all imaginable questions or problems about their area of expertise. And given that new problems and technology are constantly arising – the task is clearly not possible.  
• Moreover, responders may have little confidence that what they write will ever be read or if read that the reader will have sufficient understanding to make use of it.  

Given this understanding, in Part Two, I will lay out several ways that it is possible for an organization to make use of tacit knowledge - ways that reflect the nature of tacit knowledge that I have outlined here. 

The Three Eras of Knowledge Management

In this video I describe the Three Eras of knowledge management that I have previously written about on this blog, Where Knowledge Management has Been and Where it is Going – Part One, Part Two, and Part Three. My understanding about the third era continues to grow so I have elaborated the third era in this post.

 

In the earlier blog post I called the third era, “collective knowledge” and I remain convinced that collective knowledge is at the heart of this change. It is the "means," but what is being managed are ideas. So I am using “Idea Management" as the label for the third era both in this video and in the accompanying chart. The first two eras, Information Management and Experience Management dealt with existing knowledge, that is, knowledge that an individual or a group has gained and is available to be shared with others. The third era is about the creation or development of ideas that have not existed before. It is not the management of anything organizational members have learned through their work experience, but what they create jointly when they are brought together in an environment that supports the use of collective knowledge. That support includes convening, cognitive diversity and transparency.

In the last couple of years I have had the opportunity to work with organizations that are using third era practices and that experience has sharpened my thinking about what is occurring and why. I’m still not sure I have all the words right, but the big change I see is that management has begun to value the sensemaking capabilities of employees, that is, the ability of employees to jointly make sense of complex situations. Over the three eras management’s awareness of the kinds of knowledge that are valuable continues to expand. Initially management only valued explicit knowledge as evidenced by the resources put against building repositories, then they developed an appreciation for the experiential knowledge of employees and allocated resources to build communities, and now there is a growing acknowledgement of the sensemaking capabilities of employees and an accompanying willingness to provide the resources to convene groups for that purpose.

Of course, management being interested in the opinions, ideas, and knowledge of employees is not new. Organizations have long made use of employee surveys, fireside chats, suggestions boxes, and town hall meetings to collect ideas from employees. But in the past management has reserved for itself the right to make sense of what was collected from employees. The subtext of such practices was, “Tell us [management] your concerns and suggestions and we [management] will figure out a way to fix it.” Now working with leading edge organizations that are, by their actions, saying something quite different, I hear, “Let's convene the people who do this work and have them think together about how to make sense of this issue.”

A recent example of convening is a meeting I facilitated for NASA. Over the years each of the ten NASA Centers has grown its own KM strategy, quite independent of the other Centers and Offices. NASA administration, in recognition of the variability in the effectiveness of the various KM strategies, and spurred by a somewhat critical government report, appointed a CKO, Ed Hoffman, and asked him to develop a NASA-wide KM strategy. Ed is a seasoned KM professional, fully capable of developing such a strategy. But rather than doing that, he chose to convene a three-day meeting that brought together fifty KM professionals from across the ten NASA Centers, to think together about what the knowledge strategy of NASA should be. The meeting made use of the collective knowledge and analytic capabilities of the KM professionals. Outside perspective was provided by Christos Kostopoulos, Senior Economist at Knowledge and Learning Department- Corporate, from the World Bank and Grigg Gurvais, CKO from the FBI. All available information about NASA’s KM programs, internal NASA documents, and the government report was provided to the group. By the end of the meeting the group had identified the elements of a system-wide strategy. The following illustration shows the commitments participants made at the end of the meeting.

The NASA example illustrates the three enablers of the third era, 1) convening, 2) cognitive diversity and 3) transparency.

1. Convening
Convening is the skill and practice of bringing groups together to develop understanding of complex issues, create new knowledge and spur innovation. It is about:
• designing meetings as conversations rather than presentations
• identifying who needs to be in the conversation, including those who do the work and are impacted by it
• framing the question in a way that opens thinking
• arranging the space to facilitate conversation
• using small groups as the unit of learning
I have written about convening and the role of the leader in The Power of the Conversation Architect to Address Complex, Adaptive Challenges

Cognitive Diversity
Cognitive diversity is the deliberate use of difference to bring new understanding to an issue. When faced with complex issues our inclination is to collect more data, survey, or assign a task force to conduct interviews; when what is needed is a new way to frame the issue. Cognitive diversity brings people trained in different heuristics, problem solving strategies, interpretations, and perspectives into the room. Cognitive diversity can be found in different parts of the organization (e.g. marketing, finance, engineering), in different disciplines (e.g. biology, neuroscience, archeology), or outside the organization (e.g. suppliers, customers, consultants, academicians, alliances).

Transparency
Transparency includes the willingness of management to say, “I don’t know” and therefore to employ the organization’s collective knowledge. It is also about management providing all the available information and data on an issue so that those convened have what they need to do the work of sensemaking. Organizational members also have a role in transparency, that is, to be open about what is happening at their level, rather than hiding or discounting bad news to appease management – to bring the best available knowledge to bear on organizational issues

I would welcome other’s thinking on the third era and the supporting elements of convening, transparency and cognitive diversity, as well as useful references and examples.

My thanks to Xuehui Liu, a KM Professional in the Strategy and Planning Department of Huawei Technologies Ltd., Zhenshen, China. In addition to being a skilled knowledge management professional, Mr. Liu proved to have great skills as a videographer.

Are On-line Discussion Forums Conversations?

Conversation is a topic I often present about. On those occasions I am frequently asked, “Do you consider on-line discussion forums conversation?” I usually fumble and hedge my answer. But now, thanks to a study done by Yongsuk Kim, when he was a doctoral student at the University of Texas, I have at least a partial answer. Before I get to Kim’s study let me explain both my experience and my concerns about on-line forums that cause me to hedge my answer to that frequently asked question.

First, I fully support on-line forums. I have had the opportunity to set up on-line forums in many organizations; I co-authored a book about CompanyCommand which is one of the best on-line forums around; and I encourage organizations to make use of on-line forums every chance I get. In my opinion on-line forums are the gold standard of knowledge sharing.

My concerns are related to what I observe happening in many on-line discussion forums. I observe that a member asks a question and then various other members provide an answer. But there is little back and forth among the members. Rather, each responder simply makes a declarative statement that represents his or her own position. Responders may not have even read others’ answers before stating their own position.

Of course, back and forth exchanges are not necessary if the question is just asking for factual information, for example, “How much pressure should valve 25 hold?” A clear response from a knowledgeable peer is all that is needed. But too often I observe the ask/answer format occurring even when the asker is seeking the lessons of experience from other members. And I am hard pressed to call those exchanges a conversation.

I recognize there are many ways to define the term “conversation.” The way I am using it here is: “One or more persons actively working to understand the meaning another is trying to convey.” There is tremendous value gained, both in terms of learning and development, from an exchange that meets that definition. Through conversation with knowledgeable peers, a member is able to gain a different perspective on an issue or a broader way to think about a problem. It is possible to develop one’s judgment through such conversation.

Johnson and Johnson, researchers at the University of Minnesota, who study collaboration, say that the synthesis of diverse perspectives comes from being able to hold both one’s own and another’s perspective in mind at the same time. Holding two perspectives in mind necessarily means there has been enough conversation for each person to thoroughly understand the perspective of the other - not only the conclusions, but to fully comprehend the thinking behind those conclusions. And, having both perspectives in mind, they are able to then hold an intelligent dialogue that explores different interpretations of the problem. And that exploration even has the potential to create new knowledge.

For an on-line exchange to meet my definition of a conversation, much more interaction between parties would have to occur than the ask/answer format that is typical of many on-line exchanges. For example some of the following actions would need to take place:
• The question asker would reply to an answer that he or she receives by,
o Asking for an example,
o Asking for the data that supports the responder’s conclusion,
o Inquiring why that member’s response is better than an earlier response,
o Challenging the answer,
o Or explaining why the answer made sense from the asker’s perspective.
• Responders would have similar interactions with each other by,
o Referencing what another member said,
o Elaborating on another member’s answer,
o Posing a question to another member,
o Suggesting conditions under which another member’s answer is accurate,
o Asking for clarification of another member’s response

In his study Yongsuk Kim referenced this type of interaction as “collective elaboration.”

Kim analyzed 190 discussion threads that involved 1,200 participants in ConocoPhillips’ Networks of Excellence. He surveyed the members who had posted the questions that started each discussion thread, asking them to rate their learning from high to low and to specify the performance that resulted from the answers they received.

Kim found two factors in the discussion threads that were correlated with both learning and performance for the askers:
1) how much collective elaboration occurred in the discussion thread
2) how diverse the responders were.

In terms of the second factor, research has shown that diverse groups are often more creative, innovative, and productive than homogenous groups. Based on this understanding, ConocoPhillips Network leaders frequently post questions to a number of networks rather keeping the question within a single network. And ConocoPhillips’ network structure has made it relatively simple for a network facilitator to post a question in related networks.

This following graph displays the relationships Kim found in his study.(click to enlarge)

As the chart on the left shows, Kim found the most learning occurs when responses have high levels of collective elaboration and when members of other networks join in the discussion. Interestingly, there is less learning when members of other networks provide answers but there is little or no collective elaboration. The same pattern occurs in terms of performance shown in the right hand chart, collective elaboration increases the value. Likewise diversity without discussion is less helpful.

I would add to Kim's findings a lesson I learned working with CompanyCommand; when the facilitator models collective elaboration by his or her own questions, others will follow suit. I would also note that since most organizations track metrics for their forums, e.g. number of questions, or the number of responses to a question, it would be useful to add a metric related the amount of collective elaboration that occurs in the forums.

I started with the question, “Are on-line discussion forums conversations?” My conclusions are that:
1. It is possible to have conversations in on-line forums.
2. But many on-line exchanges are not conversations, they are just declarations of each responder’s position
3. When conversations do occur in on-line forums the learning and performance results go up.

I have a great deal of interest in the topic of how to encourage greater collective elaboration in on-line discussion forums. I would be very interested in hearing from organizations that have found ways to increase conversation with their on-line forums.

A-Space (Facebook-like) Is Making a Difference Across the U.S. Intelligence Community

I'm posting the Executive Summary of a study I conducted with the Defense Intelligence Agency. You can read the full study - all 30 fascinating pages here.

Executive Summary of How A-Space is Shaping Analysts' Work

This report provides an overview of an exploratory scientific, qualitative study conducted by the Defense Intelligence Agency’s (DIA) Knowledge Laboratory in April- June of 2009. The ethnographic study based on twenty in-depth interviews with analysts identifies how analysts are using A-Space and what impact that use is having on their analytic work within DIA’s Directorate for Analysis (DI).

The primary benefit that A-Space brings to analytic work is a venue for seamlessly incorporating cognitive diversity to address complex analytic issues. Research indicates that cognitive diversity, (e.g. different perspectives, interpretations, heuristics, and predictive models) when applied to complex problems, consistently results in more and better solutions.

• A-Space is an environment in which analysts collaboratively create new meaning out of the diverse ideas and perspectives they collectively bring to an issue. Through this collaboration, analysts have the potential to break through long held assumptions to provide new ways of thinking about complex problems.

Analysts talk about A-Space as a setting where they are able to test out ideas and theories. Analysts, faced with a stream of data from a multitude of sources have the task of finding patterns in that data that will be useful to decision makers. Sensemaking is the term used for that human ability to make meaning out of a stream of seemingly unrelated information. It requires creating hypotheses and testing them against the data and interpretations of others. And conversation, with analysts who have diverse perspectives, is the most effective means to engage in the testing and revision of hypotheses. The peer-to-peer environment of A-Space provides a conversational format to engage in joint sensemaking, which may be the most significant function of A-Space in terms of being a human intellectual force multiplier. As analysts experience the benefits of on-line sensemaking conversations, over time, such conversations could become more prominent in the everyday discourse of analysts.

• Networked relationships on A-Space provide a stream of cognitively diverse information without the costly time investment that maintaining strong ties requires

Networking is highly valued by analysts because it provides access to new ideas and diverse perspectives. However maintaining networked relationships is a time consuming activity. The time cost limits the number of relationships an analyst can invest in. The most productive network relationships for gaining unique or novel ideas are not the close relationships among an analyst’s teammates (what sociologists call strong ties) because team/division members tend to have redundant knowledge. Rather the best source of new perspectives and ideas are colleagues in other directorates or agencies who have access to information from totally different sources or provide unique perspectives or interpretation of the existing data. But these more distant relationships (called weak ties) are the most costly to maintain because they require a planned interaction by phone/email/in-person. A-Space, however, reduces the time-cost of maintaining weak ties by providing analysts a way to establish and maintain relationships through frequent on-line interaction in an informal, peer-to-peer culture of mutual trust. A-Space also greatly increases the number of distant network members an analyst can interact with, again without increasing the time cost.

• A-Space is reinforcing the value of asking questions of colleagues, providing analysts the means to uncover flaws in their own data and reasoning

When analysts ask a question on A-Space they are making a tacit acknowledgement that, even if considered the expert on their topic, other analysts have perspectives and data that can add to their line of reasoning or uncover faults in that reasoning. This willingness to be shown to be wrong – to overcome the natural tendency to only seek confirmation - is facilitated by a culture of openness that analysts themselves have developed on A-Space. Through the on-line interaction, counterparts within and between agencies are coming to know each other as valued colleagues. There is a growing sense of trust and a willingness both to help and to receive help from each other.

• A-Space is providing analysts a set of new practices to: 1) build cross agency networks, 2) gain situational awareness, and 3) hold discussions of interpretation, that operate in parallel with the normal production process. These new practices constitute an emerging model that provides a level of cognitive diversity not previously available.

Analysts appear to be making use of A-Space for practices that were either not available or were very difficult to accomplish before A-Space was accessible – practices such as cross agency networking, situational awareness, discussions, and making available highly classified team products. However, practices like co-authoring and coordinating products, which are part of the normal production process are only rarely conducted through A-Space, even though the functionality is available to do so. Thus two models, operating in parallel, appear to be emerging. The challenge for analysts will be to merge these two models over time - bringing greater cognitive diversity into the normal production process and moving co-authoring and coordination more fully into A-Space.

• The non-hierarchal nature of A-Space, results in analysts feeling that it is okay to offer their thinking even if it is not completely formed or thought through, increasing the speed of product development by eliminating faulty hypotheses early on and quickly settling on those that are viable.

A-Space provides the means to test ideas and theories against knowledgeable others and to do so early in the formulation process. Early testing saves both time and effort that would have been spent on those ideas that do not measure up, and it lends support and expanded rationale for those that do. As valuable as offering thinking early on in the process is, it requires a safe environment in which to risk that thinking. A-Space provides such an environment by being peer- to-peer rather than hierarchal. Research indicates that peer-to-peer conversations are consistently more open and trusting than those that involve hierarchy. Discussions on A-Space can be vigorous and critical without being judgmental in tone. The informality of the language and the friendly banter create the feel of a conversation among equals.

The Incentive Question or Why People Share Knowledge

I get asked the incentive question a lot. How do we incentivise people to share their knowledge? The question is asked because when managers look around their organizations they don’t see much knowledge sharing going on. This is a serious concern, but I think it is the wrong question. The question is based on the assumption that people don’t want to share what they know and therefore require an incentive to get them to do it. And that assumption is inaccurate.*

A much more useful question is, “What causes people to be willing to share their knowledge with others?” I want to answer that question in this article, but first I want to tackle the assumption that people don’t want to share what they know.

People Willingly Share Their Knowledge
There is both anecdotal and research data to support that, as human beings, we willingly share what we know. To give a personal example, I lived in Washington DC for many years and daily I walked from home to my university office. It was a rare day when a visitor did not stop me to ask for directions; “Do you know where the Kennedy Center is? Where’s the Metro stop? Far from being annoyed, I was actually pleased to be asked. DC is a difficult city to find your way around in and my own extensive knowledge of the city was hard won. I was proud of my ability to navigate the city. In fact, my pride was such that sometimes if I saw a couple standing on a street comer with a map spread out between them, I would even offer, “May I help you find some place?” My guess is that everyone has a similar experience with a subject they know very well.

Eric Erickson,* the great development psychologists, claims that we are, by nature, a teaching species. He says, “parenthood is, for most, the first, and for many, the prime generative encounter; yet the continuation of mankind challenges the generative ingenuity of workers and thinkers of many kinds.” We would not have survived as a species if knowledge sharing were not basic to our nature.

One of the most interesting studies on knowledge sharing was conducted by Constant, Kiesler and Sproull.* One of their findings was that employees differentiated two kinds of knowledge sharing. One type was sharing products, for example, computer programs, or reports they had written. The second type of knowledge was what employees had learned from their own experience, for example, how to get around a certain bottle-neck in the system, or how to deal with a particularly tricky bug in a program. This second type of knowledge they regard as part of their identity – part of who they were as professionals.

They were willing to share both kinds of knowledge, but the motivation for sharing each differed greatly. The documents and programs they shared because they considered them the property of the company. But the second kind, their experiential knowledge, they shared because they gained some personal benefit from doing so. The personal benefit, however, was not money or the promise of a promotion. According to the study, “Experts will want to contribute to coworkers who need them, who will hear them, who will respect them and who may even thank them.”

Peer Recognition
As this study shows, the primary driver for sharing experiential knowledge is the respect and recognition of peers. It is hard to overestimate the psychic value peer recognition. In a previous post I told the story of a company commander who was moved to become a very activity contributor to a US Army community because he heard from a peer that an AAR he had posted “made a difference.”

There’s a great story about Eureka, the website where Xerox copy repair technicians share “fixes” they’ve developed while repairing the copy machines. The story is about one of the technicians who had sent in some fantastic “fixes” – he was everyone’s hero. When he walked into the auditorium at an annual meeting of technicians, his peers jumped up and started clapping and whistling – celebrating both his knowledge and his willingness to share – that’s peer recognition!

Recognition means the most to us when it comes from those who really know the subject – who know what they’re talking about. It’s great to have your boss think you’re a top performer, but chances are your boss doesn’t know enough about the technical part of your work to know how good you really are – but your peers do. For a peer to say, “The person that really understands that problem is Pete,” that comment Pete would regard as a sign of respect and one he would highly value.

Who I am as a professional is, in a very real sense, what I know - about leading a team, being an aeronautical engineer, an HR director, etc. We do not give that knowledge away lightly. Before we take the time and trouble to share that knowledge, we need some assurance that our knowledge will be treated with the respect it deserves, given thoughtful consideration, and that the recipient actually knows enough to make use of it. And that leads to the second reason people share their knowledge - relationship.

Relationship
The way a professional can know how someone will treat the precious commodity of her knowledge is to know that person well enough to make that judgment call. Relationships can be built through informal conversations, reading what another has written, working together on a team, or seeing the comments made in an on-line community. If a senior leader is committed to increasing knowledge sharing in her organization, then focusing on building relationships is the most important thing she can do.

Give yourself this test. Can you think of a time when someone you’ve worked with on a team asked you for advice and you turned a cold shoulder? Can you even think of a time when someone, with whom you enjoyed a brief conversation at a recent meeting, called to ask a question and you said, “Sorry I don’t have the time.” Fortunately, most of us cannot. If we have built a relationship with a peer, even a brief one, we will help if we can.

An organization can foster relationships many ways, but nearly all of them involve people being in conversation with each other. It is through conversation that we learn enough about the other to know the depth of their knowledge, where their strengths lie, what interests they have, and what they are passionate about.

Summary
Because our knowledge is so closely tied to our identity, it’s very important to each of us that our peers view us as knowledgeable and skillful. One of the major ways we demonstrate that to our peers is by sharing our knowledge with them. But sharing knowledge is risky, the other person may make a cutting remark about it or indicate that it’s not worth listening to. And sharing knowledge is time consuming, because to really respond to another’s question or problem takes the time to understand the issue and to explain in sufficient depth. So we rightly place conditions around sharing our in-depth knowledge. The relationships we build with others provide a needed level of confidence that our knowledge will be treated with respect. Knowledge sharing and relationship are coupled.

Rather than management asking, How do we incentivise people to share their knowledge? It would be more useful for management to ask, How do we develop relationships across the organization that will set in motion more knowledge sharing?

Erikson, E. (1961). The roots of virtue. in Julian Huxley, ed., The humanist frame. New

Constant, D., Kiesler, S., Sproull, L. (1994) What’s Mine Is Ours, or Is It? A study of attitudes about information sharing. Information Systems Research 5:4 400-421.

*Caveat: It is altogether possible to defeat the human tendency to share knowledge. One sure way is to create a situation where in order for one person to succeed the other has to lose. Too many organizations create those conditions with performance management systems that rank order or pit one person against another.

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