Knowledge insights from Atul Gawande’s Reith lectures

Annually since 1948, the BBC has broadcast a short series of lectures named in honour of its founder, Lord Reith. This year’s series is being given by Atul Gawande. Although his subject is the nature of progress and failure in medicine, the two lectures delivered thus far resonate way beyond that field. I want to pick out a few points here from those two lectures in that they relate to the way we deal with knowledge in our work. The remaining two lectures have a slightly different focus, so I may look at those in a later post.

Lecture 1: Why Do Doctors Fail?

(Audio | Transcript)

At the heart of Gawande’s first lecture is an article published in the first issue of the Journal of Medicine and Philosophy in 1976: “Toward a Theory of Medical Fallibility” by Samuel Gorovitz and Alasdair MacIntyre. As Gawande summarises:

They said there are two primary reasons why we might fail. Number one is ignorance: we have only a limited understanding of all of the relevant physical laws and conditions that apply to any given problem or circumstance. The second reason, however, they called “ineptitude”, meaning that the knowledge exists but an individual or a group of individuals fail to apply that knowledge correctly.

In addition to ignorance and ineptitude, however, Gorovitz and MacIntyre identified a third cause of failure:

they said that there is necessary fallibility, some knowledge science can never deliver on. They went back to the example of how a given hurricane will behave when it will make landfall, how fast it will be going when it does, and what they said is that we’re asking science to do more than it can when we ask it to tell us just what exactly is going on. All hurricanes are ones that follow predictable laws of behaviour but no hurricane is like any other hurricane. Each one is unique. We therefore cannot have perfect knowledge of a hurricane short of having a complete understanding of all the laws that describe natural processes and a complete state description of the world, they said. It required, in other words, omniscience, and we can’t have that.

This necessary fallibility is akin to, if not the same as, the complexity that I described in an earlier blog post here.

Interestingly, Gawande chooses not to focus on necessary fallibility, but on the other two components. In particular, he is concerned that there is an uneven distribution of capabilities:

But the story of our time, I think, has now become in a unique way as much a story about struggling with ineptitude as struggling with ignorance. You go back a hundred years, and we lived in a world where our futures were governed largely by ignorance. But in this last century, we’ve come through an extraordinary explosion of discovery and then the puzzle has become not only how we close the continuing gaps of ignorance open to us but also how we ensure that the knowledge gets there, that the finger probe is on the right finger.

There’s a misconception I think about global health. We think global health is about care in just the poorest parts of the world. But the way I think about global health, it’s about the idea of making care better everywhere – the idea that we are trying to deploy the capabilities that we have discovered over the last century, town by town, to every person alive.

I think something similar is at foot in relation to legal knowledge. Those of us who work on improving knowledge within law firms often focus on the things that look hard — understanding new cases and legislation, for example — but in fact clients would get better value if their lawyers thought more carefully about the laws and processes that they take to be straightforward. Reducing ineptitude within firms is arguably more important than attempting to eliminate legal ignorance. Equally, there is much to be gained from spreading awareness of the law more widely outside law firms. This is an area where I see a number of technology-based enterprises at work, as well as the work of the National Archives in opening up the UK’s legislative archive.

Lecture 2: The Century of the System

(Audio | Transcript)

Atal Gawande’s second lecture draws heavily on his book The Checklist Manifesto. I thought I had already written about this book on the blog, but it turns out I haven’t. It is probably too late to do that at length now, since the concept has found its way deep into business culture. For example, we put it at the heart of some of the risk and quality work that I supported in my last firm.

What the lecture brings out is an emphasis on the checklist as a systematic tool, rather than a personal guide. This is present in the book as well, but when one hears Gawande speak the focus is unavoidable.

One of my colleagues said that “we are graduating from the century of the molecule to the century of the system.” And by that what he meant was that we’ve gained an enormous amount in the last century by focusing on reducing problems to their atomic particles – you know discovered the gene that underlies disease or the neuron that underlies the way our brain works or you know the super specialist that can deliver on a corner of knowledge – but what we’re discovering is that we graduate into the future, we are faced with a world where it’s how the genes connect together that actually determine what our diseases actually do. It’s how the neurons connect together and form networks that create consciousness and behaviour, and it’s in fact how the drugs and the devices and the specialists all work together that actually create the care that we want. And when they don’t fit together, we get the experience we all have – which is that care falls apart. The basics end up being known, but they’re not followed.

And so we were approached by the World Health Organisation several years ago with a project to try to reduce deaths in surgery. I thought how can you possibly do that? But it was in exactly the same kind of problem – the basics were known but not necessarily followed. And so we worked with a team from … from the airline industry to design what emerged as just a checklist – a checklist though that was made specifically to catch the kinds of problems that even experts will make mistakes at doing. Most often basically failures of communications. The checklist had some dumb things – do you have the right patient, do you have the right side of the body you’re operating on, have you given an antibiotic that can reduce the infections by 50 per cent, have you given it at the right time? But the most powerful components are does everybody on the team know each other’s name and role, has the anaesthesia team described the medical issues the patient has? Has the surgeon briefed the team on the goals of the operation, how long the case will take, how much blood they should be prepared to give? Has the nurse been able to outline what equipment is prepared? Are all questions answered? And only then do you begin.

The outcome of this work was a huge reduction in complication rates (down 35%) and deaths (down 47%). The system has been shown to have saved 9000 lives in Scotland alone.

The lectures are followed by an opportunity for the audience to ask questions, and it is here that some of the most telling points were brought out. In response to a question from an operations manager at Heathrow Airport, Gawande highlighted a point about complexity and the limitations of expecting everyone to know their own job.

In fact in order to even come at how we would attack this question in surgery, what we did was we brought in the lead safety engineer from Boeing to come with us. He didn’t know anything about healthcare, but when he saw the way that we even approached the problem of improving outcomes in surgery, he was sort of baffled, you know, that he would watch how I went into an operating room and I’d go into an operating room and I’d just start operating. And he said, “Hold on a minute. Is this really what you do? You don’t … Have you made a plan with every …” “Everybody knows what to do. They all know what to do. You guys know what to do, right?” “Oh yeah, yeah, yeah, we know what to do.” And then we’d watch one thing fall through the cracks and then another and then another. It took him only a moment to step back and say, “You all need some basic communication systems around the idea that a team has to be effective at what they’re doing.” So I think that there are lessons very much coming from other fields.

Here’s the big difference. There are two people in a cockpit trying to make something happen and in many clinical environments it’s many more than that. My mother went for a total knee replacement and I counted the number of people who walked in the room in three days and it was 66 different people. And so the complexity of making 66 people work together – you know you’d have the physical therapist walk in in the morning and they’d say, “What are you doing in bed? You should be out of bed.” And the physical therapist would come in the afternoon and it would be a different person and they’d say, “What are you doing out of bed? You should be in bed.” This is still where we are.

And responding to a suggestion that checklists might ossify and hinder innovation:

That’s precisely the danger. So there’s the bad checklist and the good checklist, right? So the bad one is one that turns people’s brains off. More often than not, the effective checklist – ask people questions that they have to discuss and get their ideas forward – and that was out of a scientific process that we identified and it’s made in ways to help an expert be even better at what they do.

For me, those are the two lasting insights from the lecture. First, checklists need to be as much about communication as they are about giving instructions. And, second, checklists should be structured to draw out additional thought and contributions by the team using them. Both of these insights can usefully inform practice in a range of areas (including the law) and would be sensibly applied in the generation of knowledge materials — whether those come in the form of checklists or otherwise.

Learning and developing

One of the things that comes across clearly in both of these lectures is a commitment to nuanced learning. Like most of his fellow physicians, Gawande is clearly keen on increasing his personal knowledge within his field and beyond. Both lectures depend on insights from other people’s published research, and Gawande shows how those insights have more general application. However, it is obvious that he isn’t interested just in the knowledge. He wants to be able to to express ideas clearly to others, and he does this really well with a coherent narrative thread running through each lecture (this continues in the later lectures too). Finally, he is alert to the way knowledge informs practice. The second lecture is based on a paper describing treatment procedures for hypothermic victims of drowning. However, Gawande extracts from this highly-specialised situation a set of principles that might be relevant to any complex treatment.

Gawande’s approach thus has the following characteristics:

  • Breadth of input
  • Evidence-based narrative
  • Thoughtful generalisation
  • Relevant conclusions

Each of those factors increases the immediate and lasting value of the final product to the listener or reader.

Thinking back to some of the knowledge content for which I have been responsible in the past, I am not sure that much of it was as well structured as Gawande’s lectures. As a result it probably had much less value than it could have done — certainly not lasting value.

It’s a good standard to aim for.

Asking better questions, getting better insight

Over the past few months I have been using a model that Nick Milton shared on his blog, to help people understand that the knowledge activities they have traditionally espoused only tell half the story.

I have reservationas about the tacit/explicit distinction, but that is irrelevant for now. The key thing for me is that there is a clear and meaningful difference between systems and tools that push knowledge to people and the activities that develop people’s ability to pull knowledge at the moment of need.

In another post, Nick describes advising an organisation which had over-emphasised the push side of the table. I think many law firms are in this position now. We have developed vast banks of precedents, practice notes, process guides, checklists and so on; and we have encouraged in our lawyers a dependency on these things. To a point, this is all good. These tools help people to dispose efficiently of the work that should not require great thought. But what about those areas where great thought is required. How do we build people’s capability to get to the insight and expertise that will help them solve the trickier problems that clients bring?

We can throw technology at the problem again — search engines will allow people to draw on the vast pool of work that has already been done. Sometimes that will disclose a really useful document that contains just the right information to help the lawyer arrive at a suitable answer. More often, though, it will produce nothing at all or many documents none of which actually help directly. Those many documents may, however, help to identify the right people to ask for help.

So it comes back to asking. Nick Milton has made this point in a couple of posts on his blog this week. The more recent post, “Asking in KM, when and how?”, identifies a number of situations in which asking might be institutionalised: communities of practice, after action reviews, and retrospects; but it doesn’t get to the heart of the question. What does good asking look like?

Fortunately, help is at hand. (The topic must be in the air at the moment for some reason.) Ron Ashkenas, in an HBR blog post, “When the Help You Get Isn’t Helpful“, explores what happens when someone shares their knowledge in a way that is actually useless.

Consider John, an account executive who is contemplating how to expand into a new market segment — one that is wrought with regulatory challenges. With a puzzled look on his face, he walks past Samantha, who asks, “Are you okay?” John responds, “Not really, I’m trying to figure out how to gain access for more of our products into Latin America.” Samantha immediately runs to her office and returns with a 100-page analytical report detailing the region. She then spends the next ten minutes going over a how-to guide on conducting market research. Out of respect to Samantha, John patiently listens. But despite her good intentions, Samantha’s input is counterproductive. John might have benefited from Samantha’s time if she had focused on solving his regulatory conundrum. Instead, John walks away feeling even more frustrated and perplexed.

What happened here? John presented Samantha with a problem, and she offered help. I suspect this kind of unfocused response is common. I know I have been guilty of it in the past, and I suspect I will be again in the future. The difficulty is that people are actually very poor at asking questions. Why that might be is a conundrum for a different time. Fortunately, Ron Ashkenas has some guidance to get better at asking.

Target your requests. Instead of asking whoever is available, intentionally target certain individuals. Create a list of people who have access to resources, information, and relevant experience about your problem. Expand your list to include friends and colleagues who tend to challenge the norm and see the world differently. Make a point of including people who are likely to have useful views but you might hesitate to approach because you think they are too busy or wouldn’t be interested.

Frame your question. Before asking for input, figure out what you really need: What kind of advice are you looking for? What information would be useful? Are there gaps in your thinking? Then consider how to frame your question so that you solicit the right advice.

Redirect the conversation. If the person offering advice jumps to conclusions, be prepared to redirect them. Most people will not be offended if you politely refocus them. For instance, had John interrupted Samantha’s lecture on market research by saying, “The issue isn’t our understanding of the market, it’s how to deal with the area’s regulatory restrictions. That’s where I could use some help,” Samantha could have spent the next ten minutes firing off some useful ideas.

This doesn’t feel like rocket science. Frequently, however, I see people asking quite open-ended questions in the hope that something useful will pop up. I suspect that what actually happens is that those with the knowledge to assist don’t answer precisely because the question is too vague. Yet again, the key to good a outcome here is the same as it is in many other contexts. Careful preparation and clarity of scope will generate the answer you need. (It is also important to be comfortable with the possibility that there is no answer. If you are precise and clear, the fact that no answer is forthcoming is much more likely to be an accurate reflection of there being no answer available at all.)

I think this is an iterative process:

  • Work out exactly what you need to know. What is the gap in your understanding that needs to be filled in order to resolve the issue raised by your client?
  • Who is the best person to answer that question? Do you know that person already, or will you need to seek advice from others? Plan how to ask the right question to identify that person.

Repeat until satisfied…

Knowledge sharing: it may not be what you think it is

John Tropea is one of my top Twitter friends for sharing interesting links and insights. Yesterday, he unearthed a great blog post from Patrick Lambe dating from 2006 (“If We Can’t Even Describe Knowledge Sharing, How Can We Support It?“). Patrick’s post starts calmly enough:

A combination of two very different incidents reminded me this week of just how incompetent we still are in KM at capturing the complexity, richness and sophistication of human knowledge behaviours. In the first incident I was asked to do a blind review of an academic paper on knowledge sharing for a KM conference. In the second, knowledge sharing was very much a matter of life and death. Although they shared a common theme, they might as well have represented alien universes.

From there, he becomes a bit more immoderate:

Let’s look at the conference paper first. After working my way through the literature review (a necessary evil), I started into the research proposal with my stomach starting to knot up and a growing sense of incredulity.

Although the authors had adopted Davenport & Prusak’s perfectly respectable definition of knowledge as a “fluid mix of framed experience, values, contextual information, and expert insight” it was becoming increasingly apparent as I worked my way into the paper that what they really meant by “knowledge sharing” was confined to contributing to and consuming from an online KM system. The research being described was designed to identify the factors that would indicate propensity for or against said behaviours. A knowledge sharing system that could, theoretically, be engineered.

Shame on them. After a good decade of practical effort and research focused on KM, how can people still think so mechanically and bloodlessly?

Justly immoderate, I think. Read on to see why.

Tonderghie Steading

It has to be right that knowledge in action is more valuable to organisations than inactive knowledge. Rory Stewart’s walking and engaging with people, as I wrote yesterday, shows one way in which high quality insight into complex systems can come from simple interactions rather than formal organised learning and knowledge. This is a point that Patrick made at greater length in an excellent paper he wrote in 2002 called “The Autism of Knowledge Management” (it’s a 23-page PDF downloadable from the linked blog post).

It depresses me that I have only just discovered this paper. Patrick wrote an incredibly useful critique of some traditional and ingrained organisational attitudes to e-learning and knowledge sharing. It should be much more widely known.

Here is his starting point:

There is a profound and dangerous autism in the way we describe knowledge management and e-learning. At its root is an obsessive fascination with the idea of knowledge as content, as object, and as manipulable artefact. It is accompanied by an almost psychotic blindness to the human experiences of knowing, learning, communicating, formulating, recognising, adapting, miscommunicating, forgetting, noticing, ignoring, choosing, liking, disliking, remembering and misremembering.

Once he has expanded on this, carefully defining what he means by ‘autism’ and ‘objects’ in this context, Patrick then presents and deals with five myths that arise as a result of this way of thinking. These are the myths of reusability, universality, interchangeability, completeness, and liberation. Of these, the one that struck me most was the myth of completeness:

The myth of completeness expresses the content architects’ inability to see beyond the knowledge and learning delivery. Out of the box and into the head, and hey presto the stuff is known. The evidence for this is in the almost complete lack of attention to what happens outside the computerised storage and delivery mechanism – specifically, what people do with knowledge, how it transitions into action and behaviour. How many people in knowledge management are talking about synapses, or the soft stuff that goes on in people’s heads? Is it simply assumed, that once the knowledge is delivered, it has been successfully transferred?


Knowledge only has value if it emerges into actions, decisions and behaviours – that much is generally conceded. But few content-oriented knowledge managers think through the entire lifecycle of the knowledge objects they deal in. Acquiring a knowledge artefact is only the first stage of what’s interesting about knowledge. We don’t truly know until we have internalised, integrated into larger maps of what we know, practised, repeated, made myriad variations of mistake, built up our own personalised patterns of perception and experience.

I can think of few more succinct and clear expressions of the process of knowing. In the organisational context, we need to be sure that everyone takes responsibility for developing their own knowledge — they cannot just plug themselves into a knowledge system or e-learning package. This statement shows why. The impact of this personal responsibility becomes clear within the section on the myth of interchangeability, where Patrick makes a valuable point about information and insight that resonated especially given my blog post from yesterday.

Beyond a basic informational level (and value added knowledge and learning need to go far beyond basic informational levels), when I have a specific working problem such as how to resolve a complex financial issue, the last thing I want is a necklace of evenly manufactured knowledge nuggets cross-indexed and compiled according to the key words I happen to have entered into the engine. Google can give me that, in many ways more interestingly, because it will give me different perspectives, different depths and different takes.

What really adds value to my problem-solving will be an answer that cuts to the chase, gives me deep insight on the core of my problem, and gives me light supporting information at the fringes of the problem, with the capability to probe deeper if I feel like it. Better still if the answer can be framed in relation to something I already know, so that I can call more of my own experience and perceptions into play. Evenness and interchangeability will not work for me, because life and the situations we create are neither even, nor made up of interchangeable parts.

We do have an evolved mechanism for achieving such deep knowledge results: this is the performance you can expect from a well-networked person who can sustain relatively close relationships with friends, colleagues and peers, and can perform as well as request deep knowledge services of this kind.

I suspect that (whether inside our organisations or otherwise) we can all identify people whose personal networks add significant value to their work and those around them. (And probably plenty whose silo mentality brings problems rather than focus.)

In his conclusion, Patrick presents “six basic principles that seem to work consistently in our knowledge and learning habits; principles that knowledge management and e-learning technologies need to serve.” These are:

  1. Highly effective knowledge performers prefer knowledge fragments and lumps to highly engineered knowledge parts.
  2. Parts need to talk to their neighbours.
  3. The whole is more important than the parts.
  4. Knowledge artefacts provide just enough to allow the user to get started in the real world.
  5. Learning needs change faster than learning design.
  6. Variety is the spice of life.

I need to read this section again — it didn’t resonate as well for me as the rest of the paper. That said, reading the paper again will be a delight rather than an imposition. I recommend it highly to anyone with an interest in knowledge and learning processes, and the systems we create to support them.

How different is the social web (and why)?

When I spoke at the Headshift insight event back in September, one of the points I made was that new forms of interaction on the web might feel subtly different from older ones. A couple of recent blog posts have called this to mind again. So here are some of my thoughts.

Barn Owl in flight

Over at the 3 Geeks… blog, Lisa Salazar argues that there is nothing new about social media.

Social networking isn’t new. I t has been around since the very first introduction to the internet. Just like Alexander Graham Bell, the first sign of life on the internet was an communication between UCLA and Stanford computers in 1969. And that certainly was social–the internet was built in response to the threat of USSR dropping bombs onto the US. Not exactly friendly but certainly social.

Through the internet, I have met people from all around the world. As I like to say on my job, I have traveled “virtually” everywhere.

Like Lisa, I have been online in one way or another for many years, but I feel that things have changed significantly between my early experiences and now. (This may just be a function of who we are — it is quite possible that Lisa invested better in her early online community than I did — so we should just be regarded as two anecdotal data-points.)

It is true that, as Lisa points out, people have built communities using e-mail lists, IRC and Usenet (as well as the closed networks such as Prodigy, AOL, Compuserve, The WELL, CIX, and all the others) since the late 1980s or early 1990s.  Those networks have been used to create content and connect people, just as we do now with the plethora of Web2.0 tools. Where is the difference? I am still trying to work it out.

I used to have an interest in Internet governance. I was a member of the CYBERIA-L mailing list (now apparently defunct [Update April 2015: I have since learned that the list has been resuscitated.]); I spoke at conferences in the US and UK; I wrote journal articles. But I never felt a connection with the governance community in the way that I do with the KM community now. It was as if we were all operating in our own focused silos. (That may also have been a result of the academic ivory towers that many of us inhabited.) I also pursued personal interests in Usenet newsgroups and on CIX. Those activities rarely spilled over into my work interests. I think that partitioning of lives is a hint as to how the old online world differs from the new one.

By contrast, my Web2.0 journey has been more open and fruitful. Apart from a couple of abortive attempts at blogging (I had no real focus, so they withered away very quickly), I started as most people do — reading other blogs and then graduating to comments. Once the comments became longer I felt I had found my voice and it was time to start blogging. At the same time, Facebook and LinkedIn gave me connections with and insights into people on whose blogs I had commented. As people started reacting to my blog posts with their comments and on their own blogs, I found that I was part of a real community. That sense of community has only deepened over time and with more interactions via Twitter and the like. I have even met some people face to face.

The difference between then and now, for me, is that the variety of interactions and ‘places’ where I engage with this community has broken down the silos that I experienced in the past. Because it is impossible not to see more facets of someone’s life and personality in their blogs, comments, tweets and status updates, it becomes easier to see them as real people — not just participants in a mailing list discussion, a conference or a newsgroup. We talk of work-life balance, but as Orson Wells points out early in this interview (from 0:48), there isn’t really a distinction.

Interviewer: Would you say that you live to work or work to live?

Welles: I regard working as part of life. I don’t know how to distinguish between the two; I know that one can and people do. I honestly think the best answer to that question that I can give you is that the two things aren’t separated in my mind.

Interviewer: There are people who devote everything to their work and have no life at all, but you have lived in a big way and you have worked in a big way…

Welles: And I don’t separate them. To me they are all part of the… Work is an expression of life for me.

For many of us, I think this is now true of our interactions with each other via online networks. Earlier this week, John Bordeaux provided a magnificent example of this in his post, “A Year Ago.” This time last year, John was laid off. His reaction was unconventional, but may offer a taste of future convention.

Using online social media tools, I stitched together a loose network of future colleagues and relationships to be tended.  Rather than broadcasting my increasingly urgent need for income, I trusted the network effect would work in time.

And it did.

Today I find myself engaged in meaningful and rewarding work to redesign a failed education system; working alongside leading professionals in innovation, public policy, and social change.

A year ago, I could not predict where I would be today.  Such is the nature of complexity and networks.  The theory suggested I should place myself in conversations, expand my connections into new networks, and a vocation would emerge.  (While I embrace the notion, I hope I never again have to conduct such experiments with my family’s financial health.)  I saw the traditional reaction to job loss as creating one-to-one intense conversations trying to match my talents to a company’s need.  Instead, I took this path.  Which amounted to no path at all, certainly not one any could predict.  To paraphrase Mr. Frost, that has made all the difference

The thing is, we knew that John was going through this. Not from his blog, but from changes in his LinkedIn status, from clues in his tweets. I hope he felt that the support we were able to give (often from a distance) was enough.

Ultimately, I think John’s experience shows that effective participation in online networks allows one to see a more authentic picture of people. Perhaps it is becoming less true that “on the Internet nobody knows you’re a dog.”

Making time

One of the things that can prevent us from getting things done is time, and how we manage it. Even without anyone else’s help (or hindrance), the average worker has to deal with procrastination and thinker’s block.


When those challenges are added to the need to work with colleagues and clients in a managed environment, things can get even more difficult. It is easy to get carried with the flow of life and work without really thinking about how best to use one’s time. Clients have demands to which lawyers are keen to respond, and most firms have financial imperatives that require particular approaches to work management. One consequence is that it can be hard to find time to do other things. In fact, in many organisations, this is intended. Tony Quinlan highlights the problem:

The drive for efficiency and perfect accounting for time is a constant anachronism — and far too much attention goes there, with added implications that activities like lunchbreaks and socialising were wasting time or somehow detrimental to the organisation. It’s often the implication that a work contract indicates a straight exchange of salary for workhours, and that any hours used at work for non-efficient work purposes is time stolen from the organisation. A very dangerous mindset to get into — and one that I’ve challenged more than a few times at conferences (typically, someone talking about email and spam and how many hours can be saved, with a spurious figure of what that means on the bottom line. Spare me.)

The contractual exchange of time for money is absolutely explicit in a law firm, where fee-earners record time in six-minute blocks, which then get converted into bills for clients. (I know many firms are moving away from the extreme version of that model, but very few of them have actually done away with the need to record time.) This can have a corrosive effect on any activities (including knowledge sharing) that are not “fee-earning” or which make it harder to reach time-related targets. Tony goes on to recall life in a more relaxed working environment.

I remember the tea trolley at Racal, back in the 1980s when I was testing radar systems.  It was actually a very useful social space — a specified point in the day when a bunch of people from different areas and specialisms met and talked as we waited to buy anything that I’d probably not allow my children to have today.

There’s a serious denigration of such social spaces these days, usually on efficiency or bottom-line grounds but (as in the case of smoking rooms) health ones too.  The value was in building cross-functional networks and communication channels and talking in non-formal environments.  And non-policed too, which made them more powerful for sharing problems or warnings of potential future issues.

Like Tony, I think the social aspect of work is crucial. If we make it harder for people to interact casually, we lose a real opportunity for creativity, change and insight. Gossip (of the non-malicious kind) almost always conveys more useful and actionable information than the formal corporate communications channels. (We need those too.)

[I]f the smoking room, the tea trolley, the staff canteen (and lunch hour) are all disappearing, where do we meet other parts of the organisation except in meetings?

A good question, Tony, and one which would frighten many people.

Do we have too many meetings? Possibly, and they may well be poorly focused as well. However, Paul Graham puts his finger on a more subtle issue. Different people are affected by meetings in different ways.

One reason programmers dislike meetings so much is that they’re on a different type of schedule from other people. Meetings cost them more.

There are two types of schedule, which I’ll call the manager’s schedule and the maker’s schedule. The manager’s schedule is for bosses. It’s embodied in the traditional appointment book, with each day cut into one hour intervals. You can block off several hours for a single task if you need to, but by default you change what you’re doing every hour.

When you use time that way, it’s merely a practical problem to meet with someone. Find an open slot in your schedule, book them, and you’re done.

Most powerful people are on the manager’s schedule. It’s the schedule of command. But there’s another way of using time that’s common among people who make things, like programmers and writers. They generally prefer to use time in units of half a day at least. You can’t write or program well in units of an hour. That’s barely enough time to get started.

When you’re operating on the maker’s schedule, meetings are a disaster. A single meeting can blow a whole afternoon, by breaking it into two pieces each too small to do anything hard in. Plus you have to remember to go to the meeting. That’s no problem for someone on the manager’s schedule. There’s always something coming on the next hour; the only question is what. But when someone on the maker’s schedule has a meeting, they have to think about it.

Where do lawyers fit into this model? Are they makers or managers? And clients — where do they fit? I don’t think there is a simple answer. However, it is a question we should always ask. Will this meeting that feels innocuous to me actually disrupt another person’s day to such an extent that they feel unable to spare the time to do something that might deliver more value instead (like chatting to someone as they make a cup of coffee)? Or, alternatively, is this meeting actually the time when something critical gets done — like finding out from a client exactly what their commercial objectives are?

Navigating the seven Cs of knowledge

It dawned on me today that a lot of our knowledge-related activities reflect, depend upon or contribute to things beginning with ‘C’. In that spirit, today’s post is brought to you by the letter C and the number 7.

On the rocks near Kilkee

In no particular order, here are the things I had in mind. Feel free to add more (or detract from these) in the comments. (And I apologise for inadvertently stealing a idea.)

Conversation. As mentioned in my last post, this is a critical part of knowledge sharing. Be aware, though, that this realisation is not enough:

simply being smarter isn’t the whole story. Clever people still do stupid things, often on a regular (or worse, repeated) basis. Wise people, on the other hand, change their ways.

Collaboration. Good collaboration may be a product of good knowledge sharing. It may even produce it. We need to be confident that what we think is collaboration really is that

So what is collaboration then? It’s when a group of people come together, driven by mutual self–interest, to constructively explore new possibilities and create something that they couldn’t do on their own. Imagine you’re absolutely passionate about the role that performance reviews play in company effectiveness. You team up with two colleagues to re-conceptualise how performance reviews should be done for maximum impact. You trust each other implicitly and share all your good ideas in the effort to create an outstanding result. You and your colleagues share the recognition and praise equally for the innovative work.

The important factor is mutual self-interest. When people create things they really want to create, and it is also good for the company, it energises and engages people like nothing else.

Communication. Don’t forget that this is not something you can judge for yourself. Good communication comes when someone else can understand what you say. They will judge whether you are communicating well. Empathy is required.

One way of talking that inhibits the exchange of knowledge is speaking with conviction. That may seem contrary to what we’ve all learned in communication and leadership workshops, where one of the lessons often taught is to speak with confidence- “sound like you mean it”. Yet, as I examine conversations in the work setting, stating an idea with conviction tends to send a signal to others that the speaker is closed to new ideas. When speaking with conviction people sound as though no other idea is possible, as though the answer is, or should be, obvious.

Connection. I can’t decide if this flows from the points above, or if it is a necessary pre-condition for them. The fact is, it is pervasive. Without good connections, we cannot function properly as good knowledge workers.

As the economy has worsened, there’s been some talk about eliminating “nice to have” functions such as KM.  Think again.  Without good matchmakers, it’s hard to have good matches.  Without good matches, it’s hard to have much productivity.

Creativity. This is not something that is reserved to highly-strung artists. We all need to think in interesting ways about the problems that we face. Unless we do so, we will just come up with the same old answers. And in many cases the same old answers are what created the problems in the first place.

…we need two processes, one to generate things we can’t think of in advance, and another to figure out which of the things we generate are valuable and are worth keeping and building upon. In science, the arts, and other creative activities, the ability to know what to throw away and what to keep seems to arise from experience, from study, from command of fundamentals, and—interestingly—from being a bit skeptical of preset intentions and plans that commit you too firmly to the endpoints you can envision in advance. Knowing too clearly where you are going, focusing too hard on a predefined objective, can cause you to miss value that might lie in a different direction.

Culture. We can use this as an easy escape: “I am doing what I can, but the culture doesn’t support me.” Yes, there are dysfunctional organisations which cannot accept that the world around them is changing. But we have a part to play in bringing a realisation that the wrong culture is wrong.

…the magic of the corporation (and the thing that makes the corporation the best problem-solving machine we have at our disposal) is that it can be all things to all people. Anthropology can help here because it understands that the intelligence of this complicated creature exists not just in the formal procedures and divisions of labor of the organization, but in also in the less official ideas and practices that make up the corporation. Once again, anthropology is about culture, but in this case the culture is the particular ideas and practices of a particular organization. Anthropology can help senior managers re-engineer their organizations.

Clients/customers. Why do we do this? It is easy to forget that the organisation does not exist for its own reasons. It exists to fulfil a purpose, and that purpose often means that there are consumers, customers or clients. When we know what they need, we are in a better position to understand what the business should deliver. That may hurt. Things would obviously run better if we didn’t have to worry about client demands, but that is just facetious.

This is a hard lesson for marketers, particularly technical marketers, to learn. You don’t get to decide what’s better. I do.

If you look at the decisions you’ve made about features, benefits, pricing, timing, hiring, etc., how many of them are obviously ‘better’ from your point of view, and how many people might disagree? There are very few markets where majority rule is the best way to grow.

Five continents

There are some additional things that are often linked to knowledge activities. I am not entirely sure about some of these. 

Change. This is often linked with culture. In addition, some knowledge management activities bring change with them. Doesn’t it seem odd (and a serious risk) that one project is supposed to bring about significant organisational change? Surely we should try and fit with what people are already doing?

Why won’t this work for you?

Capture/conversion. Traditionally, KM projects have focused on squeezing knowledge out of past actions, or in converting so-called tacit knowledge to explicit. John Bordeaux torpedoes both of these.

Lessons learned programs don’t work because they don’t align with how we think, how we decide, or even an accurate history of what happened.  Other than that – totally worth the investment. 


…it should now be evident that relating what we know via conversation or writing or other means of “making explicit” removes integral context, and therefore content.  Explicit knowledge is simply information – lacking the human context necessary to qualify it as knowledge.  Sharing human knowledge is a misnomer, the most we can do is help others embed inputs as we have done so that they may approach the world as we do based on our experience.  This sharing is done on many levels, in many media, and in contexts as close to the original ones so that the experience can approximate the original. 

Content. Otherwise known as “never mind the quality, feel the width.” Need I say more? We shouldn’t have been surprised by the Wharton/INSEAD research, but in case people still are:

The advice to derive from this research? Shut down your expensive document databases; they tend to do more harm than good. They are a nuisance, impossible to navigate, and you can’t really store anything meaningful in them anyway, since real knowledge is quite impossible to put onto a piece of paper. Yet, do maintain your systems that help people identify and contact experts in your firm, because that can be beneficial, at least for people who lack experience. Therefore, make sure to only give your rookies the password.

Control. David Jabbari nailed this one:

This trend is closely related to the shift from knowledge capture to knowledge creation. If you see knowledge as an inert ‘thing’ that can be captured, edited and distributed, there is a danger that your KM effort will gravitate to the rather boring, back-office work preoccupied with indexes and IT systems. This will be accompanied by a ritualized nagging of senior lawyers to contribute more knowledge to online systems.

If, however, you see knowledge as a creative and collaborative activity, your interest will be the way in which distinctive insights can be created and deployed to deepen client relationships. You will tend to be more interested in connecting people than in building perfect knowledge repositories.

Before we leave the alphabet, a quick word about ‘M’. If we dispose of the continental Cs above, what happens to measurement and management? That is probably enough in itself for another post, but for now a quick link to a comment of Nick Milton’s on the KIN blog will suffice:

Personally I think that dropping the M-word is a cop-out. Not as far as branding is concerned – you could call it “bicycle sandwich” as far as I am concerned, so long as it contained the same elements – but because it takes your attention away from the management component, and taking attention away from the management component is where many KM failures stem from.

Management is how we organise work in companies, and if we don’t organise it with knowledge in mind, we lose huge value. What doesn’t get managed, doesn’t get done, and that’s true for KM as much as anything else. See for more details.

What do we talk about when we talk about work?

For too long, I have had Theodore Zeldin’s little book, Conversation, on my wish-list. Prompted by a colleague’s comment I finally tracked a copy down. (It is out of print, but extremely easy to find on Amazon or Abebooks.) I wish I had done so sooner.

The word ‘conversation’ is scattered throughout this blog. Like many others, I have made the assumption that people at work converse readily with each other and that one of our challenges in making knowledge use at work better is to capture those conversations or their product in as simple a way as possible. Zeldin’s argument is that in fact we do not know how to converse.

[T]he more we talk, the less there is that we can talk about with confidence. We have nearly all of us become experts, specialised in one activity. A professor of inorganic chemistry tells me that he can’t understand what the professor of organic chemistry says. An economist openly admits that “Learning to be an economist is like learning a foreign language, in which you talk about a rational world which exists only in theory.” The Princeton Institute of Advanced Studies [sic], established to bring all the world’s great minds together, was disappointed to find that they did not converse much: Einstein, a colleague said, “didn’t need anybody to talk to because nobody was interested in his stuff, and he wasn’t interested in what anybody else was doing.”

No wonder many young people hesitate to embark on highly specialised careers which make them almost feel they are entering prison cells. … Even a BBC producer I met in the corridors of Broadcasting House, when I asked how his job was affecting his brain, said, “The job is narrowing my mind.”

Poor quality conversations don’t just happen at work — Zeldin sees the problem manifested (in different ways) in the family, in love and generally across our social interactions. Our focus, however, is work. What is Zeldin’s prescription?

Almost everyone says that the more varied the people they meet at work, the more fun it is, though often they exchange only a few words. But creativity usually needs to be fuelled by more than polite chat. At the frontiers of knowledge, adventurous researchers have to be almost professional eavesdroppers, picking up ideas from the most unobvious sources.

Zeldin’s book was published in 1998. A year later, David Weinberger made the link between good conversation and KM.

The promise of KM is that it’ll make your organization smarter. That’s not an asset. It’s not a thing of any sort. Suppose for the moment that knowledge is a conversation. Suppose making your organization smarter means raising the level of conversation. After all, the aim of KM was never to take knowledge from the brain of a smart person and bury it inside some other container like a document or a database. The aim was to share it, and that means getting it talked about.

This view puts KM at the heart of business since business is a conversation. … It’s not just that good managers manage by having lots of conversations… All the work that moves the company forward is accomplished through conversations —oral, written, and expressed in body language.

So, here’s a definition of that pesky and borderline elitist phrase, “knowledge worker”: A knowledge worker is someone whose job entails having really interesting conversations at work.

The characteristics of conversations map to the conditions for genuine knowledge generation and sharing: They’re unpredictable interactions among people speaking in their own voice about something they’re interested in. The conversants implicitly acknowledge that they don’t have all the answers (or else the conversation is really a lecture) and risk being wrong in front of someone else. And conversations overcome the class structure of business, suspending the org chart at least for a little while.

If you think about the aim of KM as enabling better conversations rather than lassoing stray knowledge doggies, you end up focusing on breaking down the physical and class barriers to conversation. And if that’s not what KM is really about, then you ought to be doing it anyway.

One of the ways that we can encourage good conversations is to expose people to a wider variety of experiences and inputs than they would expect for themselves. I mentioned in a previous post how important this is for designers. It is important for all professionals. Likewise, one of the key factors improving people’s collaboration and knowledge sharing through better conversations is familiarity with other people. In most workplaces, it is obvious that different groups engage with each other in different ways depending on how their physical proximity and familiarity. We can influence these factors architecturally.

Brad Bird (director of The Incredibles and Ratatouille) makes this point in an interview in The McKinsey Quarterly. Talking about the Pixar studio building, he said:

Steve Jobs basically designed this building. In the center, he created this big atrium area, which seems initially like a waste of space. The reason he did it was that everybody goes off and works in their individual areas. People who work on software code are here, people who animate are there, and people who do designs are over there. Steve put all the mailboxes, the meeting rooms, the cafeteria, and, most insidiously and brilliantly, the bathrooms in the center — which initially drove us crazy — so that you run into everybody during the course of a day. He realized that when people run into each other, when they make eye contact, things happen. So he made it impossible not to run into the rest of the company.

That’s great if one has the opportunity to influence architecture. What can we do otherwise? Zeldin might be able to come to the rescue. He has created The Oxford Muse: “A foundation to stimulate courage and invention in personal, professional and cultural life.” One of their projects is Muse Conversations:

At the invitation of the World Economic Forum held in Davos, we organised a Muse Conversation Dinner. The participants sat at tables laid for two, each with a partner they had never met before. A Muse Conversation Menu listed 24 topics through which they could discover what sort of person they were meeting, their ideas on many different aspects of life, such as ambition, curiosity, fear, friendship, the relations of the sexes and of civilisations. One eminent participant said he would never again give a dinner party without this Muse Menu, because he hated superficial chat. Another said he had in just two hours made a friend who was closer than many he had known much longer. A third said he had never revealed so much about himself to anybody except his wife. Self-revelation is the foundation on which mutual trust is built.

Even short of this, there are all sorts of small things that we can do. I think the important thing is to be aware (and to spread the awareness) that there are always more interesting things to know than what we already know, and that the people who know them are interesting in their own right. We just need to seek them out.

[A credit and an apology. The latter is due to Raymond Carver for corrupting a title of his. Mary Abraham is owed the former: colleague mentioned Conversation after I referred him to Mary’s post, “Confessions of a Corporate Matchmaker”, which underlines the point that those responsible for KM have an essential part to play in generating good connections from which good conversations should flow.]