Category Archives: Work

Choosing focus

I am part-way through a long post on personal knowledge management, which may see the light of day sometime this century. In doing so, I have been reflecting on something that I mention a lot in these posts: focus. I have been guilty of using the word in a very loose “I know it when I see it” fashion, but I am beginning to realise that a bit more explanation is in order.

Monochrome grass

I have an interest in photography, where focus is clearly a part of taking good pictures. However, there is more to it than that. Cameras come with a number of settings that affect the image — what is actually in focus. All of these settings require the photographer to make choices, which are similar to the choices we make when we talk about focus in a more general sense.

The first choice to be made is selection of a lens (or a zoom setting, for lenses with a variable focal length). Is the subject of the image distant or close? Do you want to concentrate on a single item or a large landscape? Variants of these questions can be used when considering personal focus as well. Is your objective finely detailed and distinct? If so, make sure you concentrate on it to the exclusion of other things (the telephoto or macro lens). Is it more diffuse — exploratory, perhaps? Then use a more inclusive approach (a wideangle lens).

Then there is a set of choices that are all interlinked — aperture, shutter speed, ISO (sensitivity or film speed, for non-digital photography). These need to be set to take into account the depth of field required (how much the subject stands out from the background or foreground), whether the subject is moving, and how much ambient light there is. Again, similar considerations can be borne in mind in a non-photographic context. Does your objective stand apart from other issues or do you need to consider it in a wider context? Are things moving fast, so quick action is required, or is a slower, more reflective pace acceptable? How much information is there on the topic — do you need highly sensitive receptors or is a strong filter preferable?

Once you have thought about all those variables, it is time to compose the image. Like everything else, careful thought about these preparatory questions improves the quality of the output. Equally, whether the output is good or not, it can be used to refine the initial settings before repeating the action. A plan-do-refine approach can also be useful in other contexts too. I can’t pretend to be a great photographer, but I do try to get better.

What do we do with knowledge?

Every now and then, I discover a new way in which my assumptions about things are challenged. Today’s challenge comes in part from the excellent commentary on my last post (which has been so popular that yesterday quickly became the busiest day ever here). I am used to discussions about the definition or usage of ‘knowledge management’, but I thought ‘knowledge sharing’ was less controversial. How wrong can one be?

Table at Plas Mawr, Conwy

The first challenge comes from Richard Veryard. His comment pointed to a more expansive blog post, “When does Communication count as Knowledge Sharing?” Richard is concerned that the baggage carried by the word ‘sharing’ can be counter-productive in the knowledge context.

In many contexts, the word “sharing” has become an annoying and patronizing synonym for “disclosure”. In nursery school we are encouraged to share the biscuits and the paints; in therapy groups we are encouraged to “share our pain”, and in the touchy-feely enterprise we are supposed to “share” our expertise by registering our knowledge on some stupid knowledge management system.

But it’s not sharing (defined by Wikipedia as “the joint use of a resource or space”). It’s just communication.

I agree that if people construe sharing as a one-way process, it is communication. (Or, more accurately, ‘telling’, since effective communication requires a listener to do more than hear what is said.) In a discussion in the comments to Richard’s post, Patrick Lambe defends his use of ‘sharing’ and Richard suggests that knowledge ‘transfer’ more accurately describes what is happening. I also commented on the post, along the following lines.

I can see a distinction between ‘sharing’ and ‘transfer’, which might be relevant. To talk of transferring knowledge suggest to me (a) that there is a knower and an inquirer and that those roles are rarely swapped, and (b) that there needs to be a knowledge object to be transferred. (As Richard puts it, “a stupid knowledge management system” is probably the receptacle for that object.)

As Patrick’s blog post and longer article make clear, the idea of the knowledge object is seriously flawed. Equally, the direction in which knowledge flows probably varies from time to time. For me, this fluidity (combined with the intangible nature of what is conveyed in these knowledge generation processes) makes me comfortable with the notion of ‘sharing’ (even given Richard’s playgroup example).

In fact, I might put it more strongly. The kind of sharing and complex knowledge generation that Patrick describes should be an organisational aspiration (not at all like ‘sharing pain’), while exchange or transfer of knowledge objects into a largely lifeless repository should be deprecated.

I think Richard’s response to that comment suggests that we are on the point of reaching agreement:

I am very happy with the notion of shared knowledge generation – for example, sitting down and sharing the analysis and interpretation of something or other. I am also happy with the idea of some collaborative process in which each participant contributes some knowledge – like everyone bringing some food to a shared picnic. But that’s not the prevailing use of the word “sharing” in the KM world.

This was a really interesting conversation, and I felt that between us we reached some kind of consensus — if what is happening with knowledge is genuinely collaborative, jointly creating an outcome that advances the organisation, then some kind of sharing must be going on. If not, we probably have some kind of unequal transfer: producing little of lasting value.

Coincidentally, I was pointed to a really interesting discussion on LinkedIn today. (Generally, I have been deeply unimpressed with LinkedIn discussions, so this was a bit of a surprise.) The question at the start of the discussion was “If the term “KM” could get a do-over what would you call the discipline?” There are currently 218 responses, some of which range into other interesting areas. One of those areas was an exchange between Nick Milton and John Tropea.

Nick responded to another participant who mentioned that her organisation had started talking about ‘knowledge sharing’ rather than ‘knowledge management’.

Many people do this, but I would just like to point out that there is a real risk here – that sharing (“push”) is done at the expense of seeking (“pull”). The risk is you create supply, with no demand.

See here for more detail: http://www.nickmilton.com/2009/03/knowledge-sharing-and-knowledge-seeking.html

The blog post at the end of that link is probably even more emphatic (I will come back to it later on). John had a different view:

Nick you say “sharing (“push”) is done at the expense of seeking (“pull”). The risk is you create supply, with no demand.”

This is true if sharing is based on conscription, or not within an ecosystem (sorry can’t think of a more appropriate word)…this is the non-interactive document-centric warehousing approach.

But what about blogging experiences and asking questions in a social network, this is more on demand rather than just-in-case…I think this has more of an equilibrium or yin and yang of share and seek.

People blog an experience as it happens which has good content recall, and has no agenda but just sharing the raw experience. Others may learn, converse, share context, etc…and unintentionally new information can be created. This is a knowledge creation system, it’s alive and is more effective than a supply-side approach of shelving information objects…and then saying we are doing KM…to me KM is in the interactions. We must create an online environment that mimics how we naturally behave offline, and I think social computing is close to this.

Nick’s response was interesting:

John – “But what about blogging experiences and asking questions in a social network, this is more on demand rather than just-in-case”

Asking questions in a network, yes (though if I were after business answers, i would ask in a business network rather than a social network). Thats a clear example of Pull.

Blogging, no, I have to disagree with you here. I am sorry – blogging is classic Push. Its classic “just in case” someone should want to read it. Nobody “demands” that you blog about something. You are not writing your blog because you know there is someone out there who is waiting to hear from you – you write your firstly blog for yourself, and secondly “just in case” others will be interested.

Blogging is supply-side, and it’s creating stuff to be stored. OK, it is stored somewhere it can be interacted with, and there is a motivation with blogging which is absent with (say) populating an Intranet, but it is stll classic supply-side Push. Also it is voluntary push. The people who blog (and I include myself in this) are the ones who want to be heard, and that’s not always the same as “the ones who need to be heard”. Knowledge often resides in the quietest people.

This exchange puts me in a quandary. I respect both Nick and John, but they appear to be at loggerheads here. Can they both be right? On the one hand, Nick’s characterisation of supply-side knowledge pushing as something to be avoided is, I think correct. However, as I have written before, in many organisations (such as law firms), it is not always possible to know what might be useful in the future. My experience with formal knowledge capture suggests that when they set out to think about it many people (and firms) actually rate the wrong things as important for the future. They tend to concentrate on things that are already being stored by other people (copies of journal articles or case reports), or things that are intimately linked to a context that is ephemeral. Often the information stored is fairly sketchy. One of the justifications for these failings is the the avoidance of ‘information overload’. This is the worst kind of just-in-case knowledge, as Nick puts it.

I think there is a difference though when one looks at social tools like blogging. As Nick and John probably agree, keeping a blog is an excellent tool for personal development. The question is whether it is more than that. I think it is. I don’t blog here, nor do I encourage the same kind of activity at work because someone might find the content useful in the future. I do it, and encourage it, because the activity itself is useful in this moment. It is neither just-in-case nor just-in-time: it just is.

In the last couple of paragraphs, I was pretty careless with my use of the words ‘information’ and ‘knowledge’. That was deliberate. The fact is that much of what we call KM is, in fact, merely manipulation of information. What social tools bring us (along with a more faceted view of their users) are really interesting ways of exposing people’s working processes. As we learnt from Nonaka all those years ago, there is little better for learning and development of knowledge than close observation of people at work. (Joining in is certainly better, but not always possible.) What we may not know is where those observations might lead, or when they might become useful. Which brings me to Nick’s blog post.

We hear a lot about “knowledge sharing”. Many of the knowledge management strategies I am asked to review, for example, talk about “creating a culture of knowledge sharing”.

I think this misses the point. As I said in my post about Push and Pull, there is no point in creating a culture of sharing, if you have no culture of re-use. Pull is a far more powerful driver for Knowledge Management than Push, and I would always look to create a culture of knowledge seeking before creating a culture of knowledge sharing.

Nick’s point about knowledge seeking is well made, and chimes with Patrick Lambe’s words that I quoted last time:

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.

Requesting, seeking, performing: all these are aspects of sharing. Like Richard Veryard’s “traditional KM” Nick characterises sharing as a one-way process, but that is not right — that is the way it has come to be interpreted. Sharing must be a two-way process: it needs someone to ask as well as someone who answers, and those roles might change from day to day. However, Nick’s point about re-use is a really interesting one.

I suggested above that some firms’ KM systems might contain material that was ultimately useless. More precisely, I think uselessness arises at the point where re-use becomes impossible because the material we need to use is more flawed than not. These flaws might arise because of the age of the material, combined with its precise linkage with a specific person, client, subject and so on. Lawyers understand this perfectly — it is the same process we use to decide whether a case is a useful precedent or not. Proximity in time, matter or context contributes significantly to this assessment. However, an old case on a very different question of law in a very different commercial context is not necessarily useless.

One of the areas of law I spent some time researching was the question of Crown privilege. A key case in that area involved the deportation of a Zairean national in 1990. In the arguments before the House of Lords, the law dating back to the English Civil War was challenged by reference to cases on subjects as varied as EC regulation of fisheries and potato marketing. That those cases might have been re-used in such a way could not have been predicted when they were decided or reported.

In many contexts, then, re-use is not as clear-cut an issue as it may appear at first. My suspicion is that organisations that rely especially highly on personal, unique, knowledge (or intellectual capital) should be a lot more relaxed about this than Nick suggests. His view may be more relevant in organisations where repetitive processes generate much more value.

On the just-in-case problem, I think social tools are significantly different from vast information repositories. As Clay Shirky has said, what we think is information overload is actually filter failure. Where we rely solely on controlled vocabularies and classification systems, our capability to filter and search effectively runs out much sooner than it does when we can add personalised tags, comments, trackbacks, knowledge about the author from other sources, and so on. Whereas repositories usually strip context from the information they contain, blogs and other social tools bring their context with them. And, crucially, that context keeps growing.

Which brings me, finally, back to my last post. One of the other trackbacks was from another blog asking the question “What is knowledge sharing?” It also picks up on Patrick’s article, and highlights the humanity of knowledge generation.

…we need to think laterally about what we consider to constitute knowledge sharing. This morning I met some friends in an art gallery and, over coffee, we swapped anecdotes, experiences, gripes, ideas and several instances of ‘did you hear about?’ or ‘have you seen?’… I’m not sure any of us would have described the encounter as knowledge exchange but I came away with answers to work-related questions, a personal introduction to a new contact and the germ of a new idea. The meet up was organised informally through several social networks.

The key thing in all of this, for me, is that whether we talk of knowledge sharing, transfer, or management, it only has value if it can result in action: new knowledge generation; new products; ideas; thoughts. But I think that action is more likely if we are open-minded about where it might arise. If we try and predict where it may be, and from which interactions it might come, I think it is most probable that no useful action and value will result in the long term.

We are all in this together

A couple of links to start with: John Stapp and “Has ‘IT’ Killed ‘KM’?

Picture credit: Bill McIntyre on Flickr

I don’t have much truck with heroes. Many people do great things, in the public eye and otherwise, and it seems invidious to single certain individuals out mainly because they are better known than others who are equally worthy of credit. However, I make an exception for John Stapp.

Every time you get into a car and put on a seat belt (whether required to by law or not), you owe a debt to Dr Stapp. As a doctor in the US Air Force, he took part in experiments on human deceleration in the late 1940s. During the Second World War it had been assumed that the maximum tolerable human deceleration was 18G (that is, 18 times the force of gravity at sea level), and that death would occur above that level. The Air Force wanted to test whether this was really true, and so a research project was set up. In order to test the hypothesis, an anthropomorphic dummy was to be shot down a test track and abruptly brought to a halt. Measuring equipment would be used to gauge the effect of the deceleration on the dummy. An account of the project is provided in the Annals of Improbable Research. That account indicates that Stapp had little confidence in the dummy.

While the brass assigned a 185-pound, absolutely fearless, incredibly tough, and altogether brainless anthropomorphic dummy — known as Oscar Eightball — to ride the Gee Whiz, David Hill remembers Stapp had other ideas. On his first day on site he announced that he intended to ride the sled so that he could experience the effects of deceleration first-hand. It was a statement that Hill and everyone else found shocking. “We had a lot of experts come out and look at our situation,” he remembers. “And there was a person from M.I.T. who said, if anyone gets 18 Gs, they will break every bone in their body. That was kind of scary.”
But the young doctor had his own theories about the tests and how they ought to be run, and his nearest direct superiors were over 1000 miles away. Stapp’d done his own calculations, using a slide rule and his knowledge of physics and human anatomy, and concluded that the 18 G limit was sheer nonsense. The true figure he felt might be twice that if not more.

In the event, Oscar the dummy was used merely to test the efficacy of the test track and the ballistic sled on which his seat was first accelerated and then decelerated. Once that was done, testing could start.

Finally in December 1947 after 35 test runs, Stapp got strapped into the steel chariot and took a ride. Only one rocket bottle was fired, producing a mere 10 Gs of force. Stapp called the experience “exhilarating.” Slowly, patiently he increased the number of bottles and the stopping power of the brakes. The danger level grew with each passing test but Stapp was resolute, Hill says, even after suffering some bad injuries. And within a few months, Stapp had not only subjected himself to 18 Gs, but to nearly 35. That was a stunning figure, one that would forever change the design of airplanes and pilot restraints.

The initial tests were done with the subject (not always Stapp) facing backwards. Later on, forward-facing tests were done as well. Over the period of the research, Stapp was injured a number of times. Many of these injuries had never been seen before — nobody had been subjected to such extreme forces. Some were more mundane — he broke his wrist twice; on one occasion resetting the fracture himself as he walked back to his office. It is one thing to overcome danger that arises accidentally, quite another to put oneself directly in such extreme situations.

And he did it for the public good.

…while saving the lives of aviators was important, Kilanowski says Stapp realized from the outset that there were other, perhaps even more important aspects to his research. His experiments proved that human beings, if properly restrained and protected, could survive an incredible impact.

Cars at the time were incredibly dangerous places to be. All the padding, crumple zones and other safety features that we now take for granted had yet to be introduced.

Improving automobile safety was something no one in the Air Force was interested in, but Stapp gradually made it his personal crusade. Each and every time he was interviewed about the Gee Whiz, Kilanowski notes, he made sure to steer the conversation towards the less glamorous subject of auto safety and the need for seatbelts. Gradually Stapp began to make a difference. He invited auto makers and university researchers to view his experiments, and started a pioneering series of conferences. He even managed to stage, at Air Force expense, the first ever series of auto crash tests using dummies. When the Pentagon protested, Stapp sent them some statistics he’d managed to dig up. They showed that more Air Force pilots died each year in car wrecks than in plane crashes.

While Stapp didn’t invent the three point auto seatbelt, he helped test and perfect it. Along with a host of other auto safety appliances. And while Ralph Nader took the spotlight when Lyndon Johnson signed the 1966 law that made seatbelts mandatory, Stapp was in the room. It was one of his real moments of glory.

Ultimately, John Stapp is a hero to me because he was true to his convictions — he had a hypothesis and tested it on himself. In the modern business vernacular, he ate his own dogfood. Over and above that, he did it because he could see a real social benefit. His work, and (more importantly) the way he did it, has directly contributed to saving millions of lives over the last 60 years. Those of us who seek to change our environments, whether at work or home, or in wider society, should heed his example. If there are things that might make a difference, we shouldn’t advocate them for others (even dummies) without checking that they work for us.

Now, the other link. Greg Lambert at the 3 Geeks and a Law Blog has extended the critique of IT failing to spot and deal with the current financial crisis by suggesting that KM is equally to blame.

Knowledge Management was originally an idea that came forth in the library field as a way to catalog internal information in a similar way we where cataloging external information. However, because it would be nearly impossible for a librarian to catalog every piece of internal information, KM slowly moved over to the IT structure by attempting to make the creator of the information (that would be the attorney who wrote the document or made the contact) also be the “cataloger” of the information. Processes were created through the use of technology that were supposed to assist them in identifying the correct classification. In my opinion, this type of self-cataloging and attempt at creating a ultra-structured system creates a process that is:

  1. difficult to use;
  2. doesn’t fit the way that lawyers conduct their day-to-day work;
  3. gives a false sense of believing that the knowledge has been captured and can be easily recovered;
  4. leads to user frustration and “work around” methods; and
  5. results in expensive, underutilized software resources.

In a comment on that post, Doug Cornelius says:

I look at KM 1.0 as being centralized and KM 2.0 as being personalized. The mistake with first generation KM and why it failed was that people don’t want to contribute to a centralized system.

We have to be careful, as Bill Ives points out, not to throw out the baby in our enthusiasm to replace the 1.0 bathwater with nice fresh 2.0 bubbles. However, Greg and Doug do have a point. We made a mistake in trying to replicate the hundreds or thousands of databases walking round our organisations with single inanimate repositories.

The human being is an incredible thing. It comes with a motive system and an incredibly powerful (but probably unstructured) data storage, computation and retrieval apparatus. Most (probably all) examples of homo sapiens could not reproduce the contents of this apparatus, but they can produce answers to all sorts of questions. The key to successful knowledge activities in an organisation, surely, is to remember that each one of these components adds a bit of extra knowledge value to the whole.

Potentially, then, we are all knowledge heroes. When we experiment with knowledge, the more people who join in, the better the results. And the result here should be, as Greg points out, to “help us face future challenges.” We can only do that by taking advantage of the things that the people around us don’t realise that they know.

Is knowledge work what we think it is?

When we talk about knowledge work, I think many of us probably focus on desk-bound paper-shufflers of some kind. Here’s a man who disagrees.

more about “Is knowledge work what we think it is?“, posted with vodpod

Matthew Crawford has an academic and work history that could mark him out as an intellectual — perhaps the ultimate knowledge worker. He has a PhD in political philosophy from the University of Chicago, after which he held a postdoctoral fellowship at the University’s Committee on Social Thought. After that, he was executive director at a Washington policy organisation. Between his master’s degree and his doctorate he worked writing summaries of academic journal articles for library CD-ROMs. His current vocation, however, is to run a motorcycle repair shop. This change in direction is the subject of a book, which is touted in a New York Times article and the appearance on Stephen Colbert’s show that you can see above.

Crawford’s argument is that what we commonly think of as knowledge work is most often in fact just mindless following of process, whereas manual tasks may often pose some difficult mental challenges.

There probably aren’t many jobs that can be reduced to rule-following and still be done well. But in many jobs there is an attempt to do just this, and the perversity of it may go unnoticed by those who design the work process. Mechanics face something like this problem in the factory service manuals that we use. These manuals tell you to be systematic in eliminating variables, presenting an idealized image of diagnostic work. But they never take into account the risks of working on old machines. So you put the manual away and consider the facts before you. You do this because ultimately you are responsible to the motorcycle and its owner, not to some procedure.

Some diagnostic situations contain a lot of variables. Any given symptom may have several possible causes, and further, these causes may interact with one another and therefore be difficult to isolate. In deciding how to proceed, there often comes a point where you have to step back and get a larger gestalt. Have a cigarette and walk around the lift. The gap between theory and practice stretches out in front of you, and this is where it gets interesting. What you need now is the kind of judgment that arises only from experience; hunches rather than rules. For me, at least, there is more real thinking going on in the bike shop than there was in the think tank.

By comparison, Crawford sees remoteness and a lack of responsibility pervading much of our knowledge work.

The visceral experience of failure seems to have been edited out of the career trajectories of gifted students. It stands to reason, then, that those who end up making big decisions that affect all of us don’t seem to have much sense of their own fallibility, and of how badly things can go wrong even with the best of intentions …

There is good reason to suppose that responsibility has to be installed in the foundation of your mental equipment — at the level of perception and habit. There is an ethic of paying attention that develops in the trades through hard experience. It inflects your perception of the world and your habitual responses to it. This is due to the immediate feedback you get from material objects and to the fact that the work is typically situated in face-to-face interactions between tradesman and customer.

An economy that is more entrepreneurial, less managerial, would be less subject to the kind of distortions that occur when corporate managers’ compensation is tied to the short-term profit of distant shareholders.

I think one of our primary challenges in management (and especially knowledge management) is to instil a culture of paying attention. To some extent, much of 20th century management drove people into places where they did not need to pay attention: they were forced into silos of specialisation where they did not need to worry about what anyone else was doing. The result of this can be seen in many modern workplaces. For example, consider this description of life in a global accounting firm, from Steve Denning’s review of Alain de Botton’s book, The Pleasures and Sorrows of Work.

He zeroes in on the HR director and her activities which include promoting day care centers and animatedly asking subordinates at monthly get-togethers how they are enjoying their jobs; organizing competitions in landscape painting and karaoke to stimulate creativity; and “Employee of the Month” schemes which reward the winners with river cruises and lunches with the chairman. (p.248)

“For most of human history, the only instruments needed to induce employees to complete their duties energetically and adroitly was the whip… Once it became evident that someone who was expected to remove brain tumors, draw up binding legal documents or sell condominiums with convincing energy could not be profitably sullen or resentful, morose or angry, the mental well being of employees commenced to be an object of supreme concern.” (p.244)

Thus it would be plausible but wrong, de Botton says, to judge the HR Director as “an unnecessary sickness”. This would be “to misconstrue the sheer distinctiveness of the contemporary office” as “a factory of ideas”. The HR Director plays a key role in maintaining the mask of shallow cheerfulness that keeps the office running smoothly. It is “the very artificiality of her activities that guarantee their success”, like a party game at a house party that initially invite mockery but, as the game gets under way, participants are surprised to find that the game enables them to “channel their hostilities, identify their affections and escape the agony of insincere chatter”. (p.246)

Yet the success is relative. He notes, tellingly, how little time, amid these systematic efforts at contrived conviviality, is actually spent on real work, and how much is devoted to “daydreams and recuperation”. (p.258)

Perhaps knowledge work is actually too easy for people to engage with it properly. By documenting processes in excruciating detail, organisations have simultaneously suppressed creativity and innovation, and created the conditions for inadvertent (but inevitable) error and failure.

From bureaucracy to agility

Last year, I referred to a post by Olivier Amprimo, who was then at Headshift. He is now working at the National Library Board in Singapore, and is still sharing really interesting thoughts. The latest is a presentation he gave to the Information and Knowledge Management Society in Singapore on “The Adaptation of Organisations to a Knowledge Economy and the Contribution of Social Computing“. I have embedded it below.

For me, the interesting facet of what Olivier describes is the transition from bureaucratic organisations to agile ones, and what that means for KM. Traditional KM reflects what Olivier isolates in the bureaucratic organisation, especially the problem he describes as the confusion between administrative work and intellectual work. In doing traditional KM (repositories of knowledge, backed up with metrics based on volume) we run the risk that administrative work is enshrined as the only work of value. However, it is the intellectual work where agility can be generated, and where real value resides.

Olivier describes the agile organisation as one where the focus is on rationalisation of design.

What is important is how the individual forms and is conditioned by work. The work is the facilitator. This is the first time that the individual has been in this position. This is where the knowledge economy really starts.

I found an example of the kind of agility that Olivier refers to in an unexpected place: a short account of the work of Jeff Jonas, who is the chief scientist of IBM’s Entity Analytics group. His work with data means that he is an expert in manipulating it and getting answers to security-related questions for governmental agencies and Las Vegas casinos. For example, he describes how he discussed data needs with a US intelligence analyst:

“What do you wish you could have if you could have anything?” Jonas asked her. Answers to my questions faster, she said. “It sounds reasonable,” Jonas told the audience, “but then I realized it was insane.” Insane, because “What if the question was not a smart question today, but it’s a smart question on Thursday?” Jonas says.

The point is, we cannot assume that data needed to answer the query existed and been recorded before the query was asked. In other words, it’s a timing problem.

Jonas works with data and technology, but what he says resonates for people too. When we store documents and information in big repositories and point search engines at them, we don’t create the possibility of intelligent knowledge use. The only thing we get is faster access to old (and possibly dead) information.

According to Jonas, organizations need to be asking questions constantly if they want to get smarter. If you don’t query your data and test your previous assumptions with each new piece of data that you get, then you’re not getting smarter.

Jonas related an example of a financial scam at a bank. An outside perpetrator is arrested, but investigators suspect he may have been working with somebody inside the bank. Six months later, one of the employees changes their home address in payroll system to the same address as in the case. How would they know that occurred, Jonas asked. “They wouldn’t know. There’s not a company out there that would have known, unless they’re playing the game of data finds data and the relevance finds the user.”

This led Jonas to expound his first principle. “If you do not treat new data in your enterprise as part of a question, you will never know the patterns, unless someone asks.”

Constantly asking questions and evaluating new pieces of data can help an organization overcome what Jonas calls enterprise amnesia. “The smartest your organization can be is the net sum of its perceptions,” Jonas told COMMON attendees.

And:

Getting smarter by asking questions with every new piece of data is the same as putting a picture puzzle together, Jonas said. This is something that Jonas calls persistent context. “You find one piece that’s simply blades of grass, but this is the piece that connects the windmill scene to the alligator scene,” he says. “Without this one piece that you asked about, you’d have no way of knowing these two scenes are connected.”

Sometimes, new pieces reverse earlier assertions. “The moment you process a new transaction (a new puzzle piece) it has the chance of changing the shape of the puzzle, and right before you go to the next piece, you ask yourself, ‘Did I learn something that matters?'” he asks. “The smartest your organization is going to be is considering the importance right when the data is being stitched together.”

Very like humans, then? A characteristic of what we do in making sense of the world around us is drawing analogies between events and situations: finding matching patterns. This can only be done if we have a constant awareness of what we already know coupled with a desire to use new information to create a new perspective on that. That sounds like an intellectual exercise to me.

It’s not my problem

As I was catching up on my RSS feeds this morning, something by Jack Vinson caught my attention.

Tools of the trade

When LinkedIn launched groups, in which like-minded people could discuss topics of common interest, it seemed like a sensible idea. Unfortunately, it is much easier to start a group than to search for an existing one, so there are many groups covering similar ground. As a result, one ends up being a member of a multitude of groups and participating in none.

Unlike me, however, Jack has engaged with some of these discussions, and in one in particular (referenced in his blog post) he tries to move the responses to a standard question in an interesting direction.

The question (posed by a knowledge manager in the mining industry) was simple enough:

I need to put together an AFE (authorization for expenditure) to start the KM program in my company, but the executives are still asking ROI questions. They have the mandate to innovate but just don’t get it. KM is about setting the baseline for indirect ROI or am I wrong?

Naturally enough, this produced some interesting answers focusing on measuring ROI or on ways of persuading the executives by other means. Jack’s response came from at the problem from a different angle:

Maybe it is not time to implement software? Instead approach the executives with the problems they have articulated (such as “innovation”), and propose changes to the process that will help remove or reduce the severity of the problems. A lot of that will have to do with the way people work, regardless of whether there is specific software in place to make it happen. What can you do with the software you have today? What could you do in addition if you were to buy the software you are proposing to buy?

I found this recasting of the question really valuable. Too often, issues are raised about the ROI of particular interventions (social software, KM activities, and so on), but account is rarely taken of the price of doing nothing. The fact is that these projects are rarely undertaken for their own sake — at least, they shouldn’t be. Instead, they are (or should be) proposals to deal with an existing business problem. That problem usually belongs to someone else — whether that be a manager in a particular part of the business, or someone in the leadership team. As Dave Snowden put it in a discussion panel at last weeks KCUK conference, we need to think about what the objects of KM are. He proposed just two:

  • improving decision making
  • creating the conditions for innovation

Given that the decision making process generally belongs to someone else, they need to judge whether (a) it is in need of improvement and (b) how best to improve it. We have a role in helping them with those judgments (by showing them alternatives, for example), but they have to make the call whether a KM approach is the right one.

Ultimately, then, it is our job to show people what is possible, and to offer a variety of options for resolving problems. Our preference for one solution over another may well be misinformed — we can rarely appreciate the full context. That is one reason why many big KM projects have failed in the past — they were not driven by the business, and so the investment that really counts was missing.

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.]

Star-shaped workers

Jason Plant drew my attention today to an old HBR article: “Introducing T-Shaped Managers: Knowledge Management’s Next Generation“. The article, by Morten T. Hansen and Bolko von Oetinger, dates from 2001 and shows how much our views on KM have changed over the past eight years. It starts by asserting that centralised knowledge management efforts and those depending on technology have not been especially successful. The alternative, it is suggested, depends on people behaving differently.

We suggest another approach, one that requires managers to change their behavior and the way they spend their time. The approach is novel but, when properly implemented, quite powerful.

We call the approach T-shaped management. It relies on a new kind of executive, one who breaks out of the traditional corporate hierarchy to share knowledge freely across the organization (the horizontal part of the “T”) while remaining fiercely committed to individual business unit performance (the vertical part). The successful T-shaped manager must learn to live with, and ultimately thrive within, the tension created by this dual responsibility.

The question the authors pose next remains an interesting one, but for different reasons. “Why rely so heavily on managers to share knowledge?” The alternative they pose is a knowledge management system.

The trouble is that, while those systems are good at transferring explicit knowledge—for example, the template needed to perform a complicated but routine task—direct personal contact is typically needed to effectively transfer implicit knowledge—the kind that must be creatively applied to particular business problems or opportunities and is crucial to the success of innovation-driven companies. Furthermore, merely moving documents around can never engender the degree of collaboration that’s needed to generate new insights. For that, companies really have to bring people together to brainstorm.

But why concentrate on managers to do this brainstorming and collaboration? The article (or at least the excerpt available online) does not appear to admit the possibility that workers at a lower level might have a responsibility to share knowledge, or that they would even be able to reach outside their silos to people at a similar level in different business units.

Eight years later, it is clear that what we actually need is not T-shaped managers, but *-shaped workers. That is, people who can share knowledge effectively within their business unit (with junior and senior co-workers): | , with colleagues at the same level in different business units: — , and even others at different levels in other areas of the business: / and \ .

Adding all these pieces together: | — / \ we get a star shape or asterisk: * . I think that is a reasonable goal for people in modern businesses: to share knowledge freely, without respect for organisational boundaries or hierarchy. Any business that relies on T-shaped managers is likely to miss the benefits offered by wider knowledge sharing. Organisations with star-shaped workers will make the most of their knowledge.

Why are we doing this KM thing?

I was reading Strategic Intuition (there will be more on this fascinating book at a later date) on the train home yesterday, and was prompted to ask myself an odd question: “why are we doing knowledge management? What will be different, and for whom?”

The passage that made me ask this question was a description of a firefighter’s decision-making process.

Never once did he set a goal, list options, weigh the options, and decide among them. First he applied pressure, then he picked the strongest but newest crew member to bear the greatest weight of the stretcher, and then in the truck they put the victim into the inflatable pants. Formal protocol or normal procedure certainly gave him other options — examine the victim for other wounds before moving him, put the victim into the inflatable pants right away, and assign someone experienced to bear the greatest weight of the stretcher — but Lieutenant M never considered them.

The researcher whose work is described here (Gary Klein) started out with the hypothesis that the decision-making process would conform to the model of a defined goal, followed by iterative consideration of a series of options. However, he rapidly discovered that this model was wrong. Instead, what he saw in the experts that he studied (not only firefighters, but soldiers in battle, nurses, and other professionals) was overwhelmingly intuitive weighing of single options. (There is more in the book about why this is.)

We often talk about decision-making processes, and one of the goals of knowledge management is often to improve those processes by, for example, ensuring better access to information, or by honing the processes themselves (the HBR article by Dave Snowden and Mary Boone on “A Leader’s Framework for Decision Making” is an excellent example of the latter). Although these activities may well improve decision-making, those decisions are ultimately made by people — not processes. The question I posed for myself, then, was: what impact does KM have on people? Exactly how will they be better at decision-making as a result of our work?

My instinctive answer is that I want them to become experts (and therefore able to act swiftly and correctly in an emergency) in whatever field they work in. That means that we should always return our focus to the people in our organisations, and respond to their needs (taking into account the organisation’s direction and focus), rather than thinking solely about building organisational edifices. The more time that is spent on repositories, processes, structures, or documentation, the less is available for working with people. In becoming experts in our own field, we also need to be more instinctive.

Coincidentally, I read two blog posts about experts over the weekend. The first was Arnold Zwicky bringing some linguistic sanity to counter fevered journalistic criticism of ‘experts’ and ‘expertise’.

Kristof is undercutting one set of “experts”, people who propose to predict the future. Lord knows, such people are sitting ducks, especially in financial matters (though I believe they do better in some other domains), and it’s scarcely a surprise that so many of them get it wrong.

Other “experts” offer aesthetic judgments… and still others exhibit competence in diagnosis and treatment…, and stlll others simply possess extensive knowledge about some domain…

The links between these different sorts of expert/expertise are tenuous, though not negligible. Meanings radiate in different directions from earlier meanings, but the (phonological/orthographic shapes of the) words remain. The result is the mildly Whorfian one that people are inclined to view the different meanings as subtypes of a single meaning, just because they are manifested in the same phonological/orthographic shapes. So experts of one sort are tainted with the misdeeds of another.

Expertise that results from real experience, study, insight, rationality and knowledge does not deserve to be shunned as mere pontification. It can save lives.

The other blog post, by Duncan Work, is a commentary on a New Scientist report about how people react to advice they believe to be expert. It appears that key areas in their brains simply turn off — they surrender the decision-making process to the expert.

This phenomenon has both adaptive and non-adaptive effects.

It is evolutionarily adaptive by being a “conformity-enforcing” phenomenon that can kick in when a large group needs to quickly move in the same direction in order to survive a big threat.   It’s also adaptive when the issues are extremely complex and most members of the population don’t have the knowledge or experience to really evaluate the risks and make a good decision.

It is evolutionarily non-adaptive when there is still a lot of confusion around the issue, when the experts themselves don’t agree, and when many experts are guided by narrow interests that don’t serve the group (like increasing and protecting their own personal prestige and wealth).

The real problem is not just that many of the crises now facing businesses are founded in actions, decisions and behaviours that few people understand. It is that we make no distinction between different categories of expert, and so we follow them all blindly. At the same time, as the New York Times op-ed piece critiqued by Zwicky illustrates, many of us do not actually respect experts. In fact, what we don’t respect are people who style themselves experts, but who are actually driven by other interests (as Work points out).

So if our KM work is at least in part to make people into experts, we probably need to rescue the word from the clutches of people who profess expertise without actually having any.

Book Review: Generation Blend

I have already voiced my scepticism about Generation Y, so it may seem odd that I chose to buy Rob Salkowitz’s book Generation Blend: Managing Across the Technology Age Gap. However, there is a lot in this book that does not depend on an uncritical acceptance of the “generations” thesis. It provides a sound practical basis for any business that wants to, in Salkowitz’s words, “develop practices and deploy technology to attract, motivate, and empower workers of all ages.”

As one might expect, underpinning Generation Blend is the thesis that there are clear generational (not age-related) differences that affect how people approach and use technology. In this, Salkowitz builds on Neil Howe and William Strauss’s book, Generations: The History of America’s Future, 1584 to 2069. However, generational differences are not the starting point for the book. Instead, Salkowitz begins by showing how technology itself has changed the working environment irrevocably. In doing so, he establishes the purpose of the book: to allow organisations to develop the most suitable strategy to help their people to cope with those changes (and the many more to come).

Organizations invest in succeeding waves of new technology — and thus subject their workers to waves of changes in their lives and workstyles — to increase their productivity and competitiveness. Historically, productivity has increased when new technology replaced labor-intensive processes, first with mechanical machinery, and now electronic information systems. (p. 24)

Dave Snowden has started an interesting analysis of these waves of change, and Andrew McAfee’s research shows that IT makes a difference for organisations. What Salkowitz does in Generation Blend is to provide real, practical, insights into the way in which organisations can make the most of the abilities of all generations when faced with new technology. When he does discuss the generations, it is important to remember that his perspective is entirely a US-centric one. That said, the rest of the book is generally applicable. This is Salkowitz’s strength — he recognises that there are real exceptions to the broad brush of generational study, and his guidance focuses on clear issues with which it is difficult to disagree. As one of the section headings puts it, “software complexity restricts the talent pool,” so the target is to accommodate different generational approaches in order to loosen that restriction. Chapter 3 of the book closes with a set of tables outlining different generational attributes. I found these very useful in that they focused the mind on the behaviours and attitudes affecting people’s approach to technology, rather than as a hard-and-fast description of the different generations.

Salkowitz’s approach can be illuminated by comparing three passages on blogging.

The open, unsupervised quality of blogs can be deeply unsettling to people who have internalized the notion that good information comes only from trusted institutions, credentialed individuals, or valid ideological perspectives. (p. 82)

On the other hand:

Blogs and wikis create an environment where unofficial and uncredentialed contributors stand at eye level with traditionally authoritative sources of knowledge. This is perfectly natural to GenXers, who believe that performance and competence should be the sole criteria for authority. (p. 147)

And, quoting Dave Pollard with approval:

“I’d always expected that the younger and more tech-savvy people in any organization would be able to show (not tell) the older and more tech-wary people how to use new tools easily and effectively. But in thirty years in business, I’ve almost never seen this happen. Generation Millennium will use IM, blogs, and personal web pages (internal or on public sites like LinkedIn, MySpace and FaceBook) whether they’re officially sanctioned or not, but they won’t be evangelists for these tools.” (p. 216)

 There is here, I think, a sense of Salkowitz’s desire to engage older workers as well as his concern that unwarranted assumptions about younger people’s affinity with technology could lead businesses towards the wrong courses of action.

At the heart of Generation Blend is a critique of existing technology, in which Salkowitz points out that current business software has a number of common characteristics:

  • It tends to be complex and overladen with features
  • It focuses on efficiency
  • It is driven by the need to perform tasks
  • It supports a work/life balance that is “essentially a one-way flow of work into life” (p. 147)

These characteristics have come about, Salkowitz argues, because the technology has largely been produced by and for programmers whose values and culture:

…independence, obsession with efficiency as a way to save personal time and effort, low priority on interpersonal communication skills, focus on outcomes rather than process (such as meetings or showing up on a regular schedule), seeing risk in a positive light, desire to dominate through competence — sound like the thumbnail descriptions of Generation X tossed out by management analysts. (p. 149)

Since this group is clearly comfortable with technology, and is also increasingly moving into leadership and management roles, Salkowitz provides them with guidance on making technology accessible to older workers and on making the most of the skills and insights of younger workers. He does this in general terms throughout the book, but most convincingly in the final three chapters. Two of these use narrative to show how (a) the fear can be taken out of technology for older people and (b) the younger generation can be involved directly in defining organisational strategy.

In the first of these chapters, Salkowitz describes a non-profit New York initiative, OATS (Older Adults Technology Services), which trains older people in newer technologies, so that they can comfortably move into roles where those skills are needed. OATS has found that understanding the learning style of these people allows them to pick up software skills much more quickly than is commonly assumed.

While younger people learn technology by handson experimentation and trial and error, [Thomas] Kamber [OATS founder] and his team find that older learners prefer information in step-by-step instructions and value written documentation. (p. 167)

At the other end of the generational scale, Salkowitz starts with a statement that almost reads like a manifesto:

Millennials may be objects of study, but they are also, increasingly, participants in the dialogue, and it is silly (and rude) for organizations to talk about them as if they are not already in the room. (p. 190)

He goes on to illustrate the point with an account of Microsoft’s Information Worker Board of the Future, which was a “structured weeklong exercise around the future of work,” which the company used to help it understand how its strategy should develop in the future. It was judged to be a success by bringing new perspectives to the company as well as showing Microsoft to be a thought leader in this area.

…the organizational commitment to engage with Millennials as partners in the formation of a strategic vision can be as valuable as the direct knowledge gained from the engagement. Strategic planning is a crucial discipline for organizations operating in an uncertain world. When it is a closed process, conducted by experts and senior people (who inevitably bring their generational biases with them), it runs a greater risk of missing emergent trends or misjudging the potential for discontinuities that could disrupt the entire global environment. Opening up the planning process to younger perspectives as a matter of course rather than novelty hedges against the risks of generational myopia and also sends a strong positive signal to members of the rising generation. (p. 209)

Generation Blend ends with a clear exposition of the key issues that organisations need to address in order to make the most of their workers of all ages and the technology they use.

Organizations looking to effectively manage across the age gap in an increasingly sophisticated connected information workplace should ask themselves five questions:

  1. Are you clearly explaining the benefits of technology?
  2. Are you providing a business context for your technology policies?
  3. Are you making technology accessible to different workstyles?
  4. Does your organizational culture support your technology strategy?
  5. Are you building bridges instead of walls? (p. 212)

The last two of these are particularly interesting. In discussing organisational culture, Salkowitz includes careful consideration of knowledge management activities, especially using Web 2.0 tools. He is confident that workers of all generations will adapt to this approach to KM at a personal level, but points to real challenges: “[t]he real difficulties… are rooted in the business model and in the way that individual people see their jobs.” (p. 229) For Salkowitz, the solution is for the organisation to make a real and visible investment in knowledge activities — he points to the use of PSLs in UK law firms as one example of this approach. Given the tension between social and market norms that I commented on yesterday, I wonder how far this approach can be pushed successfully.

Running through Generation Blend is a thread of involvement and engagement. Salkowitz consistently advocates management approaches that accommodate different ways of extracting value from technology at work. This thread emerges in the final section of the book as an exhortation to use the best of all generations to work together for the organisation — building bridges rather than walls.

Left to themselves, workers of different ages will apply their own preconceptions and experiences of technology at work, sometimes leading to conflict and misunderstanding when generational priorities diverge. But when management demonstrates a commitment to respecting both the expectations of younger workers and the concerns of more experienced workers around technology, organizations can effectively combine the tech-savvy of the young with the knowledge and wisdom of the old in ways that make the organization more competitive, more resilient to external change, more efficient, and more open. (p. 231)

I think he is right in this, but it will be a challenge for many organizations to do this effectively, especially when they are distracted by seismic changes outside. My gut feeling is that those businesses that work hard at the internal stuff will find that their workforce is better able to deal with those external forces.