One of the reoccurring themes in my work is the need for those who are involved with a problem to find their own solution and to implement that solution. I can get quite passionate about the need for action and the demotivating effects of having someone else work out the solution and simple pass it on for you to execute.

Still there may be occasions were an outsider’s view can be helpful. I’m sure we’ve all been in situation were we are powerless to effect a decision, it could be events in our office, our company’s strategy, or Government policy, perhaps its a football team selection. What is obvious to us, and often obvious to our drinking partners too, somehow isn’t obvious to those charged with making the decisions: our manager, the prime minister, the team manager. Why is the obvious not so obvious?

One reason might simply be that we (who think we see an obvious answer) lack information. Sure doing X is obvious, and sure the people in charge have considered it but doing X will effect Y. That Y exists and is a potential problem might not be common knowledge, or it could be something that we are simply ignorant of.

This explanation also works in reverse, particular were knowledge is needed. For example, as someone with lots of experience in IT I have a lot of knowledge, this allows me to see obvious solutions to many IT problems. So, its obvious to me that bid Government IT projects will go wrong but that never seems clear to those who authorise them.

A second reason is that what we consider obvious simply isn’t obvious to those making the decision. Perhaps they see a lot of related issues so can’t see the wood for the trees; perhaps they have some personal stake that makes it hard for them to do X; or perhaps it simply isn’t obvious. In such cases it can be possible to be too close to the problem.

I noticed this the other week. I was having problems sorting out some problems of my own when a friend called looking for advice for her problems. After hearing her problems I made some suggestions, the solutions seemed straight forward, at the end of the conversation she said something like “Yes, they are good ideas I’ll try them.” While I was able to solve someone else’s problems I couldn’t solve my own.

So, sometimes you can’t solve your own problems even when there is an “obvious” solution. You need help to see the problem. How can we reconcile this with my opening point about the need for people to find their own solutions and act on them? Well, I think the trick is two fold: first know when you need an outsiders opinion, and two, if you are that outsider, try and give the solution in such a way that the person asking takes the solution as their own.

In his book The Living Company Arie de Geus suggests the role of planning, particularly scenario planning, is to create memories of the future. By under taking the planning exercise we conceive of how the world may look different, we prepare our brains for a future that is not simply a repeat of tomorrow. The actual plan isn’t so important, the important thing is we’ve imagined and visited a world that is different.

This last weekend’s FT has an interesting piece on the increasing world urbanisation, particularly in India and China – here is the link. What caught my eye was mention of China’s museums of the future. This is the second time I’ve heard of these museums which display the designs and plans for the cities China is building and extending.

Future museums strike me as a great way to create future memories. The idea that I can go and see how things may, or should, be in the future is brilliant. Perhaps they even have people on hand so I can ask questions of. Of course I don’t now if the Chinese planners are explicitly trying to create future memories or if they have read Arie de Geus but that’s not really the point.

When people are faced with change, whether is be new buildings, a new environment, or a changed work environment, maybe new processes they are naturally inquisitive. If their questions can’t be answered they start to hypothesis and make things up – they create their own future memories. Since they don’t know their hypothesises are right they have doubt. Doubt about the future, and some possibly negative hypothesis creates fear.

Now your change efforts are facing an up hill battle, fear and doubt have entered the scene and different people have different ideas about what the future should look like, so, when the future does arrive they respond to it differently rather than consistently.

Creating future memories is one way to overcome these problems. Future memories can help remove the doubt, uncertainty, fear and help build a shared understanding of what the future will look like and how we should act when it arrives.

So far I know of several ways of creating future memories:

• Shared planning, specifically scenario planning – hence why I don’t like planners being a separate cadre
• Future museums, like in China
• Process miniatures, like the XP Game, these allow people to rehearse a future process in a small way.

A think the right sort of training can also help if it is interactive and allows people to rehearse future events. I’ll leave this hanging as I don’t know the magic ingredients for such training.

At the risk of sounding paradoxical I think one area were future memories might be able to help is with project retrospectives. I’m a big fan of these, I think they make sense and can really help your project teams learn and improve.

However, one of the problems I hear about with retrospectives is that teams undertaken them but then don’t follow through on their results. For example, during the retrospective the team identifies a problem and suggest a solution, everyone in the room agrees to do it. But outside the room, the next day, nothing actually changes. The team carries on as before.

I wonder if, after the retrospective, after identifying problems and solutions the team can somehow create a future memory of itself doing this. Maybe the team could build a model of the change, or maybe role-play the change. The idea would be to have team members understand and practice the change to remove doubt, uncertainty and misunderstandings.

Perhaps we need to pair retrospectives with future-spectives.

I’ve been using PDAs for about 12 years now, I started on a Psion 3a, then a 3c, then I moved to a Series 5, didn’t like that and moved back to a 3mx and finished on a Revo. As you can tell I love the things, the 3mx is still my favorite PDA but it was obvious at the time that it needed to move forward. The Revo should have been that move but it had two flaws: a poor case design and persistent battery problems.

In the end Psion got out of the market. Another British IT company that couldn’t crack the US market (the US OEM deal was too little too late) and consequently couldn’t compete worldwide. The company still survives and through Symbian the software is competing worldwide on phones not PDAs.

Anyway, I still like PDAs and I can’t imagine life without them. So, four years ago, when it became clear what was happening to Psion I jumped to Palm. The hardware was good but the software lacked functionality, still, it was a good product and I used it. However, it never quite merged into my life the way the Psion did – this may well have been changes to my lifestyle.

A couple of months ago I came to the conclusion I needed to do something about my aging Palm – the case was cracking. So I looked at the Palm website and go hooked on the idea of a LifeDrive.

I’ve had it over a month now and I have to say I’m disappointed with it.

In theory the LifeDrive is a great idea. Its a Palm PDA, and its an iPod (4Gb hard disk), its a voice recorder and a portable web terminal (Wifi and Bluetooth onboard). Sure it does all these things, but it doesn’t do anything really well. The PDA software (diary, address book, etc.) hasn’t really moved forward in 4 years; the music software is difficult to use and only seems to want to play 3 tunes before you have to do something; the voice record isn’t a patch on my Sony SX-56 and the Wifi takes for every to get a connection – and half the time tries to connect the wrong network.

So I’m disappointed with the LifeDrive. I probably should have done more research and maybe I should have jumped ship to a Microsoft based product.

But there is a bigger question: just what is Palm playing at?

Failing to move your software forward and poor products are not a route to success. Then I read that they have product delays coming up.

This goes back to their decision to split hardware (Palm) from (Palm Source) software and concentrate on the hardware. Which actually sounds like the Handspring strategy from a few years back. Remember Handspring? The Palm spin off that produced PDA’s using Palm OS. In fact, one could say that Palm has become Handspring. (Maybe not surprising as Palm actually bought Handspring about 4 years ago.)

In the early days of PDAs – and I should know, I was a summer intern at Distributed Information Processing, DIP, the guys who developed the Atari Portfolio – it made sense for hardware and software to be together because they evolved together. So we had the Apple Newton, Psion, Palm, DIP, Poqet and so on who produced hardware and software.

When the market matured it made sense to split, and specifically get out of hardware. So Psion spun out Symbian, Palm created PalmSource and HP, Dell and everyone else started using Microsoft Windows CE/Pocket/whatever. Nothing really surprising there, the same pattern happened with microcomputers (i.e. the machines before PCs) were we had TRS-80, Sinclair’s, etc. etc. each of which had its own software for its own hardware. And the same pattern is playing out in phones as manufactures increasingly use standard platforms from Symbian, Microsoft, Nokia and others.

(It is interesting to think of other devices were this split could happen next. Already there are signs of it happening in the TV and set-top box market, what about cars? There is a lot of software in them these days, or kitchen appliances?)

(And Apple are the exception, they never split hardware and software. Arguably they should have done and some reports say they may still have some kind of play lined up.)

Palm have done well to survive this long but don’t think they’ve got much of a future. They are a small hardware player in a large market, they can’t innovate (or even update) through software and their products seem to lack focus. They’ve done well to survive this long but I don’t think they can continue.

People tell me that PDAs are a bad sector to be in. The convergence of phone and PDA will leave one winner: the phone. But, having used PDAs and phones for so long I think there will always be a niche for PDAs that do things phones don’t, or are unsuitable for – like running my wine database. Unfortunately I’ve not seen a PDA product that is suitable. Maybe this is just me, maybe I’m in a minority of one.

I originally read Thinking Beyond Lean (1998) over four years ago, it was good at the time and its still good. A few weeks ago I picked up the book to check something and decided it was worth a re-read. Four years ago I didn’t know as much as I do now about lean production and lean product development so I thought it would be worth another look.

The book is a study of how car companies develop their products, and specifically, how they reuse the designs to product additional products, e.g. the Ford Mondeo in Europe is the Ford Contura in America and a Jaguar something in both places. Of course, as you might guess from the title Toyota is the pace setter in this field as in so much else.

I did write about the book after my first reading and still agree with what I said then, there is good advice here we can apply to software development.

The book is interesting for two reasons. First it is an interesting insight into product development at some very companies. Second it looks at the subject of reuse in a context of multi-project management.

Make no mistake, the car industry has problems reusing its designs. Reuse is difficult. The overriding lesson is: reuse doesn’t just happen, you have to arrange for it to happen.

Cusumano and Nokeoka do identify four models of reuse, or rather four models of design, three of which are reuse and I think its worth naming them here:

• New build: design something new from the start, even if you could reuse something there are good reasons why you might do this.
• Concurrent: two or more projects running concurrently developing new products, usually one is the lead project
• Sequential: design something new, leave it alone for a while then try to reuse it for a new product.
• Design modification: design something new, leave it alone for a bit then come back and tweak the design for a new version.

Four years ago I thought these models were useful in describing software development and I still do. However, the software industry doesn’t think like that. We have four models of our own:

• Framework: we create a project that has no objective but to create a platform for others to reuse. Usually these projects are expensive and often they fail.
• Reuse will just happen: made famous by the OO movement, the idea is that if programmers write “objects” (later components, now SOA components) then somehow they will be usable by others.
• Cut-and-paste: probably the most widely used; our own version of design modification.
• Packaged: we buy something someone else has written and work with it through an API.

I think only the last of these can really be claim to be a success.

There are lots of reasons why a reuse attempt can fail but mostly they boil down to organization. So, to make reuse happen you need to get the organization right – we’re back to Conway’s Law!

But there are other reasons, e.g. accounting. If project B is six months behind A and reuses their designs then who pays the bill, A or B?

And reuse may not always be a good thing. If you are competing on innovation then continually reusing your existing products may stop you creating innovations. It may also stop you from producing distinctive products – one of the problems Volkswagen had when it got very aggressive about platform sharing.

Yet another problem, not mentioned in the book, is your product life cycle: if all your products use they same platform then they will all age at the same pace and will all need replacing at the same time. So, just when your cash flow is low (because all your products are old) you will need to spend a lot replacing them.

I think the main difference in reading the book four years ago and today is my own scepticism about reuse. Four years ago I still believed we in the software industry could do it, all we needed was the right approach. Now I’m not sure. I think the level of complexity in software is so great trying to product something for reuse isn’t worth the effort in most cases.

That said, if the software industry is to make any headway here we need to take on the issues and lessons described in Thinking Beyond Lean .

Shortly after taking over IBM Lou Gerstner famously said “The last thing this company needs is a vision.” In an era when businesses men often seem to compete with each other for “vision” this was a brave thing to say – particularly for a technical company. I’ve been thinking about that comment for the last week.

Some years ago I was a developer at a small software company in South London. A few months after I joined they hired a Software Development Manager and charged him with sorting out developement. One of the games I’ve played with myself over the years since then is to ask myself: “In his position what would I do?” – in other words, what would my vision, my strategy be.

Last week two people I know were in the position of taking over a existing group, and my advice to them, well, the last thing you need for your new team is a vision. Sure you need your own strategy for taking over the team but beyond that I don’t think you should have a strategy.

I’d better explain myself…

If I come in with a fully formed vision for my new team, particularly if I spell it out in PowerPoint slides then it is my vision. This might be great if I’m trying to persuade investors to put money into my company, or trying to find like minded people to join me on the quest but when the people are in place it does nothing to get their buy in or address the real problem.

When you take over an existing team there are existing problems, organizational issues and a lot of history. If you come in with a vision you don’t take any of these into account. Sure, being new is a great position to be in, you have a fresh pair of eyes, you can see what others can’t because your not mired in the thick of it. But, your going to need these people to deliver something.

So, you walk into your new team, give them your PowerPoint, and talk them through what you are going to do. Your communicating your vision, your strategy, not theirs. Your task, as you have defined it, is to get your people to execute your strategy. You have to explain the strategy, they will interpret it, they may not have exactly the same interpretation as you, will you ask them to play it back? Or will you assume they got it? And if they don’t quite get it? Will you explain it again, and again until they do, or will you listen to their comments and change?

And once they do understand it your going to have to ensure they do it. You now have a policing action on your hands – make sure they do what you want. (Fortunately management have tool for this, its called MBO – Management By Objective.)

So I don’t think this is a good idea. I do have an alternative, I’ll outline it here, I’ve done most of it although, to be honest, I’ve never done it in the kind of systematic way I’m laying it out here – but then I’ve never laid it out like this before.

First don’t do anything. Listen, watch, learn. Look around you. See what people are doing, specifically see what your team are doing.

Second, expand this into a longer investigation phase. Talk to the team, talk to them one-on-one, talk to their customers, their suppliers and any other interested stakeholders. Find what all these people think of the team, what they should be doing, what they are doing, and how they are performing.

Do you observations for a while, at least a month but maybe as long as three months.

Next get the team together. Find out what they problems they see collectively. Find out what they see as their overall goal. Now this could be tricky, hopefully what they are doing and what they think they are doing matches up with what the other stakeholders think. If they don’t your going to have to correct that, but I think in the broadest sense there will be something everyone can agree on.

Now work back. Get the team to collectively agree on what they should be doing to solve the problems. Don’t tackle all the problems, if possible throw some of them away, i.e. just don’t do them if you don’t have to. Remember people can only focus on so many things so don’t pick too many.

Once the group is in agreement it will probably help to work with everyone one-on-one to find out how they see the team, the aims and their responsibilities.

At no stage should you attempt to tell them a vision or a strategy. Let them work it out. These are bright people – if they aren’t why are they working for you? They are going to be far more motivated when they create the strategy and vision then when you tell them it.

Don’t worry that what they come up with isn’t what you expected, what others want or were the company is heading. You can correct this over time if you find a problem, the trick is to expose your team to the wider picture, make them aware of what the corporate strategy is, give them examples of were it is working and then help your team work back to change what they do.

I honestly believe that when bright people know where everyone is heading and are allowed to work things out for themselves they will a) get it right, b) be very motivated to do it, c) you’ll get a better answer because you used more brains and got collective action.

This may mean eating some humble pie and you don’t get to play with PowerPoint. The point is: it is not your ideas that are important, it is the team’s ideas. It is not important for you to have a big idea, it is important for you to help the team, and the people in it have big ideas.

Do it right and you will get a strategy and vision, and it will be a truely shared vision.

Talking About Machines is a book I have been wanting to read for some time. It is a study carried out by Julian E. Orr of photocopier service technicians – early 1980’s I think. That might not sound very exciting but the findings are. Basically, Orr discovered that what is important is what the engineers do on the job, not what their managers think they do. Classroom training is OK but you really learn what to do on the job, a lot of it verbally from your immediate team – and this team is more important than the corporation.

If that sounds obvious then maybe it is, but why do we so often ignore it?

Anyway, I’ve been wanting to read this book because references to it keep cropping up. I think I first heard of it reading some of John Seely Brown’s papers – most likely Organizational Learning and Communities-of-Practice but I can’t be sure. (If you haven’t read that paper then do so, if free at that URL so you have no excuse.)

So, a sense of interest and duty lead me to this book. True, it is significant, it is important but… well, it is also somewhat long winded. Still it pulls some important truths about the nature of modern work.

For example: we think of technicians as people who show up, look at the fault, fix the fault. We believe they just do it. In truth it there is a lot more to it than that. For a start, the same technicians have to deal with users of the machine, the social setting of the machine and the inaccuracy of the information the machine gives them.

OK, here’s the truth. I read the first few chapters and the last chapters, I skimmed or missed the ones in-between. As I read it I increasingly felt I was learning little new to add to what I had read in the references to it. Perhaps if I had read more I would have found more new stuff.

Two bits do stand out.

Early on Orr notes that while we may study a problem, we may even train for a problem when faced with it we may fail to recognise it. This rings true, how many case studies did I read in business school were the problem was obvious? Why didn’t the (far more experienced) people in the case study spot the problem and the solution? Why they didn’t notice it was a problem they already knew?

Perhaps you don’t spot the problem because at the time you don’t have all the information you need. Perhaps you don’t spot it because you arr too close to it, or too remote from it. Perhaps you don’t spot it because, well there are any number of reasons. This idea has got me thinking, how many problems I face now are ones I’d know the solution to if they were presented as a case study?

Second, toward the end Orr says:

“The management of the corporation … has pursued a strategy of de-skilling through the use of directive documentation. This does not actually deprive the workers of the skills they have, however; it merely reduced the amount of information given to them.”

I run across de-skilling regularly, so many company strategies, products or procedures are aimed at de-skilling people, but do they really de-skill? Or are management fooling themselves? Most likely they just shuffle the skills a little.

So many software tools are aimed at deskilling a job, yet how often are we repeating the mistake Orr describes? Rather than invest in tools perhaps we should be investing in people, rather than “de-skilling” them we should be re-skilling them. All too often managers are prepared to invest in a tool but not in training.

(And what of the tool makers? A complicated job may result in a complicated tool, people end up needing training on the tool. Tool makers need to ensure people get this training to use the tool effectively and demonstrate the value to the purchaser. But, if what you learn in the classroom isn’t much use, how are we to train these people?)

Summary then:

Orr’s book is worthy read and has some interesting insights. I’m sorry I couldn’t read it all but it was just too slow. Maybe I’ll come back and cherry pick the remaining chapters – umm… I’ve said that about books before, it rarely happens!

The book shows us that technical work is much about the social environment, learning doesn’t happen the way we like to think it does, and strategies that sound good don’t always work they way we thinkg.

Web 2.0 is having some fallout in the business world. It isn’t all about AJAX and Google maps, a lot of the other technologies that are broadly seen to be in Web 2.0 are of more general use. Perhaps the one with the most coverage is Blogs but Wikis, RSS, Search and tagging can all be used outside of consumer web-sites.

And I can vouch for this first hand. My employer has been using Wiki’s for a few years, at the moment I’m in the middle of evaluating search engines for the enterprise, today I’ve just set up our internal blogging system and I’m looking at fitting RSS to the website I manage.

I’m actually starting to think that a search engine, deployed in a modern IT enabled knowledge based company, may actually be one of the few example of a technology fix that actually delivers performance improvements right out of the box.

A piece by Andrew McAfee in the last issue of MIT Sloan Management Review entitled Enterprise 2.0: The Dawn of Emergent Collaboration sums all this up in the name “SLATES” – Search, Links, Authoring, Tags, Extensions and Signals.

A similar theme argument is made in this piece by Rod Boothby – although Rod seems to think this means the 20 something’s graduating from business school this year will have an advantage over the rest of us.

Both authors echo Tom Davenport who praises wikis in Thinking for a Living although he’s not sure about blogs. Are blogs an effective knowledge management tool? Do they spread ideas? Capture knowledge? Intuitively, from using them I think they do, but how effective are they? There are a lot of pointless blogs out there.

Davenport also suggests a more subtle use of blogs: to manage ones own knowledge. That is, by recording what we do we have our own knowledge available to us. I think this is true, I know I’ve included links and comments in this blog to remind me of things in future. And, as I’ve said before, blogging is a form of diary keeping; that can be useful in its own right, if it sparks some reflection on our part then it is a great advantage.

The thing is, and this continues my theme from the last entry, those who work in software development have had this technology for several years. I can’t remember exactly when I first came across Wiki’s but it was certainly before 2000. People who work in the IT industry both encounter this technology and know how to use it before the majority of other knowledge workers.

In part this is because they aren’t scared by the technology, they can install a wiki, they think nothing of engaging with the computer; in part it is because they have been closer to the people who developed these tools. Sure, I don’t know Ward Cunningham (the inventor of wiki’s) personally but I do know people who do know Ward personally.

But you don’t need Ward to create a wiki. Once the idea was out there many IT people created their own. In fact, when it comes to all these knowledge management tools software developers control the means of production – to use a phrase of Marx.

What does all this mean? Well, I think it means two things.

First researches can learn a lot from looking at IT people, they are early adopters of these technologies. Is there some new technology IT people are using today that could be the next big thing? And what about the practices and process around these tools?

Second, I think this supports my argument that IT people, and software developers in particular, are at the front of new knowledge working techniques.

Last week I reviewed Thinking for a Living, I’d like to pick up one or two points raised in this book and discuss them a little further. These are not points exclusive to Davenports work but having just read the book its a convenient focus for these thoughts.

I’m convinced that software developers (programmers, testers, product managers, etc. etc.) fail to recognise themselves as knowledge workers. Worse still, I think those that manage these people fail to recognise them as knowledge workers. So, we get discussions about “the software factory” and we hear managers describe how they can make their “factory” more efficient – as if the developers were working on a production line.

The metaphor continues, too many people in the business are concerned with “process” the idea – taken from Fredric Taylor and scientific management – that if we (the management) can improve our process then the factory will be more efficient, more productive, higher quality and so on.

What those who buy into this way of thinking and talking miss is that knowledge work is fundamentally different to factory thinking. In fact, modern factory thinking is different to traditional factory thinking. Toyota considers every one of its workers to be a knowledge worker – whether they are designing cars, advertising cars or assembling them.

The problem is, that when software developers and their managers ignore the knowledge worker aspect – either by regarding development as a factory process or as something “special” and “unique” – they miss out on opportunities, research and observations presented by the existing body of knowledge on knowledge work.

Davenport’s book clearly regards software developers as knowledge workers. Personally I’d go further, I think those involved with software development – that is everyone: developers, testers, analysts, product managers, project managers, etc. etc. – are not only knowledge workers but they are in the vanguard of modern knowledge work.

Before we write a line of code we need knowledge work: what is the problem? who does it effect? what is the benefit?

When we write code we need knowledge: language, operating system, problem, business, ….

When we test code we need knowledge.

Every line of software code embodies knowledge. Even the humblest for…loop expresses so much about out understanding of the problem, the solution and the domain it exists in.

Sometimes software people are the shock troops of knowledge work: parachuted into hostile territory to replace aging working systems and practises with shiny new technology – no wonder they don’t have many friends! No wonder you want “geeks” who don’t communicate with people, sometimes you don’t want them talking to the people they are replacing.

OK, that’s a little bit of hyperbole and exaggeration to catch your imagination but you get the message.

Now for the interesting bit.

Software people are on the front line of twenty-first century knowledge work. They don’t make it easy for themselves – ignoring much that existing knowledge on knowledge work, learning and change – but they are making discoveries, they are innovating, they are finding new ways of working.

One of the innovations that is transforming the way we do software is agile development and lean software development – I say one innovation because despite the two names they share much in common.

Davenport touches on this a bit, he spends a couple of pages on Agile methods and he quotes Martin Fowler. But he only hints at the true potential here. If, and its still a big if, Agile/Lean can transform software development maybe these practises can be applied to other areas of knowledge work.

What would it mean for a lawyer to work agile?

How would a financial advisor’s work be changed?

A journalist?

And a doctor? – in fact Womack and Jones are already talking about how Lean can change health care. Their recent book Lean Solutions actually discusses this.

Some ideas can transfer immediately:

• Card-and-board “Kanban” systems to focus work
• Daily stand up meetings
• Team work: break the one person, one task, as long as it takes model
• Pairing: why not have two lawyers write a brief?

Behind this a commitment to increase our productivity with a focus on value adding work – eliminate waste!

And, underlying all this, the operating system on which the whole thing runs: Continual learning and improvement – the Learning Organization.

Perhaps the future of all knowledge workers looks a lot more like the current methods being deployed by agile software developers?

Or perhaps, software people are just playing catch up, maybe we’ve cut ourselves off and only now are we catching up.

As usual the truth lies somewhere between the two extremes. For myself, I believe the future of all work will look a lot more like modern software development running on LOOS – Learning Organization Operating System.

One of the regular features of this blog is that I review the books I’ve read. Not all of them, on the whole I only really write about the “serious” books I’ve read, so you don’t get reviews of novels, cook books, etc. that I read. Before I turn to the latest book I’m conscious that every time I review I book I seem to like it. If a book reviewer doesn’t criticise a book once in a while are they really objective?

I’d like to be really critical of a book once in a while but in truth I just don’t tend to read books I’m not going to like. I tend to spend some time choosing books – I read other book reviews, online and in the press and I read what the book says about itself.

So, I hope you’ll forgive me if I seem to ready too hand out praise for books. That said, on with the show.

To train journey to and from St Ives over Easter allowed me to finish off Thomas Davenports Thinking for a Living. I’d been looking forward to reading this book since I read a favourable review in the FT a few months ago. I liked the book but I did find it a little disappointing. I suspect my disappointment might be more due to me than the book. For much of the last four years I’ve been reading lots about knowledge management and organizational learning. As a result I didn’t find a lot that was new to me in this book.

The situation may well be different if your new to the subject, or looking for a starting point. As such this would be a good place to start, and given that Tom Davenport has been a major contributor to the subject area over the last few years it probably makes sense to start with his latest work than one of the older volumes.

What is perhaps new is that Davenport turns and directly addresses the question: “How can we make knowledge workers more productive?”

Now this question goes straight back to Peter Drucker, indeed one may characterise it as Drucker’s challenge, as Davenport reminds us:

“To make knowledge work productive will be the great management task of this century, jut as to make manual work productive was the great management task of the last century.” Peter Drucker, Age of Discontinuity, 1969.

Davenport sets out to address this question – indeed I agree with him and Drucker, I also accept the challenge. In doing so he does offer us some advice and stories of what others have done but you aren’t going to come away from this book with a “35 things to do to make your knowledge workers productive” – actually, to be fair I don’t think such a list is possible but I’ll leave my explanation for another day.

So, what does Davenport tell us?

Well, he accepts that the Knowledge Management Systems (KMSs) pushed by software companies and consultants in the 1990’s are not the answer. However he does see a role for technologies, specifically communications (e-mail, telephone), Wiki’s and search – although the jury is still out on Blogs.

He also accepts that it is not about process – practice is perhaps more important. (I’ll write more about this as I progress though my current book Talking About Machines.)

Davenport also suggests “after action reviews”, or, as we in the software development community know them retrospectives. Now in the development community lots of us know about retrospectives, lots of us think they are good but few do them. And when they are they aren’t necessarily as effective as they could be. According to Davenport this situation is pretty common, we could all use retrospectives more effectively.

Another idea that rings true with software developers and their managers is HSPALTA – “high smart people and leave them alone.” This is a prevalent management technique the software arena, too many people – managers and developers alike – are only too happy to say “its the people who make the difference” and under this cover do nothing. We have to get away from this idea that because we did it like that yesterday we’ll do it like that today and tomorrow.

Overall though Davenport’s main insight is that knowledge workers are not homogonous. Different solutions apply for different groups of knowledge workers, e.g. scripting might work in a call centre but don’t try it with a consultant. This might sound like an obvious statement but until its made it perhaps isn’t so obvious – the label “knowledge worker” can hide a multitude of sub-divisions.

Before I close this review I do want to commend the author for good referencing and some actual research. When he discusses ideas form other authors he tells you who they are and were they said it so you can track back to their original work on the subject. Nor is he shy of discussing his own research findings.

What makes this unusual is too factors: first, as I’ve said before, books from Harvard Business School Press tend (ironically) to omit these details, second, the book is still very readable.

So on balance: if your new to the subject of knowledge work and knowledge worker productivity this is a good place to start. If your familiar with the subject you’ll probably still get something from this book but don’t expect all the answers.

I had intended to draw a line under my comments on the ACCU conference last week. I’ve got most of it out of my system but I had to return to Peter Sommerlad’s presentation – Only the code tells the truth.

Peter’s starting point was that, well, only the code tells you the truth about the system. That is the code, the stuff that is compiled and executed, not the documentation, not the specification, certainly not the UM and not even the comments but the actually lines of computer code.

There is nothing new in this assertion really. One of the things I had drummed into me by Derek Andrews when I was an undergraduate was: code is an executable specification, and as such it is the only completely accurate specification because, well, its the one that executes!

(And thanks for Hubert Matthews for a very interesting keynote at ACCU and reminding me that Derek is still out there practising software!)

Peter’s argument continues: if only the code is the truth what are we doing with all this other stuff? In fact, maybe a lot of what we think of as “good” software practice is actually mythology that has grown up around how we do it.

At one extreme some of this myth may be rooted in good intentions, it never did us any good but we thought it might and somehow we came to believe it. (I’d put the original ISO9000 in this category.)

Some of the other myths may have been true at some point in the past but we should really ask “Is this still good for us?” – perhaps we need to abandon some practices that were good once upon a time but don’t really add value any more.

One of Peter’s suggestions was the comments in code may actually detract from its maintainability. The argument goes like this: some comments are useful, many are useless (comment “increment i” before ++i for example), others are confusing, some are downright wrong. If the code is expressive enough then perhaps we don’t need comments in here at all.

This is pretty contentious stuff and unfortunately the group allowed ourselves to get side tracked down this avenue for 20 minutes or so when really is was just a side show.

Peters other suggestions included: strong typing may reduce understandability, design before coding can be detrimental, testing after we code is wrong, “everything is an object” and a few more too. Basically Peter is challenging us to look long and hard at some of the practices we engage in and ask: are they still useful? And so it was the session became a very interesting debate.

This opens a real Pandora’s box but its about time the software development industry engaged in some Myth Busting.

Here is a suggestion of my own for something we need to look long and hard at

Myth: accountancy correctly values knowledge based companies and their assets.
Is developing software an expense or an investment?

Most of the time when we develop software it is classed as a cost on the balance sheet. But in fact the result is an asset – software code – in which case we are increasing the assets the company owns. If this was a car or a factory it would be included on the balance sheet and it would be classed as an investment. So, £1 spent on development becomes £1 on the assets owned by the company.

Take this a step further; what about our people? – remember “our people are our greatest asset.”

In which case, sending someone on a training course isn’t a cost, its an investment and should be included on the balance sheet under assets. Companies regularly include “good will” on the balance sheet so why not people? And why not source code?

Once accept both these points the incentive for companies to invest in people and software increases drastically. No longer are these expenditures reducing profits, they are increasing assets. However, current accountancy doesn’t recognise this.