Victory which upsets the Apple Cart

It is with a real sense of despair that I read the inner details of the Apple vs Samsung case in America. The verdict is well-known, Apple won, and with it they are following up with an injunction against Samsung selling their products in the US. At the same time Samsung will appeal.

As a patent holder myself and following a career of working in Pharmaceuticals I recognise the necessity of patents to propagate science and reward the inventor. The principle is sound but this application is problematic – both in the way the verdict was legally stage managed and in the scope of the patent.

First on the stage management: Apple played a dangerous game and set a worrying precedent for them, their psychological trump card (meticulously but negligently developed by their lawyers) was to present the jury with a ‘checking’ of rights and wrongs [mark if you agree there was an infringement]. This compared essentially one Apple model against a multitude [20 or so] models from Samsung and was a successful psychological bear trap. The evidential bias was overwhelming, on every line of every table, the jury ran through whether the Samsung Galaxy, Galaxy S2, …… infringed against the one Apple product. The way this stage management stacked the cards is a well-known phenomenon to anyone doing preference scales [for example the Lickert tests]. People have a natural tendency to avoid the extremes (all guilty, or all innocent)  instead they go for the middle, for Apple the middle was enough and whilst not every Samsung model was guilty of infringement they were found guilty of infringement for many models – game over the injunction cites 8 devices enough to wipe $8bn off Samsung’s share price.

But this is a pyrrhic victory, by suggesting this analytical framework for judgement Apple have upset their own Apple cart. Now the very many vendors of iPhone or iPad competitors can line up their array of products against Apples single product – there are any number of technologies and ideas that Apple have embedded within iPhone which they do not hold exclusive rights to. So imagine the orchestrated case on iPhone infringements arrayed against the various phones from Nokia, Samsung, HTC and so on. Now use the same rigged psychology of long tables of feature comparisons and very soon there will be a vote against iPhone, an infringement that will inevitably be followed by a marketing injunction which for Apple does not take a single product away but takes their entire market away. Who is the smart lawyer now? Of course Apple may argue ‘double jeopardy’ but by adding ‘noise’ into the legal system they make the outcome a lottery, a lottery in which those with more stakes will win (as an American might say it’s the math stupid!).

The next worrisome aspect of the Apple finding is the inseparability of the invention in the field of usability patents. Usability patents are unlike (say) Pharmaceuticals where discrete stand-alone technologies are functionally and operationally distinct – for example a cardiovascular agent is ineffective in respiratory disease. The ‘rubber-band’ is a neat trick to a common problem embedded in an ocean of other neat tricks. By their own reckoning Apple have around 15% of the smart phone market and, as Esther Dyson points out, usability is familiarity. So perhaps Apple do indeed have a novel feature in their user interface but this is a feature that only 15% of all smart phone users will get to know and love, the mass of the market will (now) have to achieve the same end point in a different way via a yet to be programmed technique. Instead of being a beacon for the mainstream the Apple interface will become the mine-field of tricks to be avoided by the rest of the market. It will be technological Esperanto – undoubtedly better and aesthetically pure – but used by very few people and beaten in practicality by the mongrel languages such as English, French, Chinese etc. Here the patent ruling is the stark warning ** do not follow **, and many other thinkers from Ghandi onwards have made the point that leaders need followers.

Usually posts on companies end with a short statement on the authors vested interest in the subject, I can state I own no Apple shares but if I did I would sell now.

If only my thumbs …..

Now that i’ve modernised and integrated my socialtech (Android, wordpress 3.1, google docs viewer for original msoffices docs & pdf, and plug ins <> twitter) … all that slows my productivity my 0th generation thumbs.

Seriously amazing technology – with all my stuff mastered to my own server

Next step an open source term extractor – I’m trying KEA – any other ideas?

Mobs, rabbles, ideas and progress.

Reactions to the IFG Report

After being part of the team that put the IFG report together on Systems Failure I am both encouraged by the response but concerned about the range of opinion. Opinion is good and democratic but often not helpful when it comes to being able to deliver something. In reacting to discordant voices the conditioned response is more likely to be either blind stridency on the part of the report authors or accommodation which leads to death by 1000 ideas as studied by Belbin on the collective IQ of teams..

Ideally the response is to synthesise a solution from as many differing opinions as possible but at the same time remain capable of coherent action. The love it / hate it opinion on agile forces the either/or dichotomy of managing which generates the pendulum swing of management fashion oscillating from one extreme to another. Discordant strident voices become the trigger for management fads and the reified “”my way”” is best simplify defies the reality of the problem being tackled.

As a skilled manager, or sane individual, you avoid the worst of extremes and learn by integrating the potential of new ideas with the practicality of the old ones. The passion of the zealots may inspire the heart but all too often they mess with the head. If in doubt try the simple diagnostic of “when good ideas go bad” where too much of a good thing become toxic – in the lab carrot juice can kill not because it is inherently toxic at low levels but in extremis the toxic limit is reached.

This thinking brings me to one of the key challenges and core peeves around IT. I also have a background in Operations Research (70’s discipline) or Systems Thinking (popular 00’s term for the same thing) so I recognise the need to understand the problem before rushing into a solution. And it is precisely ‘solutionology’ that generates much of the disconnect in IT generally, in big IT and big bad government IT. Einstein recognised this in his writing “If I was engaged in a really difficult task and had just one hour to live I would spend at least 55 minutes on trying to understand the problem as I know that once I understand the problem the solutions come easily“.

Recent material on scale would suggest that per-se scale is bad and certainly government IT see scale as special. Inherently it is neither bad nor special. Large and successful IT implementations dwarf both government IT and gives proof that scale does work – it also begs the question of your problem understanding, design and applicability in cases where it does not. But it should not provoke a luddite response as seems fashionable from some consultants. And before you condemn big failed IT projects (such as the national identity card) think first how big successful IT systems work (such as Visa or Google).

The report took some time to consider procurement. For me the damning statistic is to compare the average 77 weeks for major procurements and the 5 years in which Facebook has come from nothing to 25% of the US web traffic – or just 4 procurement cycles. It is here that the simple logic of agile – iterative learning the problem and progressively delivering solutions – can make a big difference, in the video I suggest that it is not failure of government IT that is bad, but it is the long, slow and expensive failure of government IT that sees the worst of all possible outcomes. Small companies, entrepreneurial outfits and researchers are not immune to failure – but they learn to fail fast and fail cheaply! Perhaps the successes would look after themselves if the failures could be managed cheaply, and whilst agile approaches handle success and failure equally well the established methods manage only success.

Although we had a number of discussions on risk here too Agile makes a difference. Simply by making the productive focus on workable components progress is evident and the need to ‘trust and verify’ can be managed around the tangible outputs and outcomes of work. Much of institutional attitude to risk is around proxy measures to verify hidden progress or measure inputs as a proxy for outputs. The academic theory of agile management draws from the manufacturing revolution in reducing queues, making work visible, eliminating waste, managing by outcomes and navigating by customer pull. It is only now being applied to IT development. Every supplier organisation should welcome this remembering, of course, that their reputation is sustained on the last thing they delivered.

From the comments there are already some terrific ideas, deep expertise and substantial knowledge that can help government IT but every idea is amplified by its integration with others as opposed to standing in splendid isolation. Drawing from Leon Walras’s economic theory of utility the best ideas are the product of the quality of the idea and its adoption …

On the Toxicity of good ideas

When Good Ideas go Bad

My thinking for this last week has focused on the report “Systems Failure” published by the Institute for Government and the associated blog and twitter discussion [#ukgovit]. There are some really good comments but together they represent a cacophony of ideas – distilling a course of action, of best advice, from the din of divergent opinion is problematic.

The Value of Ideas – Quality * Coherence

It is all so reminiscent of my time at the British Computer Society Healthcare Group just prior to the launch of the National Programme of Health, which became Connecting for Health and which history recognises as one of the largest failed promises in IT. Why so, how did this happen and were the ideas people responsible [not simply the Dilbert like cadre of dumb managers].

Really then what happened was that the enthusiasm and ideas of the  innovators produced the spark that something needed to be done but, of themselves, they were incapable of making it happen – too many strong opinions, to many divergent views and simply too many obdurate arguments What then should a policy maker do?

In this case Tony Blair brought in the consultants – who from the power of bogus abstraction – captured the promise of the gaggle of enthusiasts but with the veneer of coherence. Their Powerpoints suggested it could be done – wait – that they could deliver the world’s biggest IT project and that the commercial processes would help identify companies experienced enough to do the work and big enough to handle the responsibility.

companies experienced enough to do the work and big enough to handle the responsibility? [My analytical mind objects to this last – experience is a learning and size is a matter of diminishing populations. Small companies learn big companies copy. The outcome was evident for anyone who know statistics – the qualification of size produced such a small number of firms that delivered a thin envevlope of experience].

The situation was obvious if you spoke to the project teams withing the large (and now loss making contracts). Why were you chosen? because we are big. Have you done anything like this before – no! All of the expertise from the passionate, knowledgeable enthusiasts was discarded – not because of the quality of their individual ideas but because together they became toxic. Anmd of course the debris of the National Programme continues – a renewed skepticism about IT projects, a missed opportunity, good experience ignored and financial waste.

In another post I have introduced Belbin’s ideas on destructive IQ.

Statistics 101

The situation also reminds me of one of my first faux-pas at work. In my early career for a software company I was considered the statistics experts due to my ‘nerdy’ behaviour – fine I relished it long before geek was cool. At a management meeting the operations director of the software house showed a plot of project performance – with the project size graphed against the project estimating (and hence profitability) with some 50 points on the graph some 40 appeared strongly correlated with a reasonable scatter – an excellent basis for a commercial company. The remaining 10 were for big projects and showed significant f not random scatter.

Invited by the Ops Director to comment on my advice – my immediate response was “do’nt do big projects“. This was the message from the data but not the message the company wanted to hear – who were building their business on large projects. It was also not the most astute answer but, 3 years later, after I left the company it was proved to be correct. The company lost money and was taken over as a result of dependency on large project. They were just too impatient to learn!

And so

Just two things to do ….

  1. To quote Bob Dylan – It’s peace and quiet we need to go back to work again – hopefully taking just a few of the really good ideas with them. Not necessarily the best ideas, but the one that play nicely together
  2. Learn about the zone of statistic significance for experience – and take your time and your opportunities to build experience