There are increasing numbers of government services which are digital. But that doesn’t make for a digital government. This post is a challenge to set a greater ambition, to make government itself digitally transformed. As a manifesto or a call to arms, there’s a lot here: a government with the characteristics envisaged here would be a better government. But in general, the problem with transforming government has not been with describing how government might work better, but with navigating the route to get there – and that makes the question in the title critically important. Ultimately though, the digital bit may be a critical catalyst but is not the goal – and we need to be clear both about the nature of that goal and about the fact that digital is a means of transforming; not that transforming is a means to be digital. This post describes powerful tools for realising an ambition for better government – but they will have effect only if both ambition and opportunity are there to use them. On that, it’s well worth reading this alongside Matthew’s own post earlier this year commenting on the government’s digital strategy.
This is a video of Ben Hammersley talking about the future for 20 minutes, contrasting the rate of growth of digital technologies with the much slower growth in effectiveness of all previous technologies – and the implications that has for social and economic change. It’s easy to do techno gee-whizzery, but Ben goes well beyond that in reflecting about the wider implications of technology change, and how that links to thinking about organisational strategies. He is clear that predicting the future for more than the very short term is impossible, suggesting a useful outer limit of two years. But even being in the present is pretty challenging for most organisations, prompting the question, when you go to work, what year are you living in?
His recipe for then getting to and staying in the future is disarmingly simple. For every task and activity, ask what problem you are solving, and then ask yourself this question. If I were to solve this problem today, for the first time, using today’s modern technologies, how would I do it? And that question scales: how can new technologies make entire organisations, sectors and countries work better?
It’s worth hanging on for the ten minutes of conversation which follows the talk, in which Ben makes the arresting assertion that the problem is not that organisations which can change have to make an effort to change, it is that organisations which can’t or won’t change must be making a concerted effort to prevent the change.
It’s also well worth watching Ben Evan’s different approach to thinking about some very similar questions – the two are interestingly different and complementary.
There are some who argue that the only test of progress is delivery and that the only thing which can be iterated is a live service. That is a horribly misguided approach. There is no point in producing a good answer to a bad question, and lots to be gained from investing time and energy in understanding the question before attempting to answer it. Even for pretty simple problems, badly formed initial questions can generate an endless – and expensive – chain of solutions which would never have needed to exist if that first question had been a better one. Characteristically, Paul Taylor asks some better questions about asking better questions.
This wide ranging and fast moving report hits the Strategic Reading jackpot. It provides a bravura tour of more of the topics covered here than is plausible in a single document, ticking almost every category box along the way. It moves at considerable speed, but without sacrificing coherence or clarity. That sets the context for a set of radical recommendations to government, based on the premise established at the outset that incremental change is a route to mediocrity, that ‘status quo plus’ is a grave mistake.
Not many people could pull that off with such aplomb. The pace and fluency sweep the reader along through the recommendations, which range from the almost obvious to the distinctly unexpected. There is a debate to be had about whether they are the best (or the right) ways forward, but it’s a debate well worth having, for which this is an excellent provocation.
“Transformation” is a dangerous word. It is bold in ambition, but often very uncertain in precision. Instead of attempting yet another definition, as part of yet another attempt to tie the concept down, this post sets out eight powerful design principles which, if applied, would result in something which pretty unarguably would have delivered transformation. Perhaps transformation isn’t what you do, it’s how you tell what you’ve done.
But whatever the level of ambition, there is a lot in these apparently simple principles – well worth keeping close to hand.
It’s a rare treat for a site with an audience disproportionately made up of practising bureaucrats to point to a post which begins by describing bureaucracy as one of humanity’s best inventions. But there is, not surprisingly, a sting in the tail: the very qualities which are the strength of bureaucracy are the downfall of creativity and innovation. The answer suggested here is ‘Parallel Learning Structures’. From the description in the post, the recent flurry of policy labs, innovation spaces and agility in governments has strong if unwitting resonance, with that approach – but the question, as ever, is how to move these approaches from the margin to the core.
Not everything governments do is for and to people. Governments also do things with and by people. Sorting the roles of government by preposition is arrestingly simple and unexpectedly powerful. Government involves for, with, to and by; good government uses them appropriately and gets the balance right between them.
This elegant short post is also a powerful – if indirect and possibly unintended – challenge to the naive view that government is reducible to service design.
There is lots of attention and activity around the question of how government should be made to work better, and in particular how it should be made to work better with modern technology. There is much less attention given to the question of why doing that is a good thing. This piece is an attempt to fill that gap from somebody who has been thinking about these issues pretty much from the beginning. It’s an extremely good first answer, but it is, of course, not the only one possible. It will be interesting to see if others rise to the challenge Tom poses.
This is a good antidote to the kind of technological determinism which is a frequent substitute for strategic thinking. It recognises instead the importance of social and economic consequences of new technologies and, crucially, that they take a long time to play out. It is slightly weaker on introducing a new emphasis on data to the discussion, rightly recognising that traditional legal and regulatory models don’t easily fit the dispersed complexity of data, but perhaps missing the thought that data is already showing strong signs of following the stages towards organisational capture described by Tim Wu in one of the books which are the foundation for this article.
This is a powerful challenge to everybody who works in any part of government. The system is fundamentally broken because its components were never designed or intended to act coherently and effectively as a system – and they don’t. There is considerable power in that diagnosis, implying if not quite drawing the conclusion that if you want to change the system, you have to change the system. The problem, of course, is that that is both intrinsically very hard to do and never seems to be as important or urgent as addressing specific policy problems – which is where we came in. So the hard question is not whether a better system could be devised (because there can be little doubt that it could be); it is whether the current system has the capability to make the changes needed. It is hard to stop and start again from scratch. That’s not just true of the UK – it has been argued that the most needed amendment to the US constitution is to make it easier to make constitutional amendments, which is probably impossible. None of that makes Straw’s diagnosis wrong, but it does underline that the route to change is as critical as the destination.
There is a caricature of policy making in which it is presented as an exercise in introspection, free of evidence and free in particular of contact with those who might experience and understand the context and impact of its delivery. Like all good caricatures, there is something recognisable in that, and like all good caricatures, those caricatured more easily see the distortion than the likeness.
The underlying challenge in this post is a good one. Emphasis on things which can be measured distorts attention from things which may be just as important but are more elusive. Understanding the variation around a central figure is as important as understanding the central figure itself – and can tell you very different things. Broader and more qualitative approaches are an essential complement to narrower and more quantitative ones.
But policy makers are people too. Dismissing them as ivory towered elitists is too easy. It would be good to have more empathetic policy makers, but more empathy with policy makers is part of what we need to get there. Policy making is itself the product of a system – and understanding the drivers and behaviours of that system is the essential first step to changing it.
Not at first sight an obvious entry for inclusion here, but indirectly very relevant to thinking about the impact of change on large organisations. The size and complexity of organisations, it is argued, is a function of the relative costs of internal control and market transactions – whether it’s cheaper to make or to buy. That is in turn in part a function of the cost and availability of information. And so the conclusion is reached that digitally-based organisations will be smaller and fleeter of foot than their predecessors and that large ungainly organisations of the pre-internet era are doomed to extinction, with government in their current form being among those whose demise is inevitable.
In some circles, that conclusion is seen as an obvious one. Farrell’s argument is that something critical is missing from the analysis, the self-interest of individuals, and that when that is factored in, the picture looks very different. That matters not to justify slow change in large organisations, but to explain that power relations are a critical part of understanding the overall situation. And as long as they remain unequal, the pop up employer is likely to remain intriguing at the margins, rather than central to how stuff gets done.
Complicated problems can be solved; complex problems can only be managed. Complicated problems can be addressed algorithmically; complex problems require creativity and adaptability. This article is more concerned with describing that distinction then addressing it, though that may just reflect the fact that it is an extract from a book, It’s Not Complicated: The Art and Science of Complexity in Business, which no doubt provides a fuller account.
In a world of complex problems, plans and strategies do not align tidily with results, which is a reason for approaching them differently, rather than not having them. And that in turn requires organisations which can be comfortable with uncertainty and ambiguity.
A smart and pithy presentation on what strategy is – and isn’t – from the point of view of a digital service designer. Sophie is also the author of Adventures in Policy Land – a reflection by an agile non-government non-policy person on creating government policy in an agile way
This is a post about black elephants: events widely predicted by those in a position to know, but found totally surprising when they actually happen, or elephants in the room retrospectively declared to be black swans. The Grenfell Tower fire was surprising and shocking – and at the same time, predictable. That puts it in a category of things which human institutions seem particularly bad at dealing with, where a problem builds up slowly and almost asymptomatically until suddenly a tipping point is reached, by which time addressing it has become massively more difficult. At one level, the solution to that is obvious – but that doesn’t seem to make it any easier to do in practice.
And it’s perhaps worth saying that this quite abstract way of thinking about disasters is not an attempt to distract from the human tragedy, but on the contrary is a way of recognising and understanding that we need to deal with structural as well as particular issues if we are to see fewer black elephants in future.
Paul Maltby asked on Twitter
What would you put on a reading list for gov policy people eager to dig deeper on digital?
— Paul Maltby (@maltbyps) June 20, 2017
The collected answers – crowd sourced in short order – make up an impressive list. It’s inevitably a bit uneven, but there is a lot of good stuff there, and it’s well worth dipping in to.
— Paul Maltby (@maltbyps) June 21, 2017
Predicting the future is hard. Predicting the second and third order consequences of your first prediction is much harder – but it is those consequential effects which really drive the wider social, economic and other impact. This post is about what happens when vehicles are electric and autonomous, and teases out potential changes ranging from reduced tobacco consumption (because in the US most tobacco is bought at petrol stations) to changing patterns of land use.
It’s a characteristically interesting read – but the reason for including it here is less to do with the cars and more to do with its being an example of a way of thinking about the future. It uses a challenging assumption as a starting point – in this case that autonomous vehicles will change cities as much as cars have done. It focuses less on the initial change and more on the ripples that causes. And it recognises that this can only be a way of exploring possible futures, not of predicting a specific one.
Good policy comes from good policy making. There is plenty of evidence that good policy making is based not just on the rigorous analysis and evidence assessment which is the best of the traditional approach, but also on effective implementation and deep understanding of the needs and behaviour of those who will be affected by the policy. This post argues for a more broadly based approach to policy making, drawing on The Blunders of Our Governments (which remains compelling reading) to make the case.
The problem with this is not – as the author supposes – that it sounds fanciful – it is that it sounds obvious. The problem is not in recognising that policy were better done differently, it is in the doing of it. The post introduces a more substantial paper which has some useful material, but ends up describing barriers to change without offering much about how to overcome them.
A useful diagram with quite a good article wrapped round it. If there is strategic value in organisational alignment, whose responsibility is it for ensuring that that alignment is achieved? Everybody, nobody and the chief executive are all unsatisfactory answers – and the article raises, but doesn’t really attempt to answer, some important questions about how to achieve alignment in a complex organisation under constant pressure to focus on short term issues.
Echoing some of the same themes as Simon Wardley’s approach, this post argues the need for strategies to be developed with an understanding of movement and direction, rather than position – and to forge strong connection between the long term question, ‘where do we want to be?’ and the short term question, ‘what are the key choices we face now which will determine whether we are on the trajectory to get there?’