Mekala Krishnan, Jan Mischke, and Jaana Remes – McKinsey Quarterly
In 1987, the economist Robert Solow observed that the computer age was everywhere except for the productivity statistics. In some sectors, that started to change a decade or so later. Now, a further two decades on, the nature of ‘the computer age’ is very different and there is a further round of technology-driven change with even greater potential than the last one. The main conclusion of this article is that there is another surge of productivity growth waiting to be captured, though acknowledging some significant transition inefficiencies along the way. And there are still wider effects not directly reflected here – autonomous vehicles, for example, have the potential to be more immediately efficient but might add to externalities elsewhere through increased congestion.
Stepping back from that, perhaps the deeper message of Solow’s paradox, now as much as when he posed it, is that technology-based change is never just about the technology and that understanding the social and economic context in which it is deployed is always a vital part of the overall picture.
Adewale Maye – CEPR
The rise of the gig economy and the relentless undermining of traditional employment structures is often seen and presented as an inexorable characteristic of modern digital economies. That’s partly a consequence of skewed observation, partly a recognition that organisations can increasingly trade rich information for formal structures, and perhaps partly a change in the reality of people’s working lives. This article addresses the last of those points using recent US data – and concludes that the number of people working in the gig economy is small and growing only relatively slowly.
That’s a helpful balance to some of the hype, though it does unavoidably leave one of the central questions unanswered. If we can, to adapt Solow’s paradox, see the effects of the gig economy everywhere except in the productivity statistics, is that because they aren’t there to be seen, or because we are at the very early stage of what may be exponential growth? Perhaps, as with Solow’s original, it will take a decade or two to tell.
Richard Pope – Platform Land
The idea of describing things in terms of stacks is a familiar one in the worlds of technology and of operating models. It’s not such a familiar way of describing government, though it’s an idea with an honourable history, including Mark Foden’s essential summary in his gubbins video.
This post is a trailer for a series of forthcoming posts under the banner of Platform Land, which promises to be compelling reading. That promise rests in part on the recognition in this introduction of the fact that governments are both organisations with much in common with other kinds of organisation and at the same time organisations with some very specific characteristics which go well beyond service delivery:
Considerations of safety, accountability, and democracy must at all times be viewed as equal to considerations of efficiency.
The emergence of government platforms represents a new way of organizing the work of government. As such, the task at hand is not to understand how we patch existing systems of government, but of how we adapt to something new that will come with its own set of opportunities and challenges, risks and prizes.
Richard Pope and James Darling
What do you have to do to make government work better? People have been asking that question for a very long time (it’s over 150 years since the Northcote-Trevelyan report asked a version of it for the UK government), but answers continue to be elusive.
Ten years ago, there was an attempt to approach the problem bottom up rather than top down: demonstrating better government by building some small pieces of it to demonstrate what could be – and should be – possible. It was an attempt which was small to vanishing in its direct effect, but was an influential precursor of much of what followed. That influence is still visible in the way things get designed and built across government, but something of the radical edge has got lost along the way.
This post both celebrates what was done in those heady days and poses the challenging question of where the equivalent radicalism needs to come from now. Gradual change is not enough, it argues, now is not a time for patching. Given that build up, the call to action falls a little flat – a resounding cry for a committee of enquiry into the civil service hardly sets the heart racing. But the fact that better answers may be needed emphasises rather than undermines the power of the question.
Adam Grant – Sloan Management Review
It is counter intuitive that insights don’t have to be counter intuitive.
There is excitement and recognition in grand discoveries, uncovering what we didn’t know as a critical step towards doing a better thing. The bigger the surprise, the better the achievement. And at the other end of the spectrum, the time honoured way of sneering at consultants is to say that they have borrowed your watch so that they can tell you the time. Over and over again, though, big organisations pay expensive consultancies to do exactly that. There are various reasons why that might be rational (or at least understandable) behaviour, one is perhaps that the obvious is not actually obvious until it is made obvious.
This interesting article expands on the power of obviousness made obvious as an enabler and driver of change. It’s focus is on internal management practices, but the approach clearly has wider application:
Findings don’t have to be earth-shattering to be useful. In fact, I’ve come to believe that in many workplaces, obvious insights are the most powerful forces for change.
Rachel Hope – DfE Digital and Transformation
Most of government is mostly service design most of the time. That’s a pithy and powerful assertion, and has been deservedly influential since Matt Edgar coined it a few years ago. But influential is not the same as right – and indeed the title of Matt’s original blog post ended more tentatively with ‘…Discuss.’
This post, which is in effect a case study of acting as if the assertion were true, throws useful light on what it could mean. In doing so it makes it easier to see that there is a risk of eliding two questions and that it is worth answering them separately. The easy first question is whether policy and delivery should understand and respect each other and expect to work in close partnership – to which the answer must be yes. The harder second question is whether the venn diagram does – or should – eventually consume itself to become a single all encompassing circle. Verbally and visually, the argument of this post it that it does, and that argument is powerfully made in respect of the service it describes. But that still leaves open the question of whether the model works as well when the service is less specific or delivered less directly.
Theo Bass – Nesta
Discussions of the application of digital to democracy tend to get bogged down quite quickly in the (limited) merits and (extensive) risks of online voting. A more promising approach is to look at ways in which digital technologies can support and amplify democratic processes, more to do with deliberation and engagement than with quantification. This is still new territory, so experimental approaches still make good sense, but as this post brings out, there are now enough of those experiments around the world to start to group them and to see common opportunities and challenges.
‘Start with user needs’ has been the mantra of digital government since the early heady days of GDS. It’s a thought which is simple, powerful and – this post argues – wrong. Or, more accurately, unhelpful: it’s a concept which both lacks precision in its own right and risks being too tightly coupled to the construction of solutions.
This is not some random hit job, but a deeply reflective post which brings out clearly where user research most adds value, by being still clearer about where it doesn’t. In doing so it draws out a point which is relevant and important to a much wider audience. It positions user research as a means of reducing risk – and that is important not just as a way of helping senior decision makers see the value in it, but because basing decisions on unexamined and untested assumptions leads to bad consequences (and has been doing since long before government was digital).
Alan Mitchell – Mydex
Debates about personal data have a tendency to be more circular than they are productive. There is – it appears – a tension between individual privacy and control and the power unlocked by mass data collection and analysis. But because the current balance (or imbalance) between the two is largely an emergent property of the system, there is no reason to think that things have to be the way they are just because that is the way they are.
Given, though, that we are where we are, there are two basic approaches to doing something about it. One is essentially to accept the current system but to put controls of various kinds over it to ameliorate the most negative features – GDPR is the most prominent recent example, which also illustrates that different political systems will put the balance point in very different places. The other approach is to look more fundamentally at the underlying model and ask what different pattern of benefits might come from a more radically different approach. That’s what this post does, systematically coming up with what will look to many like a more attractive set of answers.
Mydex has been building practical systems based on these principles for a good while, so the post is based on solid experience. But therein lies the problem. Getting off the current path onto a different one is in part a technical and architectural one, but it is even more a social, political and economic one. As ever, the hard bit is not describing a better future, but working out how to get there from here.
Adrian Brown – Centre for Public Impact
Everybody is in favour of evidence-based policy – by definition it must be far superior to the policy-based evidence with which it is often contrasted. This post is a brave challenge to the assertion that there is an evidence base for evidence-based policy. In particular, it argues first that weak evidence can be unwittingly assembled to appear misleadingly strong and in doing so close down policy options which should at the very least be kept open; and secondly that experimentation is a better approach, precisely because it avoids forcing complex issues into simple binary choices.
That’s not an argument that evidence is unimportant, of course. But it’s a good reminder that evidence should be scrutinised and that simple conclusions can often be simplistic.
This is the recording of an event at the Institute for Government this week, in which Jamie Susskind starts by briefly introducing the arguments of his book, Future Politics, and then discusses them with Gavin Freeguard – and as the book weighs in at over 500 pages, this might be a gentler way in. Susskind approaches the question of the title from the perspective of politics and law, coming back to the question, how much democracy is the right amount? That’s a harder – and more important – question than it first appears. Answers to it have been evolving for several thousand years, but digital technology gives it a new urgency, for reasons which range from the manipulative power of social media, the elimination of leeway, to bot-driven perpetual voting.
In the last century the fundamental question was, what should be done by the state and what should be left to the market and to civil society? … In our time, the key question will be this, to what extent should our lives be governed by powerful digital systems, and on what terms?
Dan Hill – But what was the question?
This is quite a demanding essay. It demands some time to read, at about 6,000 words, and it demands more time to reflect, not least because it is subtly challenging. How do we design our interaction with our urban environment in a world of new technologies? How do we balance optimisation for individuals against optimisation of wider systems? How, more broadly, do we ensure that social objectives drive the adoption and deployment of technology rather than being driven by them? Or to step back from the detail (and in some ways from the specific subject), there’s a pretty strong consensus on what user centred design means for individuals; much less so on what it might mean for groups of people whose lives and activities intersect and affect one another.
There are clear examples of what new approaches to design might look like and of how they have been applied. But there isn’t much here about the social and political approaches which create the space for those design approaches to flourish. It’s unfair to criticise this essay for not doing something which it makes no claim to do, but the concept of ‘strategic design’ it introduces perhaps has a further level still.
Alexis Madrigal – The Atlantic
It should by now be beyond obvious that technology is never just about the technology, but somehow the hype is always with us. This article is a useful counter, listing and briefly explaining seven reasons why autonomous vehicles may not happen and may not be an altogether good thing if they do.
It’s worth reading not only – perhaps even not mainly – for its specific insights as for its method: thinking about the sociology and economics of technology may give more useful insights than thinking just about the technology itself.
Catherine Howe – Curious?
This short post is more of an aside than a developed argument, but from this source it’s not surprising that even an aside contains a couple of memorable and provocative thoughts.
The first is an expansion of the title, which nicely echoes Emily Tulloh’s recent post:
Strategy is a tricky business. Too much and you end up endlessly thinking and not doing. Too little and you end up just reacting.
The second part of the post turns to the temptations and risks of being a leader in a hierachy:
It’s very seductive to be in a leadership position as the whole system is biased towards enabling you to be right
Been Kim – Quanta Magazine
The problem of the AI black box has been around for as long as AI itself: if we can’t trace how a decision has been made, how can we be confident that it has been made fairly and appropriately? There are arguments – for example by Ed Felten – that the apparent problem is not real, that such decisions are intrinsically no more or less explicable than decisions reached any other way. But that doesn’t seem to be an altogether satisfactory approach in a world where AI can mirror and even amplify the biases endemic in the data they draw on.
This interview describes a very different approach to the problem: building a tool which retrofits interpretability to a model which may not have been designed to be fully transparent. At one level this looks really promising: ‘is factor x significant in determining the output of the model?’ is a useful question to be able to answer. But of course real world problems throw up more complicated questions than that, and there must be a risk of infinite recursion: our model of how the first model reaches a conclusion itself becomes so complicated that we need a model to explain its conclusions…
But whether or not that is a real risk, there are some useful insights here into identifying materiality is assessing a model’s accuracy and utility.
David Birch – Wired
David Birch is one of a pretty small group of people who write sense about money and identity – and he is pretty much unique in doing so with wit and lightness of touch. This short article draws out the connection between identity and attribution. We will increasingly need to know and trust the attributes of robots and systems, we will increasingly be interested in what attributes people assert about themselves – and at the intersection of those needs there will be a particularly precious attribute:
In time, IS_A_PERSON will be the most valuable credential of all.
Emily Tulloh – Futuregov
This is a post about what’s involved in doing service design and, taken at face value, it’s a pretty good one. But it also works as an extended metaphor for other kinds of change development, and for strategy in particular. Figuring it out and making it real are presented here as the fundamental stages of service design – but pretty much everything said about them works in terms of strategy too.
One version of that parallel is drawn within the post itself, with figuring it out equated to strategy and making it real equated to delivery. But it also works – and arguably works better – to see strategy as the parallel to the whole service design process: a strategy which does not take account of its own approach to delivery is one with a pretty important gap.1216ethn
Successful strategy involves both the destination and the journey, and because of that (though not only that) successful strategy is inextricably linked with successful leadership. This text of a recent speech is not only a powerful account of one person’s development as a leader, but is also a manifesto for a kind of leadership which is very different from the norm of the civil service (which is the context for both Clare and her audience). Clare talks about conformity and rebellion – and about ‘tempered radicals’ who tread a fine line between the two. That’s a place occupied by strategists too: being as constructively disruptive as is humanly possible up to and beyond – but not too far beyond – the capacity of their organisation to manage change effectively.
Bas Leurs and Kelly Duggan – Nesta
Testing, piloting, prototyping and a few more words besides all mean something similar, but all mean something different – though whether we would all agree on quite what the differences are is another matter.
This post sets out to distinguish and to map the scope of four approaches and to argue for greater rigour in their usage. The distinction is definitely useful and the rigour is definitely desirable, though the quest for absolute rigour of specialist language in general usage tends to end in disappointment. But that’s not a reason not to be as clear as possible, and it’s certainly not a reason for practitioners to be anything other than precise both in their understanding of what they are doing and in how that understanding is shared.
Audree Fletcher – Medium
This is a short, elegant, epistolary post on how design and policy come together – or rather about how they might do so better. There often is a gap between policy thinking and design thinking, though one that’s more an accident of history and career paths than of underlying incompatibility. But the contrast sketched here perhaps over-emphasises aspects of the difference: many politicians are interested in more evidence-based and iterative policy development, the trick (as the post recognises) is doing that in a way which creates a space for things not to work without being labelled as failures. And that should be one of the ways in which more traditional policy making skills complement design-based approaches.
Of course it doesn’t always work in that relatively benign way, far from it. But there are great insights here into how it might work better more often.