How many design innovation toolkits are there? The answer seems to be that there are more than you might think possible. Over a hundred are brought together on this page, which makes it an extraordinarily rich collection. There are lots of interesting-looking things here, some well known, others more obscure – though it’s hard not to come away with the thought that the world’s need for innovation toolkits has now over abundantly been met.
The bigger the underlying change, the bigger the second (and higher) order effects. Those effects often get overlooked in looking at the impact of change (and in trying to understand why expected impacts haven’t happened). Benedict Evans has always been good at spotting and exploring the more distant consequences of technology-driven change, for example in his recent piece on ten-year futures. ‘Cascading collapse’ is a good way of putting it: if the long-heralded but slow to materialise collapse of physical retail is beginning to appear, what consequences flow from that?
Today HMRC announced that 92.5% of this year’s tax returns were submitted online. That too has been a slow but inexorable growth, taking twenty years to go from expensive sideshow to near complete dominance. There is more to do to reflect on the cascading collapses that that and other changes will wreak not just on government, but through government to society and the economy more widely.
Interesting ideas on how to think about the future seem to come in clumps. So alongside Ben Hammersley’s reflections, it’s well worth watching and listening to this presentation of a ten year view of emerging technologies and their implications. The approaches of the two talks are very different, but interestingly, they share the simple but powerful technique of looking backwards as a good way of understanding what we might be seeing when we look forwards.
They also both talk about the multiplier effect of innovation: the power of steam engines is not that they replace one horse, it is that each one replaces many horses, and in doing so makes it possible do things which would be impossible for any number of horses. In the same way, machine learning is a substitute for human learning, but operating at a scale and pace which any number of humans could not imitate.
This one is particularly good at distinguishing between the maturity of the technology and the maturity of the use and impact of the technology. Machine learning, and especially the way it allows computers to ‘see’ as well as to ‘learn’ and ‘count’, is well along a technology development S-curve, but at a much earlier point of the very different technology deployment S-curve, and the same broad pattern applies to other emerging technologies.
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.
Sometimes the best way of thinking about something completely familiar is to treat it as wholly alien. If you had to explain a smartphone to somebody recently arrived from the 1990s, how would you describe what it is and, even more importantly, what it does?
In a way, that’s what this article is doing, painstakingly describing both the very familiar, and the aspects of its circumstances we prefer not to know – cheap phones have a high human and environmental price. An arresting starting point is to consider what people routinely carried around with them in 2005, and how much of that is now subsumed in a single ubiquitous device.
That’s fascinating in its own right, but it’s also an essential perspective for any kind of strategic thinking about government (or any other) services, for reasons pithily explained by Benedict Evans:
Periodic reminder: maybe 100 million people use any kind of pro PC app. 3 billion people have a smart phone, and that will rise to 5 billion people in the next few years https://t.co/NUtiAoOfS6
— Benedict Evans (@BenedictEvans) November 18, 2017
Anything that you can't do on mobile/tablet and can do on a PC is something that 90%+ of people couldn't actually do on a PC either.
— Benedict Evans (@BenedictEvans) July 14, 2017
Smartphones are technological marvels. But they are also powerful instruments of sociological change. Understanding them as both is fundamental to understanding them at all.
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.
This is an artful piece – the first impression is of a slightly unstructured stream of consciousness, but underneath the beguilingly casual style, some great insights are pulled out, as if effortlessly. Halfway down, we are promised ‘three big ideas’, and the fulfilment does not disappoint. The one which struck home most strongly is that we design institutions not to change (or, going further still, the purpose of institutions is not to change). There is value in that – stability and persistence bring real benefits – but it’s then less surprising that those same institutions struggle to adapt to rapidly changing environments. A hint of an answer comes with the next idea: if everything is the product of a design choice, albeit sometimes an unspoken and unacknowledged one, then it is within the power of designers to make things differently.
The problem with good policies, badly implemented is not primarily the bad implementation, it is that the bad implementation strongly suggests they weren’t good policies to start with. That’s the proposition advanced by this post, (and one interesting to read in parallel with The Blunders of our Government).
There are few examples of good but badly implemented policies because, in this approach, policy making is not – or not just – the grand sweep of a speech, but is the grinding detail of working through real world implications. Failure of implementation is therefore a strong indicator of a bad policy – akin, perhaps, to the idea that if you can’t explain a complicated thing simply, you probably don’t understand it.
How would you organise to impede transformational modernisation? You might set your face against all things digital, you might add as much stultifying process as you could find, you might just do things the way they have always been done.
This post explores how best not to do digital transformation, which turns out to be rather an interesting way of thinking about what it takes to do it successfully. There is a risk though of its becoming a form of confirmation bias: of course all those old ways were bad; of course the new ways are good. The risk is not that that is untrue, it is that it is not the whole truth. So perhaps there is another, harder, exercise to do after this one: assuming that the people who came before were neither malign nor idiots, why are things the way they are? What about the current way things were done has genuinely outlived its usefulness, and what was there for a reason? That’s not an argument for just keeping things as they were, but it may be an argument for making sure that we don’t throw away solutions without being clear what problem they belong to.
Rules are made to be broken. That’s an idea with considerable support from those on the receiving end of rules, rather less so from those who set them. Rules are the very essence of the Weberian bureaucracy which infuses governments and there are good reasons – fairness, clarity, consistency – why that is so. But that also means that bureaucratic organisations are designed to frustrate evolution and thus innovation – which is perhaps one reason why bureaucracies rarely communicate a sense of being on the cutting edge of innovation. And while bureaucracy is often used as a pejorative synonym for government, in this sense almost all organisations of any size are bureaucracies. Becoming adaptable and responsive isn’t just about breaking rules, it’s about adopting the expectation that rules are made to be broken.
What we get wrong about technology boils down to two things. The first is that simple, cheap and pervasive – and often near-invisible – technologies have more transformational power than things which are more obviously new and shiny; affordability beats complexity. The second mistake is to think that the impact of a new technology is driven by its technical availability, when the key date is its transition to economic and social availability, with lags which are sometimes very short but which can be very long indeed. This essay draws on examples from the invention of printing onwards to make the point that we might need to look in less obvious places for the technologies which will drive the next round of change.
All of that’s another way of putting the thought pithily expressed by Roy Amara:
We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.
The people with the shiny ideas and the shiny kit can see that change is essential and just know that their ideas are right as well as shiny. Unaccountably, the less shiny people with the unfashionable kit fail immediately to see the inherent rightness of the cause. This post has the superficial form of a rant, but it is a rant based on some important observations and a question without an easy answer: how do transformation teams understand and address the user needs of those whose fate is to be transformed?
Technology is never neutral. What gets developed, how it gets developed, and how it gets used are all driven by social, economic and political factors. People who build services are never neutral either and can certainly never be normal users of their own services. This article looks behind the internet of things to reflect on how completely frictionless transactions move power from consumer to provider, how what is normal for designers of such services is very different from what is normal for many of those who will find themselves using them, and how technology – and the data it moves and organises – is always about power.
Strategy is often seen as being about objectives and destinations. But there is no point in wanting to get across an ocean if you don’t have any means of getting there. Disruptive external change demands a response – but the nature of that response depends on where you start from and what means of transport are available, as much as it does on where you think you are trying to get to. Though the advice to set up a pirate camp within sight of the far shore depends on there being usefully positioned islands – and on being able to distinguish the Indies from America.
There’s more to innovation than having ideas. The innovation has to solve a problem (albeit sometimes made harder by the owners of the problem not knowing they have it). This article is written very much in a private sector context, where the test of successful innovation is sustainable profits, but it’s well worth thinking about how parallel issues play out in other kinds of organisations.
Some organisations manage to stimulate and thrive on innovation, others struggle to break out of their current world. Ideo, the design consultancy which knows a thing or two about this has identified six factors which drive organisations’ innovation capability (and has created a tool they call Creative Difference based on them). At one level there is nothing surprising about those six capabilities (perhaps it would be more surprising if there were), but they combine to make a good challenge to organisations on whether they are capable of being – or even really want to be – innovative.
The future is mostly just what happens. But it’s also partly what is imagined and encouraged to happen. This article is about companies in the business of telling stories about the future. Whether they are predicting a future, telling stories about a future, or making a future happen is the central question, which is touched on but never answered. And unsurprisingly, but equally unspoken, the imagined future meets the very present needs of those who commission it.
When new technologies arrive, they usually claim to be offering compelling solutions. But all too often, the clarity of the solution is not matched by the clarity of understanding of the problem it is claimed to solve. Despite the listicle headline, this is an excellent post setting out five tests for distinguishing the genuine new opportunities from the hype.
Is government organised so as to make innovation difficult? That’s not a new question (to put it mildly), but this post approaches the question through the lens of organisational debt, which produces some slightly newer answers. Not surprisingly, though, there is nothing very surprising about those answers: large, cumbersome organisations with a conservative approach to change need more than just simple ambition to become something else.