Anyone who has anything to do with the world of technology will be familiar with the hype cycle - first developed by Gartner.

A new technology emerges. Experts tout it as the solution to all problems. Commentators buy into the excitement and echo it until it becomes common wisdom. It fails to meet those inflated expectations, leading to disillusionment. Gradually a more rational view of the technology’s potential emerges. Then, finally, the real work gets done.

And repeat.

In the context of government and public service innovation, we’ve seen the hype cycle with smart cities, big data, the internet of things, open data, blockchain, digital government, virtual reality and AI, to name just a recent few.

So here’s a question:

Given that the hype cycle appears to be predictable, is there a way to bypass the peak and the trough and get to the plateau of productivity faster?

Reach for the moon

Don’t get me wrong: thinking big, ambitious thoughts can be a desirable trait. Silicon Valley’s admiration for so-called “moonshot goals” has led to significant and worthwhile initiatives that are turning science fiction into reality. Some might argue that hype is necessary to attract investment; or that it's only by betting on one potential role for a new technology that we can discover its real use.

All this may be true.

But, at least in the context of government initiatives, we should recognise that the hype cycle also has some definite downsides.

First, it can waste time and taxpayers’ money as effort is poured into applications, tests and pilots that sound exciting, but are ill-thought through, potentially setting back more meaningful work by years.

Second, and perhaps more damagingly, over-promising and under-delivering on technology exacerbates the divide between technophiles and those who could most benefit from what technology can actually do. The more we pretend that technology is a cure-all, the more we promote cynicism that it can offer anything of value when it fails to live up to inflated expectations. Government and the public sector have been burned many times before by ambitious technology projects. Given the urgent need to reform public services to do more and better with less, we can’t afford for them to be put off genuinely good ideas any longer.

Seeking ways to reach the valuable applications of new technologies should therefore be a worthwhile endeavour. Asking five questions about the claims made of any new technology might help.

1. What are we actually trying to do? To a hammer, everything looks like a nail. To an IoT network, no doubt everything looks like a device waiting to be connected. Too many technologies smack of being solutions in search of a problem. The point is that we should never start with the technology. We must always begin by asking: what are we trying to do? How do we want to work? What interventions do we want to make possible? Only by establishing answers to those questions can a sensible conversation be had about whether any specific technology is useful in a given context. To do otherwise is to have the technological tail wagging the dog of public sector reform.

2. Are we over-engineering the solution? As William of Ockham famously once said, the simplest solution is usually the right one. As we consider potential applications for a new technology, we should ask ourselves if we are making a process simpler and more effective or just adding unnecessary complexity because it sounds cool.

1. Is it significantly better than what it replaces? In Silicon Valley, a common rule of thumb is that for a new technology to take hold or change consumers’ habits, it must be at least “10 x” better than what it replaces. Electric light was 10 times better than candles. The iPod was 10 times better than a CD Walkman in being able hold thousands of songs. Uber (according to its proponents) 10 times more convenient than waiting for a taxi, and so on. Anyone who has been involved in technology transformation in government will know that there's a huge amount of work involved in process change – it may not be worth it for incremental improvements.

1. Is there a connection with those who will pay for and those who will benefit from the technology? Beware ideas where those who would have to pay for a new technology do not also receive the benefits. Many smart city solutions seem vulnerable to this. Yes, a new urban sensor network may help monitor and improve traffic flow. Yes, that may help make citizens marginally more productive. But if that doesn’t directly feed back into a city authority’s budget, who exactly is going to pay once the government grants run out? This is not to argue that everything should be judged in terms of cold, hard cash. But even the most worthy of ideas may suffer unless they have some plausible financial future.

1. What skills and processes need to be in place for the technology to work (and are we willing to adopt them?). A new technology is unlikely to make much impact unless it is accompanied by (and preferably preceded by) operational excellence. Similarly, data analytics will deliver little value if we don’t know what questions to ask, or what questions can be asked. Yet time and again technology is treated as a crutch to support tired old ways of working. Indeed, sometimes technology becomes an excuse not to change ways of working – it’s far easier to procure a new tool than to restructure teams. In short, organisations need to have the right skills to use the technology and the processes to ensure it's genuinely plugged into the way the organisation works.

A little human intelligence

I’m a firm believer that making smarter use of technology will be a vital part of meeting the public sector’s urgent need to serve growing demand on tighter budgets. But the emphasis must be on the ‘smarter use’. The obligation is on all of us - technology’s users and procurers - to think critically about the real value it can offer any particular scenario.

So as the next wave of technology buzzwords come to dominate discussions of public sector reform, let’s do our best to skip the hype and get down to business.

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Image Credits:

Cover Image: CC0 Public Domain - Kaboompics / Pixabay

Gartner Research's Hype Cycle diagram: CC BY-SA 3.0 - Jeremykemp at English Wikipedia