How to navigate the long and winding road to high-impact innovation
Innovation fails — sometimes spectacularly so. It’s hard enough when that failure comes early on during the start-up phase — that brilliant idea which somehow isn’t quite as brilliant when it collides with the first few encounters with the market. And when no amount of pivoting is going to save it. It’s hard but it’s a matter of squeezing it for useful lessons for the future and then throwing it in the bin. Chalk it up to experience and try again.
But what happens when you’ve gone much further down the road? When you’ve put in the hard yards, prototyping, pivoting and finally launching? And when your early efforts seem to have yielded success? When it does seem as if people value whatever it is that you’ve created from your idea?
You could just relax, take the (small) bouquets which come from succeeding at something, those plaudits from family and friends. But most likely you’ll recognise that, nice staging post though it is, you’re really only halfway along the journey. Because for your idea to have real impact you are going to need to scale it. And that’s where a whole new set of challenges come into the frame.
Scaling isn’t easy …..
Scaling isn’t an easy ride, even for experienced innovators. Take the case of Toshiba — certainly not a new kid on the block but a respected innovator over nearly 150 years. Not just a one hit wonder either — its success pedigree includes lightbulbs, memory chips, video recorders, TV sets and DVD equipment. They certainly understand the challenges of bringing innovations to scale — for example, they’re credited with bringing the notebook computer to a mass market with their 1100 series. Yet they lost out big time with their attempt to put HD DVD into play, losing the standards battle to Sony and its Blu-Ray system (and around $1bn in the process).
Or look at Clive Sinclair, one of the creators of the personal computer revolution whose ZX family of machines spawned a generation of programmers and helped move the technology to the mainstream in the 1980s. Despite his success with computers (millions of units sold world-wide) he managed to fail very publicly with his later venture, the C5 electric vehicle.
And on the subject of electromobility it’s worth looking at the case of Better Place. Launched in 2007 its charismatic founder Shai Agassi managed to persuade the Chairman of Renault-Nissan and ex-Israeli Prime Minister Simon Peres to back his venture, as well as attracting over $200m in start-up funds — the largest ever for its time. Take a look at his impassioned TED talk from 2009 and it’s hard not to be convinced by a man with the mission to make the world a better place through electromobility.
Yet within 9 years the company had burned through its cash and spectacularly failed — one more casualty on the road to scaling innovation.
They aren’t alone — in fact there’s a wonderful Museum of Failure located in Sweden which showcases failures from some of the biggest business names in the world. It has over 100 exhibits and you can bet that there are many more in the world outside which haven’t yet made it on to their displays. The underlying premise of the museum is not to ridicule these companies but rather to show that we can learn from failure. The companies behind the MoF exhibits remain successful because they absorbed the costly lessons and revised their innovation management models.
Scaling isn’t just a commercial challenge — if anything it matters even more to social innovators. When you want to change the world it’s important to reach scale. If you’re trying to reduce infant mortality with a new vaccine you want it to reach every sick child in the world. If you’re trying to eradicate malnutrition with a better farming method to increase yield you want to do this everywhere. This quest for scale is what drives pioneering social innovators like Govindappa Venkataswamy whose Aravind Eye Care system has meant that over 12 million people in the world can see who would otherwise have gone blind. Or Devi Shetty, striving to bring healthcare within reach of India’s poor through innovation. Or Washington Carver who spent his life trying to diffuse better farming methods to the rural poor in the USA.
But this is a sector plagued by what could be called ‘pilot-itis’; plenty of great ideas which get as far as pilot launch but then fail to scale. ‘Too tough to scale’ is the title of a helpful research report which explores the roadblocks on the journey and reminds us that changing the world requires a lot more than (just) a great solution.
And it’s the same story in the public sector. There’s no shortage of wonderful experiments which improve quality, efficiency, service levels — but too often they remain local islands of change. What’s needed, once again is the ability to take these to scale.
So scaling is hard. But it matters.
Scale -up, scale out and scale deep
It’s worth pausing for a moment to think about how we might scale our innovation. We have at least three choices:
· Scale up — make your solution bigger, reach more of the market
· Scale out — spreading your idea to reach different people, extend the geography you cover or the sectors you address
· Scale deep — building a platform around your core innovation
Importantly these are not mutually exclusive; Netflix began by building its subscriber base in the USA, then extended geographically and these days is a platform player, creating content to deliver across its streaming network as well as running the network. Lego has built a platform of storytelling books and movies after first building its bricks business, then internationalising it.
Scaling the scaling mountain
Whatever the scaling target we need to recognise that the journey to scale isn’t going to be an easy one. The good news is that we’re not the first to make it. There’s plenty of experience on which to draw and from which we can tease out useful lessons. And three things stand out if we are preparing to embark on such a journey:
· It takes time, so we need a strategy for scaling
· It takes complementary assets and systems thinking
· Adoption by the market follows an S curve so understanding what affects this will help us accelerate towards scale
Let’s look at each of these in a little more detail.
New ideas often take a long time to have impact. Think about the bicycle. It was invented around 1817 by Baron von Drais who certainly had a clear vision for what he was trying to achieve — affordable personal transportation for everyone. But it took another sixty years to make that dream a reality. Or the experience of Frederic Tudor, the ‘ice king’ of Boston who pioneered the global ice industry in the 19th century. His first (unsuccessful) voyage in 1806 took a shipload of ice to Cuba where its frosty reception had nothing to do with the product in his ship’s hold. It took another 10 years, all his family’s money and a spell in debtor’s prison before he finally succeeded in creating an industry which in its heyday was cutting and shipping close to a million tonnes of ice every year.
Innovation timescales can remain stubbornly long, even as technology life cycles shorten. For example in the field of humanitarian aid the idea of giving people money instead of food can be traced back to experiments in the early 1980s. But it took another twenty years before this moved to the mainstream — and even then it took the impact of the dreadful 2004 Tsunami to kick start the diffusion to scale.
So if it’s going to take a while to move to scale then you’ll need to do more than just pat your innovation on the head and send it on its way. You need a strategy, a long-term plan for how it will happen.
A key question which needs to be asked early is what (or who) else do you need to help you bring your innovation to scale? Because going it alone is not an option — there are simply too many different bases to cover. You need what are technically called ‘complementary assets’.
Think about the challenge in remote retailing. You might see the potential in, providing a service for those people who can’t or won’t visit shops; your solution is to bring the shop to them. It’s a good idea — but to make it work you need to assemble a lot of pieces of the jigsaw puzzle and make them work. Advertising your remote storefront, capturing and processing orders, arranging for stock to be available and storage and distribution, handling logistics over a large area — and very important, managing the cash flow so that you don’t sit on lots of stock but manage to get paid up front.
Working that out was almost certainly part of Jeff Bezos’s thought process in setting up his Amazon empire but in fact it’s a model which predates him by almost a century. Messrs Sears and Roebuck pioneered the idea of remote retailing via their mail order catalogue. Theirs wasn’t a single component innovation, they built a system. And they were smart enough to recognise that they didn’t need to own or control everything as long as they could orchestrate it and co-ordinate it. So major manufacturers, financiers and other players came into the ecosystem tent — all sharing in the value creation.
Scaling innovation needs this kind of systems thinking, identifying and then configuring the value network we need — the additional players who will make up our system — and developing the working relationships with them so that the whole system can create value. Something which George Templer understood when he had the brilliant idea of selling the granite rocks on Dartmoor to the builders erecting the New (for its time) London Bridge in 1824. The stone was perfect for the task and the builders were prepared to pay top dollar for it; the only challenge(s) to this great entrepreneurial idea was getting the rocks out of the ground, down a long steep hillside and then on the 200-mile journey to London!
He solved the problem in ingenious fashion, laying a stone tramway down the hillsides to a canal which he dug at sea level to connect to a local river. This allowed him to reach the port of Teignmouth from where the stones could be shipped round to London and the bridge built. It still survives to this day (albeit now in the Arizona desert where it was transhipped stone by original stone). His successful scaling of an idea owed everything to his ability to build a system and engage many different complementary stakeholders in its co-creation and operation.
Such systems thinking is what makes the difference between a good idea and one which has significant impact. Thomas Edison’s name may be forever associated with the light bulb but he spent a significant proportion of this time working out the rest of the system into which you could plug it, creating the General Electric Company along the way with its interests in generation, distribution and devices to consume electric power.
The same approach — building an ‘ecosystem’ was what really lay behind Apple’s success with the iPod. While the device was well designed and elegant it was the i-Tunes network behind the scenes, the negotiation of digital rights and royalty arrangements with the major music providers which paved the way for a portable music revolution. And also laid the infrastructure across which the wider smart phone ecosystem built on the i-phone now operates.
And it was here that Toshiba mis-stepped in its journey to scale with the HD DVD. It understood about ecosystems and tried to build one, but its choice of partners (including Microsoft) and its inability to get major film studios involved led to it losing out to Sony.
Understanding the S curve
Another piece of the scaling puzzle is, of course, the ‘market’ — the demand side for our innovation. Unless users make the decision to adopt and do so in large numbers we won’t succeed. So understanding them and getting them on board will be critical to scaling.
People don’t simply accept changes; instead there’s a pattern in which some are enthusiastic early adopters whilst others may take a long while to make up their minds. Whether we are talking about toothpaste or high technology machinery the same pattern will appear and it takes the form of an ‘S-curve’
Understanding what shapes this was the life’s work of Everett Rogers and his model offers us some powerful clues about adoption. He saw it in terms of a communication process involving an innovator ‘broadcasting’ a message (the innovation) to a receiver (the adopter) and doing so in different conditions (the environment). He picked apart key dimensions of each of these which might influence adoption and his insights give us plenty to work with.
For example people aren’t all the same, some are much more willing to try new things out and so working with such ‘early adopters’ can help as we develop and refine our solution. But adoption is also a social process — we tend to follow what others do and are heavily influenced by key people — opinion leaders — and by people we perceive as being like us (and whose judgments we trust).
That was critical to the success of an otherwise great product which failed to diffuse despite its significant performance advantages. When Earl Tupper launched his brightly coloured plastic storage containers in 1947 he expected people to jump at the product idea, especially with its clever patented seal. But sales stayed stubbornly low until he engaged the services of Brownie Wise, a single mother with a gift for sales. She pioneered the idea of ‘social marketing’ running demonstrations in people’s homes which became enjoyable social events and a safe place to explore new ideas. Tupperware parties still remain the dominant model for selling his product very successfully nearly 100 years later.
And different people perceive the characteristics of an innovation (the ‘message’) in different ways. Whether or not our innovation is the best new thing since the invention of sliced bread is not the issue — it is how others perceive it which matters . Which was a hard-won lesson for the inventor of sliced bread, Otto Rohwedder. He nearly went bankrupt trying to persuade local bakers to adopt his bread slicing machine — perhaps not surprisingly they didn’t see much advantage in it. In fact it added complexity, took time to set up and run and generally got in their way. He eventually persuaded (by giving away half the equity in his company) a baker to try it — and the real market of users loved the product. They saw such benefit in the increased convenience in their busy lives that sales increased by 2000% in the first two weeks and kept on doing so. The concept took off like wildfire; within five years 80% of US bread was sold ready sliced.
So if we want to scale our innovation it’s probably worth reverse engineering some of the factors in this model and using that as a checklist for accelerating adoption.
Keep on pivoting
Once we move beyond the pilot stage we lose control of our innovation. We might still be able to influence it and there are some things we can certainly take in hand. But, as we’ve seen, scaling involves a complex ecosystem and its emergence is going to be a matter of co-evolution. We can’t control everything — but we can work hard to pick up early warning of the ways in which things are moving and then adapt our approach. Those pivoting skills we learned right at the start-up and the agile approach which underpinned developing our idea are going to be even more useful as we move to scale.