top of page

Scaling innovation

Successful innovators make mistakes.  Even though they’ve learned and built routines and capabilities they can still get it wrong.  Sometimes spectacularly so.

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 also 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 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.  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.

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.  The underlying premise is not to ridicule these companies but rather to show that we can learn from failure.  They remain successful businesses because they absorbed the costly lessons and revise their innovation management models.

The examples of Sinclair and Toshiba highlight one particular challenge in innovation – the journey to scale.  We spend a lot of time worrying about the ‘front end’ of innovation – how to create new business models around products and services.  Powerful new digital tools and reorganization around open innovation principles ensures that there’s no shortage of incoming ideas.  Nor is there a lack of attention to the teams who create the new – entrepreneurs are helped through bootcamps, incubators and accelerators, in house teams have various shades of venturing options inside the walls of their parent organizations.  

But what happens when the project succeeds, and the new product or service is launched?  If a new idea is to have impact (commercially or socially) then it needs to move to scale.  People have to adopt it in large numbers,  the ideas need to spread, the concepts diffuse.  And it’s here, on the journey to scale, that we find a number of roadblocks, potholes and other obstacles to long-term innovation success.  

It’s not easy.  The Museum of Failure has over 100 ‘exhibits’ and thousands more haven’t made it through its doors and into the public eye.  This shouldn’t surprise us – after all we’re programmed to cover up failure rather than celebrate it.  But if we understand what goes wrong we might have a better chance the next time we set out on the journey.

Serial innovators know this, they reflect on lessons learned the hard way and apply them in honing their skills at scaling.  A good example is Joy Mangano, sometimes called the Mother of Invention because of her track record in bringing innovation to bear on seemingly ordinary household chores.  The huge success of products like the Miracle Mop aren’t accidents; they rely in her deep and hard-won understanding of how to move things to scale.

So what lessons can we draw to give us some signposts for the journey to scale

It takes time. Once launched 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  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. 

Timescales 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 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.

Dominant designs matter.  Innovation is all about possibilities and problems.  It involves finding ways to match needs with available means in novel fashion – and they don’t always come together at the same moment.  Back to bikes; the need for personal transportation was there for Drais, not least because of two bleak years of bad harvests and the ravages of the Napoleonic wars reducing the availability of horses.  But the technology to create a working bicycle wasn’t around.  

The next sixty years were a classic illustration of the ‘fluid phase’ in innovation where many entrepreneurs chase after the same thing, each experimenting with their solution to the problem, each adding ingredients to the soup.  Eventually it come to the boil and a ‘dominant design’ emerges – the configuration which best fits the needs/means  challenge for the most people.  

Importantly it’s not necessarily the best; history is full of innovations which were technically superior or delivered more elegant solutions but were elbowed aside by the emerging dominant design.  In the case of the bicycle Pierre Lallement may have the distinction of his name on the patent for a pedal powered machine but it was William Starley who put the dominant design together – the  diamond frame, pedal driven, chain transmission vehicle which we still use today

Henry Ford wasn’t the first car maker, his business arrived nearly twenty years after Daimler and Benz had started selling horseless carriages.  And the i-Pod was number 51 in the race, arriving three years after Sachan Information Systems of Korea had launched their MpMan.  Yet it was the Model T and the i-Pod which became the dominant design and shaped their respective industries. 

The lesson here is one of watching, adopting and adapting, learning with the market as it evolves and amplifying the key features which it values – not necessarily the ones you think are the best.

It’s about system thinking, not just coming up with a clever component.   Bringing in the other elements which make innovation work – the value creating network of key suppliers and resources, the understanding of the market and what it actually values and not least the financing, not just the venture money but the cash flow to make it work and stay alive.  

Something which another innovator wasn’t too good at.  Mr J. Murray Spangler gave the world the electric vacuum suction sweeper but had to sell his patent to William Hoover because he lacked a business model to take it to scale.  Again this is a common pattern – the originator and often patentor of innovations which have come to be famous is not the one to bring the innovation to scale. 

Think about the typewriter – for much of the past 200 years a key innovation in the world of communications.  Its origins lie particularly in the work of  Christopher Scholes a printer who developed and patented the idea in 1868.  But neither he nor his colleagues could manage to organize the wider business of making and selling it.  Eventually one of them, James Densmore enlisted the help of a businessman friend, George Yost.  They arranged a deal with the Remington company who bought the patent for $12,000.   Remongton was a well-known manufacturer and distributor of sewing machines and understood mass production; it has diversified very successfully during the Civil War into armaments and so had the business set-up, resources and networks to commercialise the idea at scale.  Its 1873 machine with upper and lower case became the Model T of its time.

The lesson here is simple – build a business model.  And make sure the story you are trying to tell has the system to deliver on its promise.

Complementary assets matter. A key question which needs to be asked early is what (or who) do you need to help you bring out innovation to scale?  It’s systems thinking once again – the need to make sure all the bits are in place.  A good example would be the innovator who saw the potential in remote retailing, providing a service for those people who couldn’t or wouldn’t visit shops.  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.  Selling is one thing, 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.  

You might think that was part of  Jeff Bezos’ thinking 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.  But theirs wasn’t a single component innovation, they built an ecosystem.  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 and other players came into the ecosystem tent – all sharing in the value creation.

It’s 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.  Henry Ford’s achievements were again at the system level; by the height of its reach the Ford system could create a car from mining the iron ore to driving one off the assembly line in 81 hours.  More important he either owned or controlled those key complementary assets.

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 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. 

So the lesson for scaling is to ensure that you have thought of the ecosystem that you will need and have in place mechanisms to help build it – partnerships, licences, strategic collaborations, et.  Without it even the best ideas may fall – a fate which befell Better Place, a start-up so promising it was able to raise over $200m in scale-up funding.  Yet barely four years later it had burned through it all and failed.

Understand adoption behaviour.   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 that was the life’s work of Everett Rogers and it offers us some powerful clues about adoption.  

He saw it in terms of a communication process and a  key point here is that 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.  Rogers lists five innovation characteristics and these provide a helpful checklist:

  1. Relative advantage – can we prove a difference in performance on some dimension?

  2. Observability – can we show the benefits – seeing is believing?

  3. Complexity – can we present our idea in simple form?

  4. Trialability – can we offer the chance of a ‘test drive’ before requiring a full commitment?

  5. Compatibility – how well does the new thing fit into the (potential) user’s world? 

This checklist also helps us understand why things often go wrong in diffusion.  Consider the question of complexity – Google TV was one their less successful ventures and it failed in part because it was perceived as too complex.  Something exemplified in the remote controller which Sony produced to fit the system which had no less than 88 buttons for different functions!

Compatibility is probably the biggest rock on which adoption funders – basically because the innovator doesn’t fully grasp the context in which their innovation will work (or not).  Sinclair’s C5 was technically very interesting but he almost completely misread the market in terms of its willingness (or otherwise) to pilot a tiny tricycle along busy roads in the worst of British weather!

Rogers’ work didn’t just focus on perceptions of the innovation – it also extended to the innovator.  People trust things which they perceive as coming from someone like them (homophily) and they are suspicious of things which come from outside their world.  And they are not all the same – people differ widely in their willingness to take on new ideas.  So finding those likely to be early adopters and working with them can help cross the chasm associated with diffusion. 

Something which working with users can really help with – by definition if users are involved in creating the innovation it’s likely to fit their world (compatibility) and they have a stake in its success.  And if the innovation originates from user’s own experiences and frustrations then it’s likely to match those of people like them and diffuse rapidly,  Betty Graham was a typist who made mistakes; her idea for ‘Liquid paper’ correction fluid spread fast amongst the thousands of other typists similarly annoyed at the problems of having to retype corrections.  And Mandy Haberman’s experience as a mother fighting a mountain of washing led her to invent (and millions of mothers to adopt) a non-splash drinking cup for babies.

Check your assumptions.  Since diffusion takes time it’s unlikely that all the things you thought of at the outset will stay the same.  Life, as John Lennon famously put it, is what happens while you’re busy making plans.  Tracking and testing the things you base your scaling model on – and pivoting to adapt to changes – is a key skill.  Otherwise you risk the fate of the Bristol Aircraft Company with their giant Brabazon airliner.  Conceived as the future of air travel for the post-war years it made a lot of assumptions which didn’t actually play out, and never flew commercially.  By contrast Boeing made different assumptions about the same market, leading to the development of their hugely successful 707 jetliner. 

Share this:

227 views0 comments

Recent Posts

See All


bottom of page