The Missing Pieces of Innovation

I realised something very important while I was a the innovation event organised by EditorEye at the General Assembly recently. It became clearer to me why, despite spending a lot of time and effort on innovation and hiring some excellent people, organisations are still struggling to get the results out of innovation. The speakers at the event, by the way, were all very good and were all covered the topic extensively. But there are some aspects of innovation which are simply not talked about, while others get a lot of focus, as I’ll show you later in this piece.


But the problem, I believe starts at the root. What is innovation? You can get as many definitions as there are people in the room. Is it new product development? Is it new ideas? Is it creativity? Is it bringing ideas to market? My definition is simple – it’s doing more with less. If it takes 100 units of resources to solve a problem, and you figure out a way of doing it with 80, that’s innovation. We can debate this later, but let me ask you a different question. Is all product development innovation?

Let’s suppose you are an insurance company and you figure out that increasingly there are older people whose lives depend extensively on technology. You survey the market, and you create a new product which looks at a comprehensive technology devices cover for this audience. You create an app and website for it, which is designed to be used by older people – simpler interfaces, larger fonts, etc. You spend time with prospective customers to understand their specific behaviour and problems and design your product to deliver their key unarticulated needs. Your product is a success. Was this an example of innovation? Let’s assume this product was prototyped in your ‘innovation lab’ which has been set up for bringing such new products to market. Still, is it innovation? Which part of this is innovative, given that all these processes are now standard practice for product development? It may be an excellent example of product development, but I repeat, is it really innovation?

Similarly, you might argue, is every successful advertising campaign ‘innovative’? Is every market research that delivers customer insight an act of innovation? What about a new business, or start up? The reality is that you’re perfectly justified in saying yes to all of these questions. And if your innovation lab delivers successful products, then surely it’s justified, irrespective of what you call it. And I’m not disagreeing with that.

However, to miss the point of innovation is also to walk away from a lot of value. Let’s suppose the typical new insurance product costs £2m to develop and test and £10m to market, hypothetically speaking. Let’s say that the numbers here represent the comprehensive resource cost, and not just actual cash outflows. Now if your new product took about the same, and was averagely successful, you’re at par. But what if you could deliver similar success with 20% investment? Or much better returns? And what if you could build a methodology for doing this consistently? That’s innovation! That means you can deliver more for less and on a consistent basis.

Most organisations look at innovation as a way of delivering new products, or new businesses. It’s also common to look at it as a process that follows a standard path: brainstorm ideas, prototype in a lab and then scale through the organisation. I challenge both of these premises. First, looking at innovation as an idea to market process limits our thinking. Innovation needs to be seen as a problem solving methodology. And specifically, a methodology that looks to improve on the expected resource requirement for solving the problem. And to the second, if everybody is replicating this model, then it stops being innovative. Not that it becomes less valuable if the new products work. But the reality is that most innovation initiatives in most companies don’t lead to success. And wouldn’t it be great if we could increase the success rate?

My model of innovation therefore starts earlier, with Problem Definition. If you’re thinking of a new product, why? Is it to ensure coverage of the market? is it opportunistic? Do you believe that there will decline in current products & revenues? Is it a strategic response to competition? Do you feel you underserve the market? Is the problem financial – your return on capital is too low and you’d like to improve this? Are you missing out on more profitable customers or a growing segment? As you can see there are many, many ways of framing your new product development effort and the problem you’re trying to solve may vary significantly. 3M for example, has a commitment to drive 30% of revenues from ‘new products’ – i.e. those built in the last 4 years. For a pharmaceutical company a new product that better addresses a disease or a family of problems, is a protectable revenue stream that can run for over a decade, even as older revenues decline through patent expiration. Whereas Google (Alphabet) just wants to solve bigger problems. That allows it to be mission driven but even there, for example there are specific problems. Arthur Levinson, ex CEO of Genentech leads a platform in Alphabet to combat ageing. Whereas in the new famous example of British Cycling, the marginal innovations are aimed at driving higher performance, and nothing to do with a product at all. This is where we step away from product development and recognise that innovation is a methodology for solving any problem in a ‘do more for less’ way, not just product development. To do this well, try approaching this problem as at least two out of a CFO, a CEO and a head of Operations, or Marketing. Or apply design thinking principles to see how the people impacted by this problem think about it. This award winning redesign of the ambulance started by looking at the ambulance as an extension of the hospital, and the start of the medical process, rather than just a form of transportation to the hospital. Kees Dorst’s book ‘Frame Innovation’ is a good starting point for thinking about problem framing.

The next step is the Research and Baselining phase, so we know what benchmark we’re trying to beat. It is likely that your ambitions are not at the same scale as Google’s (or Alphabet’s), Amazon or Elon Musk’s. In fact you may just be looking to solve an punctuality problem in your department in a way that nobody in your company has done yet. If you define your context as your company, department, industry or the world, you can accordingly set your benchmarks. This is critical because what’s innovative for a government agency (say agile development) could be very old hat for a Silicon Valley company. But this my second key point. Innovation is surely about being different, and not replicating a tried and tested method. So you need to clearly set out what you’re going to do differently (better!) from other similar efforts, before you start. It’s worth noting that of the 5 stages, this gets the least amount of attention because it’s probably the least sexy part of innovation. But it could save you a lot of effort and also dramatically sharpen the subsequent phases. In fact, often, you will be able to find a lot of examples workable ideas in other industries and organisations. No better example of this than the Great Ormond Street Hospital for children learning from Formula 1 pit stops, about swift handovers from surgery to intensive care. This represents a huge reduction of risk, in the innovation journey.

It’s only once you’ve done stages 1 and 2 that you should then get to the Creative Spark stage. For most organisations, this equates to a brainstorming exercise. One of the biggest mistakes in the area of innovation is that people jump into brainstorming with a loosely defined problem and no benchmark. To make it worse, you then get a lot of people with very little knowledge of the context of the problem state coming up with ideas many of which clearly won’t work. I know of a company which was keen to ‘pitch’ ideas to Transport for London. They ran a competition internally, generated hundreds of ideas, evaluated them and drew up a short list of 10. But the brainstorm was run with a global team, not based in London, and consequently many of the ideas, such as mobile app based solutions for contactless ticketing did not factor in the actual challenges of rush hour volumes, or the speed of response required. Besides, many of the ideas were already at play at TFL, which hadn’t been researched well enough. Running pure-play brainstorms is also of limited use if the team doesn’t have enough context of the problem. You can’t brainstorm ways of improving care pathways in the NHS, or supply chains for broadcast equipment, if you don’t know much about them, or the problems they face. There are, however, plenty of techniques for running more effective brainstorms and idea sessions. Additionally, there are other ways apart from brainstorming for the creative spark phase. Best results are often achieved through having creative people in the mix along with experts, or building unpredictability into the process. Tim Harford’s book ‘Messy’ suggests some excellent ways in which this happens.

Once you have ideas you want to take forward, you can then push them through the Innovation Lab stage. Of the 5 phases of this methodology, this is the one most organisations have invested in already and are doing with a lot of focus. Setting up a lab environment, running ‘Google sprints’, ensuring that small teams turn around quick prototypes, building design thinking into the mix and fusing the efforts of creative technologists with deep experts, a lot of companies are able to do a reasonably good job of taking new ideas through a laboratory process to an MVP stage. When I was working at Cognizant, in 2015 we conducted a quick research of ‘innovation labs’ and were not surprised to find that an overwhelming majority of leading banks and retailers already had an innovation lab of some kind. If you haven’t yet been exposed to or been a part of an exercise like this, grab hold of ‘Sprint’ by Jake Knap et al.

But even that is not enough because a lot of initiatives can fail even after lab success. Be they new products or internally facing solutions. Scaling innovation is fraught with risk, and even Google is famous for the number of initiative it has killed after promising starts. This is the key reason that many organisations prefer to buy in the finished product rather than try to build it in house. What the newly created and lab-tested idea needs is not just organisational support, but often a network in which to flourish. The best results are created when the new idea has a life of it’s own and is allowed to grow and morph independently, not simply scale to a larger replica of it’s initial form. The perfect baby needs to grow into a healthy human adult, not a full sized replica of the baby. Most businesses are unable to provide this kind of sustaining network. Steven Johnson’s excellent book ‘Where Good Ideas Come From’ beautifully elucidates this idea of a sustaining networks. When GE set up it’s fledgling IOT business in Silicon Valley, it was not just allowing it to flourish outside of the corporate headquarters, but also allowing it to sustain and nourish itself in a high tech network. In organisations such as Google and 3M, there isn’t a small and tightly defined number of ideas being pipelined to the market, there is a huge internal innovation network, where dozens or even hundreds of ideas feed off each other, combine and morph on their way to a handful becoming successful products. If it’s new product and new business development that defines innovation for you, then you could do well to keep at hand the Innovators Solution, by Clayton Christiansen.


This is just the tip of the iceberg, in a way. Innovation is hard work, and much of it is done away from the public eye, and the adulation of success. But more importantly, innovation is a methodology, which when applied, dramatically improves your ability to problem solve in a way that is ahead of the competition.


3 Easy Ways to Boost Your Mobile Strategy



It’s 2016 and almost a decade since Steve Jobs put a ding in the universe with the launch of the first iPhone. A significant part of my life in that time has been spent in delivering better business outcomes using mobile technologies. And as the iPhone 7 blinks it’s baby eyes at the world, here are some of the things I’ve learnt about mobile strategies. (If you’re wondering whether business should have a mobile strategy or just a business strategy, let me just suggest that you need to have a clear roadmap and strategy for how you’re going to exploit the mobile ecosystem. What you call it is up to you!). Assuming you are a progressive organisation, I would expect to see the following three things happening in your business:

It’s NOT a marketing problem: There has been a historical tendency to look towards the CMO when we think about mobile solutions. But people who make the investment of effort, time and attention, to download the your app are usually your existing customers, looking to make it easier to deal with you. These are the also committed customers who are self-selecting and need to be recognized and rewarded. This goes to the heart of your customer retention, cross & upsell and will directly impact your cost of servicing customers. When I was working for a major European airport we knew that the airport didn’t have a direct relationship with travellers, nor much data about the millions of people using the airport, yet there was a prevailing school of thought that the mobile website was good enough, and there was no business case for upgrading the mobile app. For any frequent user of a service, logging into a website every time is a nightmare. This is an operational and cost of servicing issue. Customer experience, after all, is a COO problem really. This is even more true as employee apps take centre stage. So if your COO and head of Channels aren’t involved and sponsoring your mobile strategy it might be time to rethink.

The New New Stack: A Whole New Architecture: In the last few years there have been a very quick turnover of the preferred ways for building mobile apps. You only have to look at the rate of change of Gartner terminology – from MCAP to MEAP to MADP as the flavour of the month. Cut to today and none of those are preferred options anymore. The axis has shifted again. Most apps are being built today on light-weight front-end tools involving some flavour of Angular with loose coupling to the back end via APIs. A word on API management is worthwhile here. As a manager, you don’t need to know about SOAP or REST but think about this as a much more modular setup, where the API layer simply pushes information out in a governed manner to whichever channel requires it – be it the mobile app, the website or a partner.

To get a sense of how valuable the API layer has become consider that Apigee have recently been bought by Google. Mashery, another API management platform was first bought by Intel and then acquired from Intel by Tibco. Other majors including IBM and CA have their own solutions in the space. APIs themselves are not new but the way they are written now and the platform through which they are managed and governed are relatively new and you’re missing a trick if your business lacks an API strategy.

There are also a number of low-code or no-code platforms. Fliplet, for example, allows you to build simple, and functional mobile apps with little or no coding. Of course, this doesn’t include scenarios where you need to connect to other systems or consume APIs. But even those can be added with relatively low effort. In the Business to Employee world which is defined by a number of micro-applications, this is a very good option.

Exploit New Behaviours: New Technologies often engender new behaviours. Probably one of the most salient in recent times is the swipe left/ swipe right behaviour that was made popular by dating apps like Tinder. Understanding these behaviour patterns and using them is key to reducing friction for your processes. Another new ‘behaviour’ is the mobile only customer behaviour – i.e. somebody who would rather transact only on the mobile device. Uber is a very good example of how massive this can be, but you will definitely see customers in future at both ends of the age spectrum, whose only device is a mobile device rather than a laptop.

What new behaviours will we become used to over the next 5 years? Will it be the invisible payment mode of Uber? The voice interface of Amazon Echo/ Alexa? Or will we find more ways of self-quantification for our personal and professional lives? The good news is that you don’t have to create new behaviours. You just need to keep abreast of them and ensure you’re able to exploit them.

The Unbearable Bigness Of Data

(And What We Should Be Doing About It)


Welcome to the Data Deluge.  

By now you’ve probably gotten sick of hearing about big data, little data, fat data, thin data and all manner of data. You’ve gotten your head around Terabytes, Exabytes and Zetabytes. You’ve noted that the price of data has crashed by 90% over the past few years on a per unit basis. Your CIO has mastered Hadoop and MongoDB and you understand the benefits of data lakes over, say, data puddles. The scary part of all of this is that we’re still in the early days of the data deluge. We are hurtling into a quantified universe fed by smart cities, homes and cars; platform driven models and clickstream driven relationships. In fact, I was having coffee this morning with the well travelled, well informed, and always insightful John McCarthy from Forrester, and we were positing that in a few years from now, data will take over from ‘Digital’ as the centrepiece of the organisational transformation and focus across the world.

Right now, though, we’re caught in a deluge with no real clarity about how we’re going to actually use all the data that’s floating around. And here are three key challenges we’re going to have to deal with:

What, not Why – A New Mindset

A question I often ask my colleagues who are experts in data sciences is as follows: let’s suppose that when it rains, people drink more cappuccinos. Now, if Starbucks knew this, it could advertise or promote cappuccinos every time it rained. It could even launch branded umbrellas. But how would it discover this? Historically, the story would be one of a smart store manager who one day realises that rainy days increases his cappuccino sales, and having defined the premise, starts to collect the data to validate his hypothesis. Or even more traditionally, Costa Coffee runs focused groups, and the link between weather and coffee preferences is established. Critically, a qualitative hypothesis would be at the front of the process and data collection would follow. Because, how else would we know if it’s the rainfall or the pollen count or indeed, the volume of traffic on the roads that we should be correlating coffee sales with?

In the new world of data, or ‘big data’, this works the other way around. A brand like Caffe Nero could take all their sales data across the world, and run hundreds or thousands of analyses, searching for correlation, with any number of external and easily accessible data sources. This includes the obvious ones such as weather, or transport, but also for example days of week or month, time of day, and train and bus schedules, sales in other retail stores, etc. This list is only limited by your creativity and the data availability.

But most fundamentally, this is a shift from why, to what. As well highlighted by Cukier and Schonberger in their book on Big Data, in this new world, we find the correlation first and then the hypothesis. And we actually don’t care why. Let’s suppose we discovered that the coffee consumption actually varied with the tides. We would need to verify whether this was simply a spurious correlation, but from there on, we could go straight to predictability and dispense with the causality, or the ‘why’ question. This is a mind shift for those of us who are used to a ‘scientific’ mentality which requires us to establish causality in order for any approach to rise beyond heuristics into a scaled and logical argument.

The Crown Jewels?

If you haven’t read Adrian Slywotzky’s great book on Value Migration, this would be a great time to start. The book talks through how value migrates from older to newer business models or from a segment to another, or even one firm to another.

We are going to see significant value moving to those companies in each industry that get the value of the data. Be it healthcare, or education, or automobiles, or even heavy industry. Either an incumbent, such as GE, with it’s smart engines and its Predix platform, or challengers such as Amazon, in retail, or upstarts such as 23andme.

The question you want to be asking yourself is, in your industry and in your firm, what are some of the areas of opportunity where you can create new platforms to data-enable processes, or value to customers. How can you converge the primary and ancillary meaning in your data onto areas of your competitive strategy? And also, you may want to perform an audit of what data you might be giving away, perhaps because you feel that it’s not core to your business or you have a player in the industry who has historically be collecting this data. For example, Experian and credit scores. Ask yourself are you merely giving away data that you don’t use, or are you handing over the source of competitive differentiation in your industry? Remember the story about IBM, Microsoft and Intel? I argued this point in my post about Uber and taxi companies, too.

To underscore the earlier point, I believe that value will increasingly migrate, in each industry, to those who best manage, and build strategic & competitive alignment with their data strategies and/ or new offerings based on the data and its meaning.

Adding Love To Data

A couple of years ago, at the annual FT Innovate conference, a lively round table discussion followed after a well known retail CEO had made a presentation about data and analysis. The presentation covered examples of analysing customers to great and occasionally worrying insight, within the industry. From knowing if a woman is pregnant even before she knows it herself, to people having affairs, or stacking beer and nappies together, in front of the stores, all of this can today be deduced from data itself. The debates afterward spilled over onto lunch led to the insight that while there’s been a lot of talk about analysing customers, it misses the point of empathy.

Let’s remind ourselves though – the customer does not want to be analysed. As with any relationship, he or she wants to be loved, cherished, understood and served better.At the end of the day, for most businesses, this translates to a mind-shift again, of adding a layer of human understanding to data, to creatively and emotionally assess the customers’ needs and to allow the analytics to feed off the empathy and emotional connect, rather than be driven purely by the algorithm.

In Sum:

You will hear a whole lot more about data in the coming weeks and months. However, for starters, you could keep these 3 guidelines in mind:

  • Look for correlations, not causality. You want to throw tons of data together and find patterns that aren’t born in some logical causal hypothesis but is simply an observed correlation done at the data level.
  • Be aware that the future of your industry, just like any industry, will involve the value of data. So try to identify and own areas of data which help you drive competitive advantage and/or new products and services, and start building proofs of concept.
  • Add love to data. Don’t just analyse your customers. Bring observation and empathy to the table as well, and marry the analytics with the empathy for best results.
What are your lessons from working with big, small and tiny data so far?

Why Is Good Design So Difficult?

Golf has been described as a game where you try to put a very small ball into a even smaller and remotely distant hole, with instruments singularly ill adapted for the purpose. 
While a degree of difficulty is desirable in sport, it’s safe to say, we don’t want to gamify everything we do to by adding levels of challenges. On the contrary, we spend much of our lives individually and collectively working towards the opposite objective. How to make it easier. Easier to shop, to commute, to acquire and consume. Easier to access, easier to use. Making things easier has always been the holy grail of progress, the end game of science and technology and of design.

So why is good design so infernally difficult? Why do we feel at so many points in our lives, and during our everyday routines, that a product or a service has been really badly designed? Just this morning we discovered that the water filter in our fridge needed replacing. This can only be done by moving the cupboard sized fridge away from the wall, and unscrewing a plate behind, and then following nearly non-existent instructions in the manual, which are definitely not for the model we own. We decided to call in the professionals. Samsung recommends that the filter be changed every 6 months. Would you pay £80 every 6 months to a plumber to keep your fridge running. No, me neither. Which is why we’re going to video record the plumber and ensure we can do it ourselves next time round. Computer hardware manufacturers solved a similar design problem a long time ago, by putting the USB ports and network points in front of the device, rather than behind, and colour coding the ports.

But surely you must see instances in your daily lives that make you want to pull your hair out, simply because of the thoughtlessness of a service or a product? Some are unintended such as the walkie talkie building and the hitler tea pot. But others are just examples of callousness in design, while still others are simply relics from an older world that need a makeover.

In fact this lethargy is probably at the heart of any number of products and services which were fine a few years ago, but you simply would not design them the same way today. Consider home security. Some of the leading brands offer you the choice of “key-holder” response and “police response” at different price points. But why not a combination? Why can’t I opt for police response when I’m on holiday? Why does the alarm signal go to the provider first and then as a phone call to me? Why can’t it trigger a message to an app on my phone, with an option to turn on one or more video streams from inside the house? If you had to design a home security system from scratch today how would you design it? Chances are you’ve walked down a road where an alarm has gone off, in a home or a shop, and you’ve just walked past it, because everybody around is just ignoring the noise and getting on with their lives.

A friend of mine had an instance of an alarm going off while he was on holiday and as I was the nominated person the alarm company called me and I went round to his house at 6 AM on Sunday morning. As it turned out, there wasn’t much going on but a friendly neighbour popped by and  we looked around the house together. The neighbour found a way to get into the house because he discovered that a back window was open upon entering the house the alarm went off again. At which point the alarm company called on the land-line inside the house. The neighbour picked up the phone and he told the alarm company that he was the neighbour and he was with the key-,holder and that everything was alright and incredibly, the alarm company said in that case it was fine and hung up. Needless to say my friend changed the alarm company as soon as he got back.

Today you would probably design something like this, which allows you to see what’s going on in your house. DIY web cams aren’t the answer though, as they’re susceptible to be hacked. The right combination of institutional and personal information sharing is key.  You might also enable some community and collaborative features which allows the local community to get involved – after all they’re the ones putting up with the alarm shrieking, so they have a vested interest. Not to mention that they run a risk of a similar burglary.

Tony Fadell, the designer behind Nest and now at Google, calls this the challenge of habituation, the way in which we get used to how things are. (Like ignoring the neighbours house alarm). This is a brain feature which allows us to make somethings second nature so we can take our environment for granted without having to process everything we see all the time. The inertia, or lethargy for businesses to change a product or service stems from our habituation process. But also baked into this are network effects, accepted semiotics and social norms. The QWERTY keyboard could arguably be improved on, but the network cost of billions of people relearning how to type is mind-boggling. But the Android app Swype is a great example of a marginal design improvement. You do not want to try and improve universal symbols such as the red-amber-green of traffic lights or the signs for male and female toilets. Yet, we’ve all seen the attempts at creative improvements on toilet signs and I’ve certainly scratched my jaw on occasion trying to figure out the right sign when it’s been too abstract, or when it’s at the bottom of a flight of stairs in a pub where I’m already not at my thinking best.

Having said that, there are hundreds of products and services which could and should be better designed. Increasingly because of the way technology evolution is creating a change in our behaviour. A simple example is business cards, for those of you who still use them. Previously you would try to perhaps make your business card memorable, or be creative about how it conveys your key messages, especially if you weren’t working for a well known and recognizable brand. Increasingly though, you may want to ensure your business cards scan well, mobile apps for scanning business cards becomes a mainstream behaviour. This means avoiding vertical cards, and preserving clarity of the data in an OCR situation. The way Apple Pay or Uber scan your credit/debit cards into your mobile phone apps, is leaps ahead of earlier apps where you had to manually enter the information.

The design challenge of today, is that as products get smarter, and software gets baked into every product, how can we ensure that the experience is a good one. This isn’t simply about traditional interface design, because many products won’t have a traditional ‘user interface’ i.e. a screen of some description. In fact the user interface is now a combination of interaction, transaction, experience and environment design. You have to be aware of how the user is engaging with the product through it’s lifecycle – from unwrapping and setting up the product through to it’s ultimate replacement or disposal – and also how it engages with the environment. Parking sensors in a car is an excellent example of how the product engages with the environment and provides the feedback and engagement with the user so you know how close you might be to the object behind your car. But my earlier example of the fridge filter is a clear example of not considering the environments. I would think most people keep their fridges with their backs to the wall and probably wedged in between other appliances. As such accessing the back of the fridge is difficult and potentially dangerous if you’re moving a large fridge yourself.

One of the best principles for redesigning objects is to re-imagine their evolving purpose. Here are two examples. The first is the ambulance. Traditionally thought of as a vehicle to transport people to hospitals in the shortest time, and designed accordingly. Based on some research, it became apparent to the redesign team that a better way to consider the ambulance as a mobile unit for delivering energy care and medical services. I.e. the treatment begins in the ambulance itself. This made the principles of the redesign clearer and in turn led to a series of changes which dramatically changed the concept of the ambulance design. The second example is the wheelchair. Again, traditionally seen as a way for people with walking disability to gain the freedom of movement,  wheelchairs have always been visually  overpowering. Now, viewed as a way of giving the same people a normal social life, the redesign principle is that when you see somebody in a wheelchair, you should notice the person first and not the wheelchair. In fact even the standard wheelchair symbol is getting a redesign, in New York.

Both of these examples highlight the need for empathy, for research and for re-imagination. Sometimes the hardest of the three is the empathy and this is what makes great design so difficult. Even though plenty of design principles are now chronicled, perhaps none as well as those of Dieter Rams.

dieter rams design principles

In these times of digital transformation, the big opportunity for most organisations is to use software and smart technologies to redesign their products and services in a way that dramatically improves customer engagement, solves the problem or creates delight. The opportunities for rethinking and redesigning are immense, and if you don’t do it, the chances are that there’s a start up somewhere reinventing the design of your products.

Innovation in Pictures

These 2 cartoons wonderfully illustrate the nature of transformation – both the problem of structuring innovation and the opportunities to see things from a different perspective.

Think outside the box

The problem of structuing innovation….

Coffee new business model

The ability to map your business model to true customer needs….

3 Things Most Organisations Miss About Innovation

innovation-illustration live outside the box
There are probably more definitions of innovation than there are books about management, but I have my own favourite definition. It’s simple, and it says “Doing more with less”. To put it more technically – it’s shifting the input/ output curve. Imagine that it takes £100 to build each floor of a house, so a 10-storeyed house would require and investment of £1000. Let’s also suppose that it takes £50 per month to maintain the house. A business with a budget of, say 2000 could expect to build a 10 story house and maintain it for 20 months. Or it could build an 8 story house and maintain it for 24 months. This is the kind of resource allocation choice which most people make routinely in the course of their daily work. Usually the choices are more complex, but they follow the same principles. Innovation is the process where you can bring the cost of building per floor down to say, £80, so now your choice curve has shifted. You can build a 12 story house, and maintain it for 24 months.

So far so good, and so obvious, you might say. But now consider the following questions:

What if your closest competitors are already able to build houses at £80 per floor. Are you still being innovative? What about if companies elsewhere in the world are doing it, but not your competitors?

1: Benchmarking & Exploiting Safe Innovation.

This is the first key thing that people often miss. All innovation needs to work off a baseline. Before we try to do more with less, we need to understand what the benchmark is, at present. And that benchmark needs to consider your company, your competitors, your industry and even at a global level, depending on the area of innovation. In a remote village where people have never heard of pulleys, and people manually pull water out of wells in buckets, the arrival of a pulley may represent a local innovation. But of course, to the outside world, it’s not an ‘innovation’ per se. This is both good news and bad. The vast majority of companies are doing ‘catch up’ innovation of this kind. After all, once something has been done once, it really isn’t innovative any more. It’s just imitation. It’s not innovative to go direct to consumer once Nespresso has shown us the model. It’s not innovative to build an App Store – now that we can just copy Apple. And it’s not innovative to build a ‘wiki’ for your next project. Perhaps this is a harsh view and may be your organisation poses some specific challenges. Actually, on the positive side, this means that there’s enormous innovation opportunity in this catch up space. I call this ‘safe’ innovation, because it’s relatively low risk. The key risk is execution related. Somebody else has proven the model.

So when you next think about innovation, step 1 should be to conduct a benchmark, and identify the safe innovation opportunities based on your competitors, industry, region or global examples. Only once you’ve achieved parity with the benchmark do you really need to step into unchartered territory. And although I don’t have data on this, I’m willing to bet that safe innovation offers much higher risk-adjusted ROI than venturing into new areas.

2: Find A Problem First

Necessity, we know, is the mother of invention. It turns out therefore that Innovation and Invention are actually close siblings. The current thinking on innovation is that you shouldn’t have an innovation department or team. But equally you should first identify the problem you want to solve, in order for innovation to be effective. This is why you get the most innovation in resource starved communities. This is why the Indian ‘jugaad’ style of innovation is getting airtime now. In New Delhi, taxi drivers sometimes use a fake seat belt strap which can be slung over the shoulder at short notice to suggest to any law enforcement official aka policeman, that the driver is wearing a seatbelt. Less ethically cloudy, is the example of the fake steering lock, which is a cheap but realistic plastic decoy which looks just like a metal steering lock, the kind often used in India by owners when the leave a car parked. The plastic decoy acts as a deterrent, and costs a fifth of the actual lock. Or indeed stories about creating post natal incubators out of auto parts so they can be easily maintained.

The resource may not just be money – it may be time. Thus is is that the pit-stops for formula 1 cars have evolved dramatically from 67 seconds to 3 seconds over the past 65 years, and is now proving the inspiration for surgeons in operating theatres.

Resource constraint is often a key problem but identifying a specific business problem or opportunity also helps. The role of serendipity should not be understated – considering the history of 3M post its and many useful tools are the result of a ‘solution in search of a problem’ – notably the flash drive. But almost always, the original effort was aimed at solving a problem – even if it ended up solving a different problem.

Invention and innovation are also connected by concentric ripples – usually a new invention sets off a ripple of innovation as people start to use the invention in newer and unplanned ways. Some of these lead to further inventions but others live happily ever after as great innovations. Almost everything we see on the web today represents innovation around the core invention of the world wide web and a few other key inventions. You can expect to see great applications of graphene over the next few months and years, and everybody knows the story of text messaging, invented for one purpose, but made famous for a completely different reason.
What is common though, is the application of innovation thinking to a specific problem or opportunity. Not just throwing people and resources into a blue sky mode of ‘let’s think of some cool stuff’. That’s usually the least effective way of getting returns on innovation investment.

So the next time you think about innovation, spend the time upfront to ask the difficult questions like ‘what’ and ‘why’ and ‘which’ until you land on a specific problem that needs to be solved. Then unleash your innovation.

3: Where Is The Creativity?

90% of the literature and discussions around innovation focus on how to manage the process. Including methodologies, how to allocate funds, how to build teams, how to nurture ideas, how to measure them, and so on. Yet at the very heart of innovation lies creativity, and there’s not enough discussion about this.

Creativity is often a personality trait. Some people are creative – usually by nature, and often by virtue of the breadth and variety of their work and life experiences. Others are not. Do you employ creative people? Do you employ a variety of people? Do you encourage the variety of experiences? Every time a bank hires an employee on the basis of his or her banking experience alone, it loses a bit of creativity. Obviously, the majority of people working in any industry should be experts in that industry, but creativity is often about introducing an element of managed entropy by adding people who bring a different set of experiences, mindset and thinking to the organisation. When I was first offered a job in a technology company, I said that I knew little about technology. I remember clearly the reply: “I have hundreds of people who know about technology, don’t worry about that” (thanks Pradeep!)

Beyond the individual, the culture and environment play a big role. The physical manifestations of this are easy to achieve – most companies have labs or spaces intended to foster creativity. The harder part is to build an organisational culture that fosters creativity. This means an ability to encourage risk taking, thinking differently, the ability to evaluate a problem through multiple lens, the willingness to continuously look outside of the business for ideas and perspectives and interestingly, a trade off with productivity at some levels. Call it the breathing space for creativity. Steven Johnson calls this the primordial soup, as exemplified by the natural environment where new species flourish. Remember, you can’t process your way to innovation, but you can significantly improve the probability by fostering the right environment.

The third requirement for creativity is the quick feedback system that recognises and rewards early and good outcomes, instead of killing them because they don’t fit the current model. You have to be prepared to be wrong, when you innovate but you also have to rely on being recognised when you’re right. And often, right and wrong can be quite confusing if measured against the yardstick of the past or even the present. The only measure should be – does it solve the problem, and does it do it in a more resource efficient way? No better example here than Kodak, which had created digital cameras long before they were popular, but chose to ignore them.

Bottom Line

So the next time you sit down to think of innovation, in your business or industry, or even in a small group, ask yourself these 3 questions up front.

1. What’s the problem we want to solve

2. What is the currently accepted and best way of doing this, and are we doing that already?
3. Are we bringing creativity to the mix in order to get different outcomes?

Around this you can wrap all the well known lean and fast-fail processes and build structures and systems to scale your innovations. But missing these three things can lead to the creation of a shell of processes without the spark of innovation to actually deliver results.

What Is ‘Digital’?

Despite working in the digital space for years, now I was quite stumped a few weeks ago when i was asked to define it. Sometimes you can get away by circumlocution or to use the technically correct term, waffling. But given all the hype around digital transformation, I felt that it was a good time to try and get a working definition going. For one it helps to cut the hype. And two, clarifies what is NOT digital at a time when the label is being slapped around with abandon.

So I read descriptions of digital in the media, and on our competitors sites. I listened to analysts and and read books and white papers. I asked our clients what they were doing. And I spoke to the experts in Cognizant, and spent time just thinking about this. And I’m happy to say I’m willing to stick my neck out and try and define digital in less than 25 words.

Of course the problem with definitions is the tradeoff between pithiness, abstraction and comprehensiveness. You can be very pithy but be too abstract e.g. ‘Digital is the future of business’. Or you can take a whole page to define digital, but that’s a description and not a definition. So here’s my definition and you’re welcome to challenge it or differ with it, or adapt it as you wish.

Digital means: exploiting emerging technologies to create user / customer centric interfaces and data driven business models, leading to more agile, responsive and competitive business models.

Let’s break this up.

Emerging technologies are certainly a driving force of digital. It’s the reason why we’re having this conversation. But to be clear, there are many discrete elements that make up the emerging technology theme. Arguably the big bang for ‘digital’ is the launch of the iPhone – because it put powerful computers into people’s pockets. It democratised access and provided a platform for almost all the other innovations. Samsung’s (and others’) lower cost and Android driven imitation of the iPhone ensured a mass market for smart phones. Alongside the smart phone though, you have to consider the continuously evolving web 2.0 (are we still allowed to say that?) and the emergence and maturing of HTML5, Javascript and more frameworks to deliver slick web front ends than you can shake a smartphone at. HTML5 and the ever improving web have had a see-saw battle with native mobile platforms, frameworks and entire generations of technology have come and gone in the past 5 years. Remember MCAP and MEAP platforms, and the allure of cross platform development for mobile apps? All of this have also greatly helped social platforms – which includes Facebook, Twitter, Whatsapp and hundreds of messaging and collaboration platforms.

Behind the scenes: But this is not just about front end technologies. Moore’s Law continues to drive the cost of computing down, leading to significant capabilities to process data – be it the in-memory database capability of a SAP Hana or the emergence of Big Data, and our ability to analyse and make meaning of ever larger data sets in continuously decreasing cycle times. Newer and more efficient Graph (Neo4J) and clustered database models (Hadoop) are supplanting the once ubiquitous RDBMS providers. And the en masse shift to cloud infrastructure and smarter automation has created a whole universe of services – starting with the PAAS and now a generic ‘as a service’ nomenclature.

The Internet of Everything: And to top it all, the next wave of internet connected sensors and devices is just beginning. Another whole wave of connected and smart objects has the potential to change everything, again, in the way we buy and consume goods and services. The Internet of Things does not have a single killer app, yet, but it’s growth and spread nonetheless are accelerating.

Its not what you did, its how you did it: the shift in the underlying methodology has played its role. The maturing and widespread adoption of agile frameworks and the toolkits to deliver them is a key construct of digital. The rapid evolution of technologies both necessitates and enables a much more adaptive and cyclical approach to technology delivery.

Design thinking: Almost absurdly, all this fantastic technology is still not what truly drives the digital change we see in businesses us. That honour belongs to the emergence of design thinking and service design methodologies. Some of this is commonsensical and you would think should have been the norm rather than an innovation. But the mind-shift is fundamental. Industry leading businesses are now recognising the need to be customer journey driven. I use the word interface in a broad sense here and not just restricted to screens. The question to ask is how do your customers, partners and even employees interface with your business? Historically, this was driven by inside-out thinking. In other words, businesses decided how they wanted to run their processes and designed systems and interfaces to match those desired processes. So if a bank’s preference was for the customer to be in the branch while opening an account, that’s how the processes and systems were defined. In digital, those interfaces are conceptualised outside-in. This means the starting point is the user. What does she or he want to do? How does the prospective customer want to open the account? What are her constraints? What would make her choice easer and her experience better? Once you start thinking outside in – you reach a very different point in the way systems and processes are defined. And when you combine this user centric interface thinking with the technology opportunities that are emerging you begin to understand why transformation is the buzzword du jour.

Data Driven Decisions: Implicitly or explicitly, every decision we make (what to wear to work, for example) is made on the basis of data that we process (what meetings do I have, what is the dress code, what is the weather?). Complex decisions require more sophisticated data. Historically this data has not been available to us for many large and small decisions. How much to spend on the marketing campaign? Where to open the next store? Who to hire as a program leader for a new business area? How to implement a hot-desking policy? As a consequence, most businesses have relied on ‘experts’ for these decisions, whether they are from within the business or consultants brought in for the purpose. Experts use their wisdom which is often an implicit accumulation of data from deep experience in that area. What we are witnessing, thanks to the combination of lean thinking and instrumentation, is a seismic shift to more explicit data driven decision making. For example, if everybody used a smart phone to access the office for a month or two, it might provide data that suggests that wednesdays are the busiest day of the week while friday is the lightest. The latter may be visually obvious but the former may not. Or the data may show that on mondays, the average time spent in office by people is actually just 4 hours – because they are in meetings or on projects outside. Suddenly there is explicit data to influence your hot-decking policy depending on what your objectives were. This is a tiny example but very representative of how digital is reshaping our decision making. Now imagine this at scale and for the hundreds of decisions made every day and you get a sense of what I mean.

Responsive business models:  we are used to stability and to treating change as a temporary disruption between periods of stability. Not dissimilar to moving house. Increasingly though, we find ourselves in a state of continuous change. The disruption is not a passing inclemency, but it is the new normal. Think of moving from a house to a caravan, for example. What the combination of technologies, design thinking and data surfeit allow us, is to build a responsive or adaptive business model that is able to keep pace with a fast changing environment. Think evolving operating model instead of target operating model. Think of the cost of change as a part of the cost of doing business, not as a capital expenditure. Obviously, industry context is vital – Retail banks and media businesses are much further down the path of transformation than, say, infrastructure providers. But while the impact may vary, the change is universal. Digital is not therefore about B2C vs B2B, it’s not about marketing or about your social media. I believe this is fundamentally about your business model being impacted by better data, delivered at the point of decision making.

Agile Strategy: Seen in this way, it would therefore be logical to look at your strategy as an agile and evolving artefact. Many companies still look at 3 year or 5 year plans which are sequential. Instead, we should be looking at rolling 12 quarter roadmaps which reflect our strategy, but which can be modified on a quarterly basis, keeping a vision or end goal in mind. But more about that some other time.

The point of all this is to be competitive. And digital business models which use technology, design thinking and data optimally are far more competitive in the world we live in. I heard John Chambers, the CEO of Cisco, say ‘Change will never be this slow again’. And 52% of companies from the Fortune 500 list of 2000 no longer exist. Collectively that sums up the challenges and dangers of being change resistant. So whether you agree with my definition of digital or not, a response to the change around us is not optional. Enjoy the ride!

Suggested reading:
Code Halos: Malcolm Frank, Ben Pring & Paul Roehrig
Being Digital: Nicholas Negroponte
Dataclysm: Christian Rudder
Mobile Mindshift: Ted Schadler, Josh Bernoff, Julie Ask
This Is Service Design Thinking: Marc Stickdorn  & Jakob Schneider
The Lean Start Up: Eric Ries