When and Why new thinking overcomes old models

I've been watching the recent gun debate in the US with a lot of interest.  Clearly we have a safety and security issue, with far too many people losing their lives to gun violence, in "unsafe' neighborhoods but also in places that should be safe, like schools.  One of the side effects that is going to be very interesting to watch, and I'm not the first to comment on it, will be the new energy and passion young people who experienced the violence first hand in places like Stoneman Douglas will bring to the debate.  As I think is happening in many places and in many settings simultaneously, old, entrenched models are under attack by new ways of thinking and new dynamics in ways that we've not seen before.

Whether its the entrenched power of the NRA facing off against a new and younger population who are fed up with gun violence, or new ways of moving and managing money (digital and alternative currencies) versus traditional finance and banking, a lot of existing business models, thinking and infrastructure are under attack or up for debate.  The question becomes - which wins?  Does new innovative thinking, passion and new dynamics have the power to overcome deeply entrenched existing business models and policies?  Why should this time be different?

The Tipping Point

More importantly, in any setting where existing models and infrastructure confront new dynamics, opinions or innovation, what is the tipping point that eventually collapses the old order?  In many cases companies and industries will become bankrupt in the same way Hemingway described:  gradually and then suddenly.

Look no further than GE.  How does a company heralded for its financial strength and acumen, with leaders who are constantly feted as CEOs of the century suddenly become a pariah to the stock markets and have to shed entire businesses to stay afloat?  Welch created and Immelt perpetuated a company culture and structure that became too rigid, too inflexible and while often heralded as an innovator GE proved unable to scale innovations or create radical change because the company was too wedded to existing models.

Many people believe that the tipping points will originate from technology or capability.  Their arguments are based on the emergence of new technology and its capability to disrupt existing processes and models.  Bitcoin and alternative currencies are used as potential examples.  While these ideas may have some merit, I think they get it exactly backwards.

People and Policies

There are two tipping point signals that really matter and they are intertwined.  They are people and the policies, governance or regulation that they allow or endure.  Dramatic change in any setting - government, politics, gun enforcement, MP3 distribution, you name it - don't change dramatically because of new technologies, but because of shifts in people and policies.

People and their politics will be behind any new gun legislation.  People and their willingness to accept or their ability to understand alternative currencies will be behind the success or failure of Bitcoin.  People and their needs and demands will be behind whether or not GE can right itself.  People and their politics were behind GE Financial's downfall, and will be behind whether or not GE rights its ship.

We all recognize that driverless cars are the likely future.  What is slowing down adopting and rapid dissemination of this capability?  Not the technology, which promises a bright future.  Not funding - the VCs are eager to fund the rollout and to anoint winners and losers.  What slows driverless or autonomous vehicles is the ability of people to adapt to these ideas and the politics of regulation and safety.  People and politics will be the sticking point that slow adoption and use of these vehicles, just as they are in any new disruption or innovative adoption.

Old infrastructure is powerful

Old models and old infrastructure has a lot of staying power, because we tend to cling to existing investments and what appears safe and conventional, even after what is safe and conventional has changed.  We still think flying is dangerous, when you are at more risk driving to the airport than flying a much greater distance.  The old, existing infrastructure creates FUD, while the new ideas and solutions can only promise future benefits.

The tipping point occurs in every instance when people decide that the old infrastructure no longer satisfies their needs, and when politicians and regulators are moved by the momentum of the people to make changes that favor new ideas and no longer support old infrastructure.  This is why the kids from Stoneman Douglas may create change that other mass shootings never did, although there's enough investment in the old laws that unfortunately may lead to just tinkering around the edges.

The tipping point also usually emerges from an unlikely or unexpected source.  As I've discussed before, MP-3 distribution was in demand even when it was illegal.  Napster was doing it long before Apple got involved, and Sony should have dominated this market because it had both a catalogue of music and a player.  It took Apple to recognize the demand from the people and to create the regulation or "politics" (licensing) in the situation to realize the opportunity.

Looking for the tipping point

When you are looking for change, anticipating a shift or wondering when a new technology could reach critical mass, look for the critical shifts in people and their opinions or demands and the concurrent shifts in politics, regulation and policy.  When we look at trends, we constantly look at four criteria:  Political, Economic, Societal and Technological or PEST (an acronym from the first letters of each word).  People are inherently behind the Political and Societal issues, and often have more impact than the technology.  Look at what's happening with people, markets and consumers and the impact or influence they have on regulations and policies to understand when new thinking will overcome old, embedded models or infrastructure.

Six factors that lead to greater innovation success

I've been thinking a lot about why innovation fails.  Not about why supposedly innovative new products fail, because there are multiple reasons for the failure of a new product.  It could be too early or too late in the market window, or it could simply have the wrong pricing or distribution.  A new product may lack key features or components, or like some successful products take years to build an audience.  I'm actually more interested in the 90+% of ideas that never make it to product development.  Why is there so much failure in the front end of innovation?

I was going to write this describing the failures in the front end, but that seemed too negative.  If we can identify why ideas and processes fail, then we can begin to add value to innovators everywhere.  So, first a brief segue into the importance and value of failure, then six ideas to implement to increase innovation success in the front end.

Failure - the good, the bad and the ugly

Let's first admit that some failure is necessary.  If some ideas don't fail then we probably aren't stretching ourselves and our thinking.  If you have a very high success rate in the front end, then it's likely all of your ideas are incremental.  To some extent failure demonstrates that your front end is exploring, discovering new ideas and technologies and stretching the definition of the company and its value proposition.  As much as any can be, these are good failures.

A lot of failure isn't due to ideas, however.  A fair amount of failure in the front end is tied to too strict metrics, too onerous expectations, too little patience, a culture that resists innovation and wants to get back to efficient, effective operations.  This is the bad side of failure.

Of course, the ugly failure is taking a poorly conceived idea and pushing it through a product or service development process, incurring significant costs, only to see the new product fail in the marketplace.

Six ideas to accelerate success in the front end

1. Spend enough time scoping and shaping the innovation opportunity.  Often executives will say they need new solutions in a specific area or market space, but fail to establish exactly what the outcomes or deliverables should look like, how much divergence from existing products should be delivered, and the potential range of innovation outcomes (products, services, business models) is acceptable.  Without better scope and definition, the innovation teams almost invariably constrain themselves to something that looks and feels a lot like existing products or services.
2. The more divergent and/or disruptive the opportunity, the more you need to conduct trend spotting and scenario planning to understand how the future may unfold.  Incremental ideas simply add features to existing and valuable solutions.  Disruptive innovation creates something radically new, so it helps to have a sense of how the future may unfold, to predict emerging needs or segments.
3. Gather market and customer needs, using both qualitative and quantitative means.  Understand the market and the customer.  Understand the existing solutions, the alternatives and the substitutes.  Find unmet or underserved needs, and understand the value and importance of those needs to your customer.
4. With this framing and context as convergence, diverge again to find the best technologies, IP or ideas, either internally or externally, that create solutions within your scope and based on your research.  Whether you conduct a brainstorming exercise or use open innovation, this is a new opportunity for divergence to find the best solution.
5. Prototype, prototype, prototype.  Build prototypes and conduct rapid experiments with your ideas.  Get rapid feedback and incorporate the feedback into a new round of prototyping.  This confirms your assumptions and provides meaningful feedback from customers.
6. Understand your commercialization path.  You may simply place the requirements for the new product or service into your product development program, but other pathways to value exist.  What are the best pathways to value?  Licensing, partnering, joint venture and other means are also available.  Consider the best means to get the new idea to market and to value.

If you can frame your innovation activities in such a way that you improve the definition of the activities (scope) and gain more insight and definition about customer needs and market trends (context) then your second divergence (finding the best ideas or technologies or IP) will be much easier.  Using more and more frequent prototyping helps accelerate the identification of the top attributes and features, and signals customer demand.  From this you can plan the best path to value.  

Building these attributes into your front end process will not eliminate failure, and that's not your goal.  Your goal is to have the appropriate amount of good failure (early) and reduce or eliminate bad failure (late).

Innovation Depth makes the Difference

I've been thinking about innovation for a while now, trying to puzzle out why some organizations seem to be able to innovate almost effortlessly while others are more sporadic or face significant innovation challenges.  At some moments in my career I've blamed this phenomenon on lack of breadth - the idea that too many companies shrink innovation activities down to idea generation and rapid evaluation.  This isn't completely wrong, there still is a lack of innovation process breadth and not enough appreciation for the thoughtful exploration and divergence in the 'front end' of innovation, followed by rapid prototyping and realization in the latter stages. 


However, I'm warming to the idea that the real problem with innovation, the real reason so few organizations can perform innovation effectively, is a lack of depth.  Because even if we get the innovation process (steps, activities, tools, methods) right and follow them carefully, a lack of depth constantly slows or distracts innovation teams.


Let's set our definitions


When I'm talking about innovation breadth, I mean from the start of an innovation activity (typically an executive who needs a new product or service or wants to attack an emerging opportunity) through to product or service realization.  Now honestly some of that breadth is in product or service development, not necessarily the responsibility of the innovation team, but to fully count as innovation we need to release a product or service that has impact on customers and the bottom line.


Too few companies have a good understanding of the 'front end' and the important activities and processes, but many can stumble through.  What we need to turn our attention to is the depth question.


When I'm talking about innovation depth I'm talking about capacity building - people with deep skills or experience using the tools and methods defined in the innovation process.  I'm talking about a depth of commitment of those people, who aren't rushed into and out of an innovation activity but can commit the time necessary to do it right.  I'm talking about the depth of commitment of the organization, so that innovation isn't a flavor of the month.  When we talk about innovation depth we are talking about the recognized 'range' of innovation outcomes (I like Doblin's ten types).  Depth also embraces the corporate culture and how it enables or resists innovation, rewards and recognitions and so on.


In other words, innovation breadth is about defining and understanding the end to end process for innovation, the tools, processes and methods and ensuring this is continuous and whole.  Depth is about deciding how capable the innovation process, tools and people are, and how supportive the corporate culture, funding mechanisms and reward structures are, as well as ensuring that people have the necessary time to perform innovation activities effectively.


Sustaining Innovation


Now to the analysis.  Any company at any stage of its existence can stand up a team, define some simple tools and describe an innovation process.  That's not overly difficult, and as evidence shows many companies have done exactly that.  They have a defined process (on paper) and in some cases even a product or service to demonstrate as an outcome.  Frankly most of these processes are incomplete, not well thought out and excuse the pun but paper thin.


Developing the capacity to innovate, building the depth of purpose, skill, experience, time and funding, changing or rethinking rewards and how people are allocated, is a much more purposeful and taxing experience.  It requires real strategic thought because expectations and even the nature of work changes.  This is a real - I almost hate to write this - change management effort, because we are changing the expectations of at least some people, changing how they are tasked, skilled and compensated.


Having the cake without baking it


So, what I'm saying is that many companies want the outcomes of innovation, consistently and reliably, without taking the time to invest in the processes and tools and people who can make the outcomes happen.  This is worse than expecting to have a cake and eat it simultaneously. This is trying to eat the cake without bothering to bake the ingredients, perhaps not even being careful to have the right ingredients in the correct measures. 


I honestly believe these paper thin innovation processes have to change, because they cannot stand up to consistent use.  My expectation is that every company will need to do more and more innovation, and an innovation process without depth simply cannot stand.  The alternatives are to outsource innovation and hope your consultants get it right, or to develop depth in your innovation process to mature it and harden it for more consistent use.

Will big data solve the innovation gap?

For many companies, I think there is a relatively significant gap between what they actually generate as compelling new products and what they wish they generated.  We could call this the "innovation gap".  The gap is real, and it means that many companies aren't as profitable or as competitive as they'd like to be.  Many of have (in some cases for years or decades) advocated tools and methods as a way to improve the innovation funnel, to create more innovation more readily that had value as new products and services.  To date, there's been some improvement but the innovation gap still remains.


Lately, with the advent of "big data", machine learning and other factors associated with data and more intelligent processes, the argument has been made that these capabilities will solve the innovation gap.  This claim seems to suggest that big data and analytics and machine learning can do a better job in the front end generating new ideas that lead more rapidly to new products and services.  And at some level I agree, but I think placing too much emphasis on big data or machine learning for all of your innovation work is a mistake.


What big data and machine learning could do


Basically, the 'front end' of innovation is an exploration and discovery activity, meant to discover needs and opportunities and assess customer needs in order to generate new ideas that may or may not solve the problem.  Good innovation is both a discovery and a combinatorial effort, which in some regards means that machines and algorithms must be able to parse through more potential combinations than humans can.


The challenge with this thinking is that in many cases, humans create the rules by which the algorithms work, and if humans are often blinkered to new ideas or emerging technologies or unusual combinations, then the algorithms may be as well.  Further, having an algorithm spit out hundreds of potential combinations without the ability to assess their viability or value seems rather meaningless and complicated.  Beauty and efficacy is often in the eye of the beholder.  I never knew I needed or wanted a multi-tool until I got one for Christmas.  And even today, while it's breadth of tools is undeniable, it often sits in my drawer at home, as I suspect many of them do.


There is definitely a place for big data, analytics and machine learning, but I think more as a component of a viable front end process than a replacement.  For at least some time into the future, humans and their ability to connect and assess ideas and identify trends and opportunities will do a better job than machines alone.  Intuition and past experience count a lot, but leveraging the data and insights that big data and algorithms can create will increase value in the front end.


What humans do better


Machine learning is still nascent, and still trying to capture the spark of real intuition and foresight.  This means that today most machine learning is exceptionally good at anticipating and predicting outcomes when the conditions are similar.  This means that for some time into the future, machine learning and algorithms should be able to anticipate incremental innovation demands.  However, I'm not so sure about disruptive needs and opportunities.


Humans are omnivorous connectors.  We are happy to ignore what should be incompatible needs or standards to connect things that don't seem to be connectable.  We connect things in random, often unexpected ways (you got chocolate in my peanut butter) that sometimes lead to spectacular failures and other times lead to amazing successes.  No algorithm could have predicted Steve Jobs and Apple combining MP3 players, digital music and a distribution mechanism called iTunes.  Therefore, companies that focus on machine learning and algorithms in the front end may perfect their incremental innovation and completely ignore disruptive innovation.


Watch this space


With all that I've written above, the capability of the algorithms and machine learning is advancing quickly.  It would not surprise me to find algorithms that get much better at predicting future disruptions and breakthrough innovations that emerge in the next 5-10 years.  Even then there will be a significant human component to understand and place the disruptive opportunity into context.


Fifty years ago we were promised individual jet packs and residence on the moon by the year 2000.  2001 promised a journey by an intelligent AI and astronauts to Jupiter.  Here in the real world some technologies have advanced quickly, but I think more development is necessary before we hand over the innovation reins to AI.  But that doesn't mean machine learning and big data doesn't have a place in the front end now, and those that start incorporating these as an input (not a replacement) to the front end will learn and benefit in ways that will cause others jealousy or regret.

Yesterday or Thinking about Tomorrow?

The Beatles (they were a pop group for those of you who cut your teeth on Eminem) wrote jangly songs about yellow submarines and walruses.  It was the 60s, so I guess you had to be there to understand.  They were all about sunny days, happy feelings, a kind of Beach Boys from England with mod outfits and mop top haircuts.  They also had that outrageous Sergeant Pepper phase, but I digress.


The Beatles also had a few melancholy songs, perhaps none more famous than "Yesterday".  Yesterday is a song about looking back with some regret, after realizing that the recent past wasn't so bad, that some opportunities may have been missed.


The Beatles were innovators in rock and roll, introducing a new perspectives, a really interesting competing view of the world between Paul McCartney and John Lennon, introducing eastern musical themes and instruments into rock and roll, and many other innovations.  But for innovators I think the most relevant song they sang was Yesterday.  It's also one of the most covered songs in history.


Why Yesterday?


Missed Opportunities
Yesterday is about missed opportunities, and if anything about innovation is true, all innovators will acknowledge that far too many innovation opportunities are ignored, missed, skipped past.  Too often we don't even become aware of innovation opportunities until someone else has capitalized on the opportunity.  In hindsight all innovation seems evident, but it rarely seemed that way at the time.


Timing
Also, there's a realization in yesterday.  The old joke goes that the best day to start a diet if you want results was yesterday, but the best day to start if you don't want the pain is tomorrow.  If you replace the word "diet" with "innovation" the saying holds.  The best time to have started an innovation activity is almost always "earlier than this" because it takes longer to do good innovation than most people realize, and the opportunities open and close more quickly than most people expect.  However, like dieting, most teams put off innovation until it is an absolute necessity, and then cheat their way through the diet.  The best time to get started with innovation was yesterday, but that doesn't mean we can't start today.


Nostalgia
The final idea that relates Yesterday to innovation is nostalgia.  The singer looks back on missed opportunities and how wonderful the past was.  Likewise, many people and companies tend to look back at the past through rose colored glasses and see only difficulty and challenge in the future.  Innovators know that the best opportunities like in front of us.  Let go of the past, look toward the future with optimism and expectation.


Thinking about tomorrow


In fact, if we are going to stick with a musical theme, the innovator's mantra is Fleetwood Mac's  "Don't stop thinking about tomorrow", always looking forward, always thinking about possibilities.


So, which perspective do you and your team favor? A nostalgic look back, full of regret about the past, clinging to what you have, or a more optimistic view toward the future?  Are you caught up in Yesterday, or thinking about tomorrow?  Innovators will always be thinking about tomorrow.

Don't forget the steak: What Super Bowl ads forget

There's an old marketing adage that you sell the sizzle, not the steak.  Sell the benefits, not the features.  I wonder, as I watch Super Bowl television ads, how many marketing people have forgotten the basic tenets of their craft.


This isn't to say that the ads aren't catchy, funny, endearing and often engrossing.  But sometimes the ads are so interesting or so well developed that they neglect to tell us what they are for.  In other words, watching these ads makes me think that we've completely lost the steak in all the sizzle.


A good example is Tyrion (Peter Dinklage) up against the voice of god himself (Morgan Freeman).  The rap battle was great, but the products they were featuring were barely acknowledged.  It's as if we are supposed to buy the products because of the really interesting advertising, rather than the benefits they provide.


What's this diatribe got to do with innovation?


Going through the elaborate motions


As a blogger and consultant I make a living talking about the importance of innovation process, that innovation is a repeatable business process that any company can learn and master.  So I have to tread the razor's edge here when I say increasingly corporate innovation looks a lot like Super Bowl advertising.  Too much focus on the sizzle and not nearly enough on the steak.  Alex Osterwalder has taken to calling this "innovation theater", where the players do their bit, act out innovation roles but in the end we are left with nothing but an empty set.


Let me be clear:  innovation processes, defined workflows, fully understood tools and methods, are vital to doing good innovation, but increasingly what we see is Potemkin Village innovation (if you'll excuse the introduction of another analogy), a false front dressed up to look great, but with very little going on behind the scenes, and no results.


Many innovation teams are going through elaborate motions, adopting many techniques on the surface but not fully understanding them, or doing the exploration and deep thinking and discovery necessary to develop breakthrough ideas and products.  There's a lot of activity, reference to interesting tools and methods, some templates are completed and with a lot of fanfare, ice breaking and sometimes yoga.  But in the end, there aren't any interesting or valuable ideas.


What's missing


What's missing from this elaborate kabuki theater is actual commitment to investigate needs, understand future trends and draw conclusions about emerging markets and needs.  What's missing is the desire to put in the work to change the existing business model, disrupt existing revenue streams and products.  Innovation will often spin off into elaborate motions when people realize just how much and how radical the change is that's needed.  Once the realization happens, it's easier to go through the motions, to call on Peter Dinklage and Morgan Freeman to rap battle, than it is to say exactly why Doritos or Mountain Dew is so much better, or tastier, or healthier, or less expensive, than other alternatives.


 And yes I get the fact that Dinklage being on fire means the new Doritos are spicy or that everything Freeman touches turns to ice means that the Mountain Dew flavor he was advocating (which one was it?) is cooler or more refreshing.  And this is where the analogy breaks down.  When you are marketing, subtle signals may reinforce value propositions for the potential customer.  Other than discovering customer needs, there's nothing subtle about innovation.  It's not called "creative destruction" for nothing.  You can't wink wink nudge nudge innovation.  It requires commitment, willingness to change and to overturn existing markets, customers and revenue streams.


I love the Super Bowl ads, don't get me wrong, but I think you could easily insert the logo of a different company into many of the ads and the ads would achieve about the same effect.  They are too subtle, too full of themselves to do any good except for the advertising agencies that create them.  Likewise, a lot of innovation is too subtle, and too resistant to change, to do any good.  It becomes innovation theater, and we need to go back to the basics to create really compelling products.