A couple of weeks ago I was given an advance copy of a new book called The Other Side of Innovation: Solving the Execution Challenge, by Vijay Govindarajan and Chris Trimble, two faculty members from the Tuck School of Business at Dartmouth.  The publishing date will be September 2, 2010.

I'll start by saying that this is one of the most useful books on innovation I've read in a long time.  I want all of my clients to read it.  A few months ago, I wrote a post cautioning business leaders against expecting innovation to happen within their development processes.  In this book, the authors focus on this point, and provide clear guidance for developing innovative ideas that cannot (or should not) be developed within the existing development process.

The book is broken into four main parts:

In the introduction, the authors provide some good background information to help the reader to discern whether or not a new idea should be developed within the current development process, or whether a new process should be created.  They use clear examples, and illustrate which types of ideas the current processes should be able to handle, and show examples of companies that have executed both within new and existing processes.  In this section they also lay the groundwork for their basic premise that managing innovation is not a wild, maveric process.  It is a controlled, disciplined process that just happens to look very different from managing the day to day business.  The rest of the book discusses how to create and manage the new process once it is determined that the innovation cannot be developed within the existing process.

The next two sections present the heart of their recommendations for executing innovation.  The first section contains three chapters discussing how to build the team.  They call the team charged with developing the new innovation the Dedicated Team, and clearly point out how this is different from the team that is charged with managing day to day development, called the Performance Engine.  These designations are very useful, and the authors do an excellent job of describing how the two teams need to collaborate, how to select people for the Dedicated Team, and how to manage the partnership between the two.  They also make a nice distinction between the responsibilities and challenges the leader of the Dedicated Team will face, and the role of the senior executives who need to support them.  What I found particularly useful is that they identified just about every "pink elephant" that could be in the room when discussing these issues, and this book could be used as a guide to foster objective discussions about potentially sensitive issues.

The second of the two sections discusses the management of the innovation initiative itself, referring to the work of the Dedicated Team as running a disciplined experiment.  These chapters provide an excellent resource for illustrating how the work of executing innovation is very different from the work of the day to day development process.  It discusses performance metrics, and how Performance Engine metrics will be harmful to the execution of innovation initiatives.  They present an enlightening way to talk about planning, acknowledging that plans for innovation initiatives can only be based on assumptions.  The goal of the process is to focus on learning, considering the initial plan as a hypothesis, and adjusting it as more information is learned.  They also discuss the fundamental difference between this approach and the Performance Engine approach, which is to focus on results and adherence to plan.  Again many "pink elephants" are exposed as the authors point to the many ways it is easy to fall into the trap of using Performance Engine metrics when evaluating against assumptions.

The final section is the conclusion, and here the authors share several innovation myths, many of which center around one main idea.  Managing the innovation process is not the result of people breaking rules, creating crazy ideas, and throwing things against the wall to see what sticks.  This is akin to what I would call running a casino inside your company.  Instead, managing innovation requires just as much discipline and rigor as managing the Performance Engine.  In fact there is no room for running on autopilot, as the team needs to be on their toes constantly to evaluate what they are doing to see if they are getting closer to their goal.  The authors do a great job of calling out and dispelling these myths repeatedly throughout the book, and it's nice to see them listed out at the end.

Finally, this book is clearly for people looking to manage the execution of innovative ideas to make them real within an organization.  It is not for people who are looking create new ideas.  In fact there was only one statement I disagreed with, and it came at the end of the book.  As the authors were reiterating their point that innovation cannot happen without disciplined execution, they correctly point to the fact that most organizations focus most of their innovation efforts on the Big Idea Hunt.  They then say that the Idea Hunt may be serendipitous and difficult to manage, but that this random nature applies only to the Idea Hunt.  Here I strongly disagree.  In my work, I apply similar principles and discipline to the Idea Hunt.  What this tells me is that regardless of whether you are trying to create new ideas, or develop the most promising ones, developing innovative ideas is anything but random and Govindarajan and Trimble have presented an excellent guide for how to execute them.

I was recently asked to contribute a short piece to the blog section of a new website - OnInnovation.  It's sponsored by the Henry Ford Foundation, and is intended to collect insights from innovators and thought leaders, and enable people to connect with their ideas.  I thought it was a great idea, and one worth supporting.  Below is an intro and link to my post:

Preserving Dignity to Drive Creativity
Posted August 10, 2010
We’ve all had the nightmares in one form or another.  You find yourself at a podium and you forgot what your speech was about.  Or you are at the office and realize that you aren’t wearing any pants.  These nightmares are powerful reminders of our deep seated fear of exposing ourselves to the judgment of [...]  Read Complete Post

I'd love to know what you think of the site.  Does it have legs?

I was recently reminded of the "hit rate" for investment in innovation (I'm also including entrepreneurial ventures here).  Most companies, VC's and others use estimates as rules of thumb.  An optimistic one is something like 1/3 of their investments will be winners, 1/3 will break even, and 1/3 will fail.  Others are more like 1% will be wild successes, 2 - 3% will do OK, and the rest will fail.

What's interesting to me is that most people accept these rules of thumb.  The reason why this is interesting is because this means that for the most part, people buy into the idea that the likely success of a new venture is largely random.  And yet there is a lot of money being spent on market research, market testing, basic due diligence, etc. before deciding to pursue a new opportunity. 

Clearly, there are forces at work that the current business community and education system do not yet recognize, let alone support and develop.  Steve Jobs' success at identifying and developing winning ideas may be intuitive, but it is not as if he is a magic person with a crystal ball.  He is just an example of someone who naturally has the ability to connect underlying market motivations with new and different offerings to satisfy them.  I'm sure there are others who have this natural ability, but if they do not also have the desire or skill to be the CEO of a large company, then the output of this ability will not be as apparent. 

There is a lot of talk about the "new economy", and how the skills that got us through the industrial age will not work to take us forward.  And yet we are so entrenched in nurturing the skills necessary for success in the industrial age, that we no longer remember the fact that it took a lot to get people to focus less holistically so they could work more efficiently within the required corporate silos. 

Success in the future will require that we recognize, develop, and nurture the ability to think holistically; to be able to see similarities in ideas and objects that appear dissimilar on the surface.  This is what is necessary to make a connection between an underlying motivation, and developing a new solution to satisfy that motivation.  In my opinion, the current "rules of thumb" tolerate a lot of waste in the system.  I think we can do better.  Until then I'll continue my work in helping to build a linear path for organizations to reduce the random nature of their innovation investments.  It seems that it's currently the only way for the people who can think like Steve Jobs, but are not Steve Jobs, to make their ideas heard.

This all makes me wonder about two things.  Will we ever get to the point where most of us can spot the difference between a good creative idea and a bad creative idea before we invest in developing a product to see real market results?  And will we ever get to a point where people will recognize the limitations of linear logic, and use it in good balance with more holistic logic?

I've been talking to some people in the software industry about innovation, and we were comparing my innovation and development processes to agile and waterfall development processes used in the software industry.  At first glance, I thought it was a straightforward comparison; that the innovation process I describe is analogous to the agile development process, and the development process I describe is analogous to the waterfall development process.  After thinking about it more, I realized that it wasn't so simple.

The similarities are that the innovation process and the agile process are both iterative, while the development process and the waterfall process are both sequential.  In fact the development process I describe the waterfall development process used in the software industry are very similar, and work well when a process is known, needs to be repeated, and it's important to optimize it.  As I described many times, the system falls apart when companies try to innovate beyond incremental improvements when using this process.  The problem in the software industry is that the waterfall process is too often used to develop very new products.  As a result, people spend time trying to estimate very detailed steps required to develop something new.  However, if it's completely new, these steps are often unknowable.

While the development and waterfall processes are similar, I realized that the innovation and agile processes are only similar in that they are iterative.  The main difference is that the innovation process as I describe it is used to figure out what new products and services should be developed.  It requires a deep understanding of the market, and the ability to translate market needs into criteria for a successful offering.  On the other hand, the agile development process is an iterative way to develop an offering that has already been defined.  What is not known is the best way to develop the offering, because it is the first time it is being developed.  The future is uncertain, and this process acknowledges that as long as progress is made toward a defined goal, the correct steps will be taken at that time.

This also points out why many companies may fail to develop breakthrough innovations even though they are working with iterative processes while they develop new offerings.  Ultimately, development processes of any type are best used to develop defined offerings.  You can't "develop" your way to a breakthrough.  That can only be done by understanding what motivates the market, and translating that motivation into criteria the development team can work with - whether they iterate it or not.

In my last post I discussed four dimensions of innovation. Innovation is a very broad term, and impasses in understanding often result when people are using similar terms to describe very different things. In summary:

Innovation for Optimization - Creating and developing new ways to manufacture and deliver existing offerings to the market.

Innovation for Improvement - Improving the existing offering as it is perceived by the market.

Innovation for Invention - Developing new offerings that will deliver known benefits in ways that are currently unknown, but ultimately more relevant to the market.

Innovation for Disruption - Developing an offering that changes the competitive landscape of the market.

In distinguishing between different dimensions of innovation, we can begin to see that working to achieve the goals of each type of innovation requires very different types of problem-posing and problem-solving skills.  This also results in the need to make sure the innovation process itself is conducive to the work that needs to be done.  Let's think about how the process may differ to best enable each Dimension.

If we think about the first two Dimensions - Optimization and Improvement - the similarity is that the criteria for a successful is already defined, and the benchmarks are well established.  With Optimization, the goal is to deliver the same offering that has always been delivered.  Success can be easily measured.  With Improvement, the offering is different from the existing offering, but the existing offering is used in comparison and as a benchmark.  Since both of these Dimensions can be compared to what the company is currently doing, the existing development process is probably fine for managing the work.  Yes, issues arise when teams try to introduce levels of variation in Improvement projects, but most often, the process itself will dictate how far the variation can stray from the norm. 

In most companies, Innovation for Improvement is about as far as they can go in developing something new.  That's because that's the limit of most existing development processes.  If they can even attempt the second two Dimensions - Invention and Disruption - they struggle with them at best.  Think of the large corporations that spend lots of money on blue-sky R&D, open-ended market research, and open solicitation of new ideas that have a difficult time getting a new invention or disruption out the door.  That's because the existing development processes are not equiped to handle such a great variation on the theme.  Different processes are necessary to achieve the goals of the Invention and Disruption Dimensions.

So what does a process for Innovation for Invention and Disruption look like?  While the details may vary, there are some basic components that are necessary:

The main goal of this process is to define the criteria for a successful offering.  Just as Innovation for Optimization and Improvement start with a benchmark, it is equally necessary to know how to tell if we've done a good job.  This criteria is more fundamental than a benchmark, and is often described in terms of market motivation as expressed as an opportunity that informs all the other business disciplines. (Notice that it is not a fully formed solution. It needs to enable multiple solutions, and transcend specific technology solutions.  It should guide the development of new technology, not be a result of it.) Once this is in place, the other components follow:

It is not random.  Just because existing benchmarks are not relevant, that does not give license to just make things up.  This does not mean that everything needs to be linear, quite the contrary.  Non-linear and random are not always related.  If you've done a good job of creating the success criteria this will become obvious to the right people.  Which leads us to people:

The people need to have strong problem-posing abilities.  Too many random solutions live past their useful life because of a lack of problem-posing abilities in an organization.  In this process we must first pose the right problem, the solution to which will satisfy the success criteria.  This will then set the stage for any problem-solving activities.

The team should be multi-disciplinary.  Although people must first be selected for problem-posing abilities, they should also come from different disciplines.  This will help the team to avoid blind-spots, as well as ensure that the opportunity is translated accurately to the rest of the organization.

It must feed a development process.  Development processes are good at delivering an offering to the market.  The opportunity must be defined in such a way that the following development processes is informed, but not spoon-fed.  Therefore it is good to have some crossover people from the development team involved in the innovation process, as well as have some innovation team members move into the beginning of the development process.  Think of a baton hand-off in a relay.  It's not an abrupt hand-off at one point in time, but a gradual ramping up and down of the team members doing the transition.

These are the most important aspects, and I'm sure more points could be added.  But the important point is that this process is different from the development process: It is comprised of people with different skills, has different goals and outcomes, and should not be force-fit into an existing development process.  When people at your company talk about innovation, stop and think about defining what type of innovation is really needed, and then make sure the right process is being used to realistically enable it, and outsource it if you need to. 

We hear a lot about the need to break down silos, to look outside of the usual venues for innovative ideas, and to embrace new points of view. In this day and age, we have access to more information from more sources than ever before. At first glance, it would seem that the task of collecting different ideas and points of view would be easier than ever.

Unfortunately it doesn't always play out that way. Because there is so much information out there, the new challenge is in filtering out what is relevant from what is not, and this task is as daunting as finding new information used to be. Think about this the next time you search for information. How are you determining the relevance?  What are your filters? I do believe that people need filters to help them to cut through all the daunting information out there.  However, what I'm finding is that it is now the filters that are limiting the diversity of the ideas and points of view, rather than the desire to seek out what is new.

Filters are useful to the extent that they are used to focus the mind to recognize relevant information. But how often do you notice when people are using irrelevant filters? For example, if a certain author or expert provided useful information in the past, their point of view may be less likely to be questioned in the future. It becomes a shortcut that is intended to save time, but can result in blind following and group think. As I've said before, there is no excuse for not thinking about what you are doing. Especially in the realm of innovation, every problem is unique and a new filter must be created for every query for new information. This doesn't need to take a lot of time, but it does require that you stop and think before blindly accepting or dismissing new information or sources.

What filters are you using as you make decisions about new ideas or points of view? If you ask yourself if they are relevant to your current task at hand, you may be surprised at your answer.

This weekend I read a fascinating article by Columbia professor Dr. Robert Jervis in the Boston Globe.  He wrote about the way our brains make connections, how these connections inform our decisions, and how this process could have contributed to the incorrect decisions the CIA has made when drawing conclusions about terrorist threats.  He made two points that were of particular interest to me.

The first point is his assertion that humans are very good at recognizing patterns and making connections that are relevant to our world view.  In the work I've been doing, I would call this a linear connection.  The second point is that once humans reach a conclusion, they are not very good at questioning their initial assumptions.  They tend to disregard or manipulate data that could call their conclusions into question. (I'm sure we've all had frustrating experiences with this human trait.)

After reading the article, I was struck by the similarities between the problems the CIA is experienceing, and th eproblems many companies have when trying to innovate.  And as is often the case with companies it became clear that, while I'm sure the CIA has plenty of good problem solvers among their ranks, I would bet they are lacking people with good problem-posing skills.  Successful innovators are very good at questioning assumptions, making non-linear, synesthesia-like connections, and posing new problems.  These people are more open to finding the path that reconciles the data they have, rather than paying attention only to the data that reconciles the path they have chosen.  Sound familiar?

All of this then made me question one of my own assumptions.  I believe that people who can make relevant (as opposed to random) connections between seemingly disparate ideas have a heightened ability to make cognitive connections.  I have imagined this very physically, as a brain with more physical connections being made. But is it really this way?  Maybe these people lack the ability to make the well worn connections that others make, resulting in the need to make new connections more often.  Or maybe it's not physical at all.  Is it due to a difference in the way we perceive information, or a tendency to suspend judgment until all data is reconciled?

I don't have an answer as to why this happens, but as I work to build models to objectively select people with good problem posing abilities I'm realizing that the need to identify and nurture their skills is broader than I had anticipated.

We've talked about the difference between the innovation process and the development process in terms of the results they are expected to achieve; the innovation process being used to identify market relevant opportunities for innovation, and the development process being used to efficiently and reliably get offerings into the market.  We've also talked about how different people, and different thought processes lend themselves to achieving these goals. 

What we haven't talked about is how the different processes should enable people to best do their work.  This is where we often see culture clashes in companies who try to standardize performance objectives based on discipline when they should be targeted to the overall objectives they are tasked with achieving.  Let's see how this plays out by examining some common process elements and seeing how they differ between the innovation and development processes.

The complexity of the development process can best be defined by the sheer number of tasks, functions, and people that must be managed.  It is often a project manager's sole job to coordinate and keep track of everything that must happen.  This person also communicates the interrelations between the tasks required of different functions so that the team can proceed toward the goal.  For this reason, quality of work is evaluated based on whether or not the team members complete their required tasks efficiently and according to schedule.  There are well defined parameters for the completion of tasks to hit project milestones.  In fact, every task is planned and scheduled before the project starts, and the project operates under the assumption that when all tasks are completed, the project is done.  As can be expected, the planning process is very involved, but this typically happens once, when the process is being initially determined.  After that, most projects are similar to the first and can follow predictably along the same steps. So, it can be said that the purpose of the development process is to ensure that human error can be engineered out of the system.

The complexity of the innovation process can best be defined by the fact that the team typically has no idea what the tasks should be at the beginning of the project.  This team is guided by an overarching goal, and needs to be flexible and creative enough to do whatever tasks are necessary to collect the information that will help to achieve it.  The fact that a set of tasks worked on the last project may be useful knowledge, but it is certainly not a roadmap for the next project which will have a different overarching goal.  For this reason it is difficult, if not impossible, to map a process step-by-step for a person outside the work process to plan, manage, and communicate.  Quality of work is evaluated on whether or not each person is able to construct logic and create solid rationale leading to recommendations, making sure to voice any logic breaches that come up so that the team can step back and address them.  Milestones are certainly helpful, but they are more useful for the team to structure their thinking, and less useful to determine tasks.  At the end of the day, it can be said that the purpose of the innovation processes is to ensure that intuitive leaps are made transparent, able to be evaluated, and that recommendations can be presented in such a way that the rest of the organization can make use of them.

Think about how your company's development and innovation processes.  Are they different?  Do they try to achieve different goals while using a similar process?

I've been reading several articles lately that discuss different processes for innovation.  They typically center around a few main themes; ethnography, rapid prototyping, open innovation, and other ways to connect market insight with opportunities for new offerings.  And yet when I talk with clients who have tried similar processes, I get mixed responses regarding the results.  Most can point to isolated events that would not have occurred without the new process, but none can say that these processes have increased their ability to consistently connect opportunities for new offerings with the market they are intended to satisfy. 

I'm actually not surprised when I hear this.  Over the past few years I've come to the realization that there is a big, pink elephant in the room regarding innovation processes.  That pink elephant is the fact that some people are better at making non-linear connections between disparate disciplines than others.  Why does this typically go unsaid?  Because the perceptual skills required to make these connections are difficult to identify, define, and measure, let alone codify into a bullet-point job description.  However, everyone perceives the world differently, and better descriptions of process will not turn a linear thinker into a non-linear thinker.

Think of it this way.  No one would argue that everyone has different levels of physical ability.  I can swim, but if I was standing next to Michael Phelps, we wouldn't need to be near the water for anyone to guess who could swim faster.  That's because physical differences are observable, definable, and we can easily measure the results of the output.  Differences in perceptual skill are invisible, but that doesn't mean they aren't real.  The problem is that most organizational processes have been designed to take the human variable out of the system.  In terms of development and other day-to-day processes I think this is a good thing.  But it just doesn't work for developing breakthrough innovations that will connect with the market.

In the next few posts, I'll be reviewing best practices I've developed to identify the right types of perceptual skills for innovation, and connecting them to different disciplinary skills.  For now, start noticing how different people in your company perceive the world around them.  You may be surprised at what you see when you really start looking.

Most organizations have mastered the ability to deliver their products and services reliably and efficiently.  Remember the 99% lists?  As consumers we've come to expect excellence, and companies that don't deliver above and beyond this excellence won't last very long.

Organizations themselves also take these skills for granted.  I'm often reminded of this when I'm working with clients to develop innovation processes.  Many of the people within companies become frustrated that the organization's capacity for change is so low. 

At this point, it's helpful to step back and really think about what your development and manufacturing processes are expected to do.  If you work in a business where 99.9% isn't good enough (most organizations), then expecting the current process to accomodate breakthrough innovation is just not realistic.  Alternatively, expecting that the outcome of the innovation process will be products and services that fit neatly into existing systems is equally unrealistic.  Innovation efforts that implicitly carry either of these expectations will most certainly fail.

Innovation processes require room for experimentation, trial and error, incorporating unpredictable human elements, and all the other things that would bring current development and manufacturing processes to a screeching halt.  It's far better to separate each process, and let each one be what it needs to be.  Your innovation process should result in the identification of new opportunities that can be delivered in multiple ways.  Some may be able to work with slight modifications to existing processes.  Others may require completely new processes. 

Your innovation process should deliver market relevant opportunities.  Your development and manufacturing processes should deliver offerings to the market reliably and efficiently.  The real organizational challenge is managing expectations within the organization for what each process should deliver, and establishing the right connections between them (more on how to do that later).  But don't expect one to deliver on the expectations of the other.