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?

This fall I'll be teaching a class at the business school at BU.  It should be an interesting experience, as the class emphasizes multidisciplinary product development.  This class has been offered for a while, so the materials are pretty well set.  I'm looking forward to collaborating with the other faculty members, as we each teach a section within a specific discipline, but the students' project needs to span the disciplines. 

I'll be teaching an Operations section, and what will be interesting is that I'll be able to focus on making the connections many clients have trouble with.  For example, if the students learn about market research in one class, they seldom learn how a consumer need could impact an internal, operational decision.  Making these connections will be fun, and I will be interested to explore the students' natural aptitude for making these types of connections.  I'm curious about whether or not people are more holistic thinkers naturally, and whether it's the corporate silo system that beats it out of them.  I'm also curious to know whether this type of thinking is hard-wired into some people, or whether it can be learned.  Of course I don't expect there to be black and white answers to these questions, but I will be curious about the trends.

A friend asked me what was the most important point I wanted to get across in the class.  From my perspective, I'd love for the students to understand that the tools and processes necessary to develop a product are not usually the best tools and processes to generate ideas for new products.  This is where I see many clients get into trouble.  I think the question comes down to whether or not you truly have the courage to start with the unknown, rather than an idea for a known, tangible product.  I'd also like to make sure they truly understand the difference between a product specification and the criteria for an offering that will be valued by the market.  Most people think these are the same, but they are very, very different.

I'm sure that by the end of the semester I'm sure my expectations will need to be reset in ways I can't imagine.  But now I just hope I can impart some wisdom beyond their textbook learning to help them to do more meaningful work.  I'd like to help them to be the type of employees that may not be described as the best behaved, but as the ones whose ideas actually work.

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?

There's no question that truly innovative people are creative.  But creativity alone is not enough.  True innovators, those people who can deliver new ideas and offerings that are relevant to the market, possess something in addition to creativity.  I've been doing a lot of work in this area lately, and will be working with PDMA and with a consortium at the Steven's Institute to help identify best practices and build a body of knowledge in this area, especially as it relates to enterpreneurship and new venture creation.

However, before we can build a credible body of knowledge in this area, we must first be able to identify what "it" is that successful innovators have that others - even highly creative people - may not have.  I've written about this briefly where I've metaphorically described this skill as the ability to make synesthesia-like connections between seemingly unrelated ideas or observations.  But ultimately, I think this is just one way to describe the way they perceive the world and make connections within it. 

What's interesting to me is that we currently don't have a good way to talk about the way people perceive relative to how it may help or hinder them in doing specific jobs.  Is there anything on your resume that talks about the way you perceive the world?  I would guess not.  And if there was, would it be even remotely helpful to the person reading your resume?  Again, probably not. And yet this is the one area where I see people either succeed or fail in their ability to perform as early stage entrepreneurs, investors, and innovation managers in large companies.

I'm also not sure if it's the actual perceptual skills that are different, or the way our brains process what we are perceiving.  For example, if a person who sees the similar in the dissimilar looks at a block of ice, a puddle of water, and a cloud of steam, they would describe them all as similar - they are all composed of H2O.  Others would look at the surface details and describe them as three different structures.  Is that perceiving, or processing?  I hope to collect different points of view on this question as part of the body of knowledge. 

What I do know now is that when you are assessing someone's ability to successfully innovate, it might be useful to stop and think about how they perceive the world.  Are they able to see similarities in dissimilar things?  Do the similarities make sense?  Is the person assessing them able to tell the difference?  As John Hagel states in many different ways in his blog, we are about to enter a Great Shift in how our world works.  It might be time to figure out how to define perceptual skills that could go easily unrecognized in the old economy, yet will be absolutely necessary for success in the new economy. 

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. 

A couple of months ago I was discussing models that help to think about focusing innovation efforts with Hutch Carpenter.  I said I would post one that I use, and Ooops!  I forgot to do that.  So here's a model that I often use when discussing the type of innovation capability a client wants to build.  My working definition of innovation is "doing something new that adds value to the business."  It's not just about making new products or technology.  For that reason, the people, processes and skills necessary to innovate can vary greatly, and we need to be very clear about what is necessary for each specific situation.

This model is based on two points that drive the approach to the innovation effort.  First, the degree to which the lines in each box are orderly or chaotic represents how well the end solution can be defined before the project starts.  Second, success criteria is determined differently at each innovation dimension. Let's look at how they differ.

Dimension 1 - I call this Innovation for Optimization.  The product or service that the company develops will stay the same, and innovation will focus on new ways to manufacture and deliver the offering to the market.  New technologies, processes, and organizational structures may be introduced.  Clear benchmarks for success exist, and the results can be tangibly measured with existing metrics.  The consumer will not notice a difference in the product or service, but may share in the benefits of the innovation through cost savings and ease of access to the product or service.  An example would be a new manufacturing technology that reduces production costs by 50%.

Dimension 2 - I call this Innovation for Improvement.  The goal is to improve the existing offerings themselves.  It may be that the product becomes easier to use, or new technologies will enable enhanced functionality.  In this dimension, success criteria may not exist already, and can be derived by learning directly from the market. It may involve learning what pain points the consumer has with existing products, or uncovering new uses that an upgrade can deliver.  An example would be the addition of calcium to an orange juice product.

Dimension 3 - I call this Innovation for Invention.  The goal is to develop new products and services that will provide the same benefits as existing options, but in new and better ways.  In this dimension, success criteria for the specific product attributes does not exist, and consumers may not be able to articulate the potential solutions. However, the benefits are well recognized. An example would be new products that increase the ease of eating yogurt on the go.  A yogurt company may develop new technologies or formulations to enable drinkable yogurt or yogurt in a tube. New internal benchmarks for manufacturing and cost structures may need to be created, as the company is making different products.

Dimension 4 - I call this Innovation for Disruption.  The result of this type of innovation is that it fundamentally changes the competitive landscape.  Very often - but not always, this type of innovation focuses more on changing existing business models than on changing the products themselves.  We can see this type of innovation playing out in the publishing and other media industries, as existing business models are becoming irrelevant.  New products and technologies play a part, but they are enablers that allow consumers to access media more easily and inexpensively than ever before.  The sources of power are shifting in the market, and existing benchmarks become irrelevant. Consumer research is very important here, but as a source of information about what is valued, not as a source of solutions as in dimension 2.

Since my work involves ensuring that new offerings are relevant to the market, the focus is from the perspective of how the consumer (or other end-user) will perceive the differences.  It also sets the stage for how directly the consumer can give input to what the end result will be, and guides the type of work we need to do.  From my experience, most companies are very good at Optimization, and they can often stretch to create innovative improvements.  This work can be handled in existing development processes.  In future posts, I will describe the fundamental difference in the work necessary to innovate in the 3rd and 4th dimensions, as this is where the existing development processes typically break down.

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.

Last night I attended a panel discussion on Smart Medical Devices, put on by the Biomedical Engineering Society.  There was a lot of discussion about the definition of Smart Devices, new technologies (which were very impressive), and ultimately the discussion found its way to pointing out the need for biomedical engineers to act as translators between the engineering and medical communities.

Sound familiar?  This is exactly the type of discussion that goes on in design thinking circles. Just as it's important for designers to understand human needs to design better products, the same is true for designers and engineers who need to understand clinical needs to develop better products and to guide technology development.  What I truly appreciated was the engineers' description of translation.  This is much less confusing than the thought process of a specific discipline.

This should not be surprising. What struck me, however, was the fact that this capability was discussed as something that was necessary, but the problem was in finding engineers who were interested in spending time in the field.  It was suggested that typical engineers would rather develop cool new technologies, and weren't as interested in solving problems in a low-tech way.

In my work, I have never encountered a designer, engineer, or marketing person who was unhappy that I was able to identify the problem that needed to be solved, and present it as criteria that was relevant to them.  However, I have often found that most designers, engineers, and marketing people who work in development processes are much more interested in solving problems than in identifying them.  My main takeaway from this event is that there is a burgeoning frustration with people trying to solve their way to problem identification.  It just doesn't work. 

As I've discussed in many previous posts, problem-solving and problem-posing are very different activities and require different skills.  It's unrealistic to expect a doctor to define the engineering challenge, just as it is to expect the consumer to define your new product breakthrough.  Problem-posers have developed the skill to discern the motivation behind what is said, regardless of what market you are in.  Last night's discussion was yet another highlight of the same issue.