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?

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. 

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.

Of course your company isn't running a casino on purpose. But is it running one accidentally? You can tell based on its approach to innovation investment.

Does your company solicit new ideas for products and technologies in a more random fashion, investing in those that either can be executed with current resources, or do not pose much risk to the status quo?  Do people know the success criteria for a breakthrough idea?  In other words, is there a way to tell if a new offering with no current benchmarks is likely to succeed?  Usually the answer is no.

Does this sound familiar?  If it does, then your company probably casts a wide net in terms of investing in innovation.  Since most ideas are likely to fail, it's better to invest in more, and more varied, options to hedge your bets.  Notice I said bets, because that's exactly what the organization is doing.  The innovation process is essentially providing a mechanism to place bets knowing that most will lose, and hoping that the one(s) that succeed will cover the losses.  Isn't that what happens in a casino?  It provides a place for people to come and place many bets, hoping that a few wins will cover the losses.

On the other hand, does your company understand its market, define new opportunities to better meet the market's needs, and develop technologies that enable new products and services to satisfy those opportunities?  This may not be nearly as sexy an option at first glance, however it does provide a way to tell if radical new ideas have a chance of succeeding before investin in their development.  The chance of failure in developing something truly new and different is greatly mitigated. This is the difference between investing and betting.

In a real casino, the house always wins when most bets are lost.  In a real company, the only way the house always wins is to ensure success.  So why are most companies pursuing the casino model?

It's funny how the planets sometimes align around a topic.  This week it's the chicken and the egg question regarding technology and consumer research. 

It all started last week when I was talking with a friend from a local technology start-up about the need to understand consumer (or other end-user in B2B situations) motivations in order to ensure the relevance of new product offerings.  Then today I saw two interesting posts that essentially dance around the same question; when developing breakthrough innovation, which comes first?  The first post is from Don Norman, and suggests that historically breakthrough innovations begin with technology, and that what he's calling design research to uncover unmet needs is only useful in developing incremental improvements.  The second post is from Roy Luebke and is a response to Norman's post, suggesting that design (observational) research can point to all types of innovations.

What was interesting was that I was able to agree and disagree with both of them, based on a) how narrowly or broadly consumer research is defined, and b) the expectations for what either research or technology will deliver.  Let's look at both.

First, Norman describes the tasks of design research, and points to the fact that pure technological invention was what drove the creation of many inventions from the airplane to text messaging.  And I would say that taken literally, he is correct.  If you've been reading this blog for a while, you know that I view contextual research as a source of information, not answers.  (I use the term contextual research because it does not focus the outcomes too narrowly.) And consumers could never be expected to come up with such breakthrough inventions as the ones he describes.  When viewing contextual research as a source for answers, the most you can expect is a good list of improvements to existing products.

Second, Norman then points out that it is technological invention that is the source of breakthrough innovation.  Again, he is right in that the inventions he described would not be possible without new technology.  However, they would not be successful if they didn't satisfy a consumer motivation.  In reality, consumers rarely change their behavior to accomodate technology.  They adopt when the technology is put into a form that seamlessly fits into their lives.  All of the inventions on Norman's list enable consumers to do something they already wanted to do (travel, communicate, etc), but in a better, faster, less expensive, etc way. Knowing the motivation ahead of time can save a lot of time and money, as well as help a company to define what business they are really in.

In that sense, Norman's post appears to be based on the idea that the consumer will give you the answer, and that after the technology is developed product success is hit or miss.  I would have to disagree with both of those assumptions.

On the other hand, Luebke acknowledges that learning from consumers can point to many different types of innovation.  That is true, but he doesn't comment on the fact that contextual research should be tailored to collecting the information that will inform the decision that needs to be made.  For example, a consumer can be asked directly to evaluate current product features.  Understanding their motivations, however, is what is necessary to guide the development of new products and services they would never think to ask for.  This is the type of constraint inventors typically love to solve with new technology.  This is how learning from consumers can drive technology development - it provides a purpose, not a directive.  This is where research and invention come together.

Ultimately it doesn't matter whether we are starting with a technology or a market segment.  Technology can certainly enable the creation of totally new products and services.  But these new products and services will not succeed unless they satisfy the market's motivations better than existing alternatives.

Last year, I wrote a post about Design Thinking in response to an article in Brandweek that I felt was misleading on the topic. In it, I pointed to Roger Martin's work as some of the very best at describing what Design Thinking actually means. Last week I got into a Twitter discussion with Steve Finikiotis after he pointed me to a Harvard Business Ideacast featuring Roger and his ideas on Design Thinking.  I agree with Roger's views, however I have noticed some unintended consequences as the terms are put into practice. I boiled down these issues to three main points that I would like to discuss.  

First, I philosophically agree with Roger regarding the need for contextual research, abductive reasoning, and problem posing.  However, what I find in practice is that the term Design Thinking can be potentially problematic in its interpretation. This is because design is a functional discipline in most organizations, just like marketing, engineering, or finance. Most design education focuses on teaching the fundamentals of honing the craft and developing tangible design skills.  The work Roger describes of creating plausible hypotheses and solutions based on contextual research is often done by people who do not have traditional design backgrounds.  As a result, I have seen the term create some organizational confusion regarding work that I have found to be discipline agnostic. 

My second point is related to the first. Roger talks about how designers and business people need each other in a way that should break down silos to allow the necessary connections between their disciplines to be made. Again, I agree wholeheartedly, yet in practice, the term Design Thinking can cause the unintended consequence within an organization to segregate, rather then integrate the disciplines.  Richard Farson, a psychologist who has written quite a bit about design, discusses the need to focus on the "meta" level of all functional disciplines as a way to rise above the executional level within a functional discipline and frame the common problem at hand. When I've presented the "meta" idea to client organizations, it tends to help to philosophically integrate the disciplines within a team, and resolve the terminology issue.  It is something to think about.

Finally, Roger very eloquently speaks of the need to integrate creative and analytical thought. (see abductive and adductive reasoning) Amen to that! However, I find the integration of these two types of reasoning to get us part of the way there, but in order to accurately connect seemingly unrelated concepts we need a different type of cognitive skill.  For example, we certainly need to integrate creative and analytical reasoning to hypothesize a consumer's motivation behind what they say, and to develop new solutions to satisfy those motivations.  However, the ability to accurately translate from a specific plausible hypothesis to a related plausible solution appears to be a different type of cognitive skill that is employed in addition to the integration of the types of reasoning. In the work I've been doing, we're just beginning to scratch the surface of what that is. When I have something concrete, I'll be sure to share it.

I'll end by saying that I'm certainly not intending to criticize Roger Martin's work. On the contrary, from what I've seen he has done a better job than anyone in terms of creating awareness of the need to integrate creative and analytical thought processes and solutions. For that, he has earned my heartfelt gratitude. However, we cannot expect him to do everything alone, or to have every answer.  It is our responsibility as practitioners to raise the issue when we sense inconsistency between theory and practice, and continue to work together to hone these concepts.

It's no secret that I believe that the ability to translate market needs into viable offerings that meet those needs is the key to successful innovation.  It's also no secret that I believe that this ability does not reside in any one discipline, educational background, or company process.  Last year I wrote three posts, each about an element of translation that I felt was important for an organization to embrace the capability. The three elements were Awareness, Capability, and Evaluation.

I still believe that these three elements are necessary for an organization to embrace translation, and I have been focusing on what it would take to actually recognize and build it.  In the post about having the capability to translate, I ask the question about whether or not the organization has the right people to perform this task.  This past year, I have been trying to put my finger on what exactly it is that a person who is good at translating is actually doing?  What skills do they posses?  Is it learned?  If so, then how do you teach someone, and by extension an organization, to make accurate connections between seemingly unrelated ideas, disciplines, process phases, or stakeholder needs?  Is it innate?  If so, then how do you teach an organization to recognize these skills, accept the differences, and embrace the outcomes?

Where I have landed is that everyone can learn better techniques and processes such as deriving motivations from contextual research, or evaluating intangible attributes.  However, even with the best techniques and processes, some people are able to make these connections, and others are not.  Once that pink elephant in the room was called out, the rest became more clear.  It gave me a different perspective on process, and has allowed me to continue to hone my best practices in identifying these people because these skills don't fit on current HR checklists.

Some people may not like this conclusion, but it's really no different than recognizing that people possess different physical abilities that make them better than others at physical tasks, so why wouldn't different mental abilities exist as well?  An exploration into the field of perceptual psychology has shed some light on this subject for me as well, especially when we look at recent research into synesthesia. 

Synesthesia is a perceptual experience, where some type of sensory crossover takes place.  For example, a person with synesthesia may hear sounds when they see certain colors, or they may experience a smell when they come in contact with certain textures.  Historically, synesthesia has been confined to describing specific sensory crossovers that are not experienced by the general population.  Recent research by experts in synesthetic perception, has broadened the understanding of what goes on in our brains as we perceive the world around us.  He has found that cross-sensory mapping is happening all the time, to the point that we take it for granted.  For example, dancing is a kinetic response to sound stimulus; a cross-sensory mapping ability that goes unquestioned by the general public.  They suggest that we only notice when people perceive sensory crossovers that are not commonly experienced by the average person.  It sticks out when someone sees a color and hears a sound, but we don’t find it odd that a person may hear a sound, and move their body in a way that mimics the rhythm of the sound.

The newest thinking actually goes so far as to define synesthesia as a consciously elevated form of the perception that everyone already has.  Just as people have varying degrees of physical abilities, it makes sense that varying degrees of perceptual abilities exist as well.  It therefore also makes sense that some people are naturally better at perceiving one type of input, such as consumer motivation, and mapping it to a seemingly disconnected output, such as an offering toward which the consumer will respond positively.  To put it bluntly, some people are better at making the connections necessary to create successful, market relevant innovation, and this skill is independent of which discipline they choose to study.

So what does this mean for translation ability?  Is it a form of synesthesia?  A form of creativity?  Much more work needs to be done before we will know for sure.  What is important is that we are beginning to develop models that support the idea that getting the right people in place to focus on innovation is an important first step.  We can then develop systems and processes to support them, rather than take the place of the human element.

A few posts ago, I talked about how an organization's development and innovation processes should be different, as they have different goals.  I then talked about how differences in perceptual skills are better determinants of successfull innovators than the organizational discipline in which they reside.  At this point it may be useful to step back and look at the fundamental differences in the thought processes that enable people to be successful in the development and innovation processes.

As the development process requires a high degree of reliability and certainty, thought processes that involve inductive and deductive reasoning are most appropriate.  Inductive reasoning determines rules by moving from specifics to generalities.  For example, if every time we touch ice it is cold, we can then make a rule that all ice is cold.  Deductive reasoning determines conclusions by moving from generalities to specifics.  For example, if we know that all ice is cold and we are told that an object is made of ice, we conclude that the object will be cold.  Both of these types of reasoning work hand-in--hand, and can be proven or disproven by observing or experiencing additional examples.

In contrast, the innovation process requires the creation of highly plausible hypotheses and solutions that are not readily observed or experienced - at least not in the current context.  The thought processes most applicable in these circumstances are abductive and adductive reasoning.  These types of reasoning require that intuition and creativity are applied to observed and experienced facts.

Abductive reasoning determines plausible hypotheses.  For example, abductive reasoning would be used to determine hypotheses for why ice would be cold.  Further investigation beyond external observation would be required to prove or disprove each hypothesis proposed.  Adductive reasoning determines plausible solutions.  For example, depending upon why ice is cold, we may develop new solutions for how to make ice.  Each solution would need to be tested through experimentation.  Both of these types of reasoning also work hand-in-hand.

We can see how different types of reasoning are applicable in different situations.  We can also see how different types of reasoning are important in any functional discipline in an organization.  Both innovation and development groups need multidisciplinary teams. When selecting people to work in either group, it's much more important to assess how they approach identifying and solving problems than which discipline they come from.