Innovating in Your Dream and With a Drink

There are a few reported approaches to boosting human creativity.

Some of them are very proper. Perhaps the most popular is taking a shower — especially if followed by going to the garden and sitting under the apple tree. Another is practicing mindfulness meditation, an action 10-12 minutes of which are claimed enough not only to reduce stress but also generate better solutions to creative problems.

Other approaches may carry a stigma with them. For example, it was reported that moderate procrastination may lead to higher creativity ratings in test subjects. The authors of the study speculate that procrastination can set in motion a mechanism of problem restructuring, which results in the production of more creative ideas.  

Procrastination is generally frowned upon in the marketplace. But in its defense, I will say that the average productivity of American workers has increased 400% since 1950; yet we’re working the same 40-hour workweek, at least on paper. Don’t we have a right to treat our brain to an occasional spell of a quiet, unrushed deliberation?

And how can we justify, on the moral ground, the fact that human creativity can be stimulated by the consumption of moderate amounts of alcohol (resulting in a blood alcohol content of approximately .075, i.e., just below the U.S. legal limit)? The authors of the respective study hypothesize that people under the influence are more susceptible to so-called mind wandering, which means losing some focus but gaining the ability to see a “bigger picture.”

As I argued before, in contrast to many narcotics or drugs, ethyl alcohol is a simple chemical molecule, whose behavior in the human body is quite well understood. Using this relatively simple model, researchers may start identifying specific neurochemical reactions in the brain that are responsible for creativity.

Recently, a new entry has been added to the list of factors boosting creativity: an interrupted nap. When people fall asleep, they first go through the nonrapid eye movement sleep stage (or N1), often described as “the twilight zone between sleep and wakefulness.” A group of French researchers showed that spending at least 15 seconds in N1 — and then being awakened — boosted the creativity of test subjects: they were significantly more likely to find a creative solution to a math problem than test subjects who proceeded past N1 without awakening or those who didn’t fall to sleep at all.

I strongly suspect that the positive effect of mindfulness meditation is realized through the same, N1-dependent, mechanism. I also suspect that alcohol stimulates creativity by chemically “firing up” the same brain structures that get activated during N1.

It’s only a matter of time that researchers identify the sections of the brain responsible for creativity — along with safe and efficient ways to stimulate them on demand. And we all will have a choice regarding how we prefer to innovate: in our sleep or with a drink.

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How to Build Your Innovation Dream Team (Part 2)

In Part 1, I described two potential approaches to building a corporate innovation team. One emphasizes specific individual skills of team members, the other focuses on the optimal mix of functional roles within the team.

There is the third approach to the formation of innovation teams. This approach doesn’t pay attention to the team composition or individual skills of its members; it emphasizes the way the team operates.

The logic behind this approach was eloquently articulated in a 2015 article by Google’s Julia Rozovsky. The article argues that the composition of a team matters much less for its success than how the team members interact, structure their work, and view their contribution. The article listed five key factors that set apart successful Google teams:

  • Psychological safety: team members taking risks without feeling insecure or embarrassed.
  • Dependability: team members counting on each other to do high-quality work.
  • Structure & clarity: teams having clear goals, roles, and execution plans for each member.
  • Meaning of work: team members working on something that is personally important for them.
  • Impact of work: team members believing that their work matters.

Interestingly, it’s the first factor, psychological safety, that was by far the most important of the five. The safer team members felt with one another, the more likely they were to admit mistakes, work together, and take on new roles. The results followed.

The notion that innovation requires taking risks without fear of negative career repercussions is hardly new. We often hear calls to “fail fast and often” — or even to celebrate failures — as a surrogate invitation to innovate.

Unfortunately, while voiceful in promoting risk-taking, experimentation, and learning from mistakes, firms fail to introduce specific corporate policies encouraging and rewarding such behavior of their employees.

What can be done (or at least tried)?

Based on my research of factors favoring innovation, I’d like to propose a few recommendations on building corporate innovation teams

1. Create a brand-new team for each strategic innovation project and adopt a modular approach to the formation of innovation teams.

To avoid groupthink within innovation teams, I recommend creating a brand-new team for each strategic innovation project. This may result in a slow start of the project, due to the frictions between members of the team; however, the benefits of the cognitive diversity brought by new members should eventually overweight the cost of the initial delay.

I further recommend that each innovation team include a few members of the core innovation team (thoroughly trained in innovation management tools) and several outsiders from different units, functions, and locations. Naturally, this modular approach requires the creation of a firm-wide repository of employees with a track record of their prior involvement in innovation activities. Ideally, at some point, this repository will start collecting data allowing to judge the innovation skillsets of prospective members of the team and their optimal functional roles within the team.

2. When creating innovation teams, use a mix of subject-matter experts in the project’s domain and non-experts in this specific innovation field.

This recommendation takes a cue from a 2016 study that showed that the high ratio of domain experts on corporate boards resulted in poor performance of respective firms. The major problem with having too many domain experts on the board was “cognitive entrenchment,” the inability of expert-dominated boards to effectively respond to new information, especially when faced with an increased level of uncertainty. (And an increased level of uncertainty is what innovation is all about!) Sure, the optimal ratio of SMEs vs. non-experts needs to be determined empirically, but for longer-term projects, it can be adjusted midway.

3. When creating an innovation team for consumer-oriented projects, include team members with demographic characteristics mirroring the ones of the prospective end users.

This recommendation is inspired by a 2013 report by the Center of Talent Innovation that found that when innovation teams had one or more members of the same gender, ethnicity, culture, age, or sexual orientation as the project’s target end user, the entire team was far more likely to understand this user’s needs, increasing the likelihood of innovating more effectively.

4. Place members of the innovation team especially those involved in strategic innovation projects on fixed-term (tenure-like) employment contracts, as opposed to employment-at-will. 

This proposal is based on multiple studies (reviewed here) showing that the labor laws that make it more difficult to fire employees increase their participation in corporate innovation activities. The idea here is to provide members of the innovation team with immunity for failure for the whole duration of the innovation project, a bureaucratic equivalent of giving them psychological safety.

5. Make stock option grants, as opposed to cash bonuses and other monetary or non-monetary rewards, the principal incentive for engaging employees in innovation projects. 

This proposal is based on a 2015 finding that firms that offer stock options to non-executive employees are more innovative. This proposal, as the previous one, is based on a theoretical framework created by Gustavo Manso, who postulated that the optimal incentives motivating employees to innovate must include a combination of tolerance for failures in the short term and reward for success in the long term.

Of course, there is no guarantee that any of the proposed recommendations, especially taken alone, would result in immediate positive outcomes. But if you believe, as I do, in the importance of experimenting, then experimenting with the way you build your innovation team is a good place to start. 

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How to Build Your Innovation Dream Team (Part 1)

Do you agree that to pursue a corporate innovation project, you need a dedicated innovation team?

Maybe not. We often hear that “innovation is everyone’s job” along with arguments that any structure kills creativity and stifles innovation.

Why is the idea that “innovation is everyone’s job” still alive and well in many companies? (I happened to work for one.)

Because this allows corporate leadership to adopt a hands-off approach to innovation.

No need to formulate the company’s innovation strategy and identify key business problems to solve. No need to design and implement specific innovation programs. No need to create a reward and recognition system that would incentivize employees’ engagement in innovation activities.

Instead, you just announce an open season for “ideas,” launch an innovation hackathon or two, and then claim that the collective wisdom of the whole company has been harnessed. (Ironically, helping this hands-off approach to innovation thrive is the proliferation of innovation management software.)

Fortunately, more and more corporate leaders begin to understand the need and the value of creating a dedicated innovation team. Of course, every employee should ideally take part in innovation projects, but it’s the ultimate responsibility of the innovation team to take ownership of the whole process. Anyone with even a passing knowledge of how corporations work knows that when everyone is responsible for something, no one is.

Let’s leapfrog?

And here we reach a crucial question: how should this innovation team be formed?

Several approaches exist.

The first emphasizes the personal skills of the team members. That’s why you can hear that the best way to staff your innovation team is to hire…innovative people. Great advice, of course, but unfortunately, with a limited practical value.

This is not to say, however, that more specific recommendations are completely lacking. Soren Kaplan, for example, suggests looking for these five qualities when recruiting new hires:

  • Leapfrogging mindset: a desire to view the world with the goal of changing it.
  • Complementary knowledge: possessing the knowledge and expertise that is complementary to yours.
  • Strategic relationships: bringing along a strong network of business partners.
  • Ambiguity tolerance: the ability to make decisions based on limited data.
  • Optimistic persistence: the ability to persist through the tough times.

I like these suggestions. But I suspect that most corporate HR departments, even equipped with advanced evaluation tests, will have trouble with finding enough candidates meeting such a high standard.

When a revolutionary meets a magic maker

Instead of paying attention to the skill sets of individual team members, the second approach emphasizes the need for their optimal mix. This approach specifically focuses on the functional roles each member of the team plays in the project. For example, Braden Kelley suggested that each innovation team should include nine innovation roles including these five:

  • Revolutionary: a team member generating and sharing ideas.
  • Connector: a team member bringing people together.
  • Customer Champion: a team member responsible for interactions with customers.
  • Magic Maker: a team member responsible for implementing novel ideas and solutions.
  • Evangelist: a team member creating a buzz about the project and its results within the organization.

(The other four roles are Conscript, Artist, Troubleshooter and Judge.)

This approach is obviously more practical than the first. In fact, some firms have already adopted the spirit, if not the exact letter, of it by creating innovation joint task forces composed of representatives from different corporate units and functions: R&D, sales and marketing, customer service, finance, legal, etc.

Implicit in the formation of an innovation team composed of people from different corporate walks of life is a belief that this team can only be successful if it includes people with diverse professional expertise and experience.

In recent years, this concept of functional diversity was augmented by a growing body of evidence suggesting that socially diverse groups (i.e., those with a diversity of gender, race, ethnicity, and sexual orientation) are more innovative than socially homogeneous groups.

Research shows that socially diverse groups are better at solving complex problems not only because people with different backgrounds bring new information, but also because the mere presence of individuals with alternative viewpoints forces group members to work harder to sharpen their own arguments.

This is good news for HR managers in charge of creating innovation teams: in our rapidly globalizing workforce environment, bringing together people with diverse professional and social attributes is much easier than identifying individuals with a leapfrogging mindset or optimistic persistence.

It’s all about the process

There is the third approach to the formation of innovation teams. This approach doesn’t pay attention to the team composition or individual skills of its members; it emphasizes the way the team operates.

I’ll describe this approach in Part 2.

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Are You Free to Innovate?

My search for factors advancing corporate innovation has led me to a somewhat unexpected conclusion: to innovate, you need freedom.

This freedom can be realized at three major levels. The first level is individual, manifested as freedom from being discriminated against for whatever reason. Organizations can realize this freedom by promoting diversity and inclusion.

The second level is organizational, realized as providing corporate employees with immunity for failed innovation projects. Organizations can do this by modifying their termination policies.

Do You Live in a Free Country?

There is one more level of freedom, which almost never receives proper attention: the level of political freedoms in individual countries.

I first came across this point in 2014 while reviewing the 2013 Global Innovation Index. The Index ranks innovation capabilities of the world’s nations by using 84 indicators, which include the quality of higher education, availability of venture capital, government support, etc.

Even a brief look at the Index led me to a curious observation: the top of the innovation ranking was heavily populated by established democracies (as defined by the 2013 Freedom of the World Report). The reverse was also true: the bottom of the Index was stacked with countries with an extremely low level of democratic development.

Later, I attempted to boost this observation with some statistical support. I took innovation rankings from the 2019 Global Innovation Index (Y-axis) and plotted them against the rankings of political freedoms from the Democracy Index 2019 (X-axis). Here is the result:

Indeed, a reasonably strong correlation (R2=0.46) exists between the world countries’ innovation potential and the level of their democratic development. Free countries innovate better.

What About Economic Freedoms?

Recently, I came across the 2021 Index of Economic Freedom composed by the Heritage Foundation. The Index evaluates the extent and effectiveness of government activities in areas known to have an impact on economic growth:

  • Property rights and judicial effectiveness
  • Government integrity and the level of corruption
  • Tax burden
  • Government spending and fiscal health
  • Business and labor freedoms
  • Financial and monetary freedoms
  • Foreign trade and investment freedoms

Of course, it was tempting to see to which extent economic freedoms correlate with the innovation potential. For this purpose, I used data from the 2021 edition of the Global Innovation Index (Y-axis) and plotted it against the rankings taken from the 2021 Index of Economic Freedom (X-axis). The results for 129 countries for which both sets of data are available are presented below:

Like with political freedoms, a country’s innovation potential strongly correlates with the level of its economic freedoms.

The State of the United States’ Innovation

At first glance, the state of the United States’ innovation is bright: over the past three years, the country has consistently held the third-highest position in the Global Innovation Index (all three years following Switzerland and Sweden).

However, clouds might be gathering on the horizon. The 2021 Index of Economic Freedom places the United States only at the 20th position, of a total of 178, in the rankings (in the category of “mostly free” countries). Even among the Americas nations, Canada and Chile score higher.

The state of political freedoms appears to be trending in the wrong direction. Until 2015, the Democracy Index has defined the United States as a “full democracy.” In 2016, for the first time, the country was classified as a “flawed democracy”; its rankings have been gradually sliding down ever since. Freedom House, non-profit advocacy on democracy, political freedom, and human rights, points in its 2021 report that the United States finds itself among 25 world’s countries with the largest decline in freedom and democracy over the past 10 years.

True, the United States still spends a lot of money on R&D—more than any other country in the world—a factor that may explain the stability of its innovation ratings. However, as I pointed out before, only about 30% of this money comes from the federal government, whereas 70% of it is contributed by the private sector. In the long run, this may jeopardize investments into fundamental but potentially risky R&D projects.

Another concern is the growing mistrust in science among Americans; some egregious examples of this mistrust have been on display during the ongoing COVID-19 pandemic. Research shows that mistrust in science often manifests as unwillingness to support it. Taking to the extreme, this sentiment may result in attempts to “defund” science both at the state and, worse, federal level.

Finally, a development to watch is a possibility that some 20 states may soon essentially ban all or nearly all abortions, a social policy shown to negatively affect innovation at the state level.

Innovation has been the driving force of American growth and prosperity—and, as such, a key component of the nation’s psyche. And yet, given current trends, the American innovation edge can’t be taken for granted. Losing it will have consequences we Americans don’t even want to contemplate.

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Location (Location, Location) and Innovation

In my previous post, I discussed evidence indicating that liberal social policies make U.S. states implementing them more innovative.

If so, one would expect that liberal U.S. states are in general more innovative than conservative.

To see if there is any empirical support to this assertion, I plotted a measure of the innovative potential of all 50 U.S. states and the District of Columbia against an estimate of their liberalism or conservatism. 

As a measure of innovation at the state level, I used the 2021 WalletHub State Innovation Index, a set of 22 indicators of innovation-friendliness.

As a measure of ideological orientation, I used a parameter Gallup calls “liberal advantage.” It derives from the 2018 Gallup’s tracking poll in which respondents in all U.S. states were asked to describe their political views as liberal, moderate, or conservative. The liberal advantage is the percentage of people self-identified as a liberal minus the percentage of people self-identified as conservative.

By this measure, the most liberal U.S. state is Massachusetts (liberal advantage +14) while the most conservative is Mississippi (liberal advantage -38).

The results are shown below:

Indeed, there is a reasonably strong correlation (R2=0.44) between the liberal or conservative sentiments in each state and the innovation potential of this state. Liberal states are in general more innovative.

I must emphasize that the above graph suggests only correlation; more data is needed to prove causation, i.e., that it’s the states’ political orientation and not something else, e.g., the amount of money allocated to R&D, that accounts for the lower innovative potential.

And yet, policymakers would be wise to consider state social policies when discussing an investment of federal money into regional innovation projects.

I’d also like to draw attention to one of my previous posts discussing evidence that the ability of a country to innovate correlates with the level of political freedoms in this country.

Remember your real-estate broker’s mantra: location, location, location?

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What Can Social Policies Do to Innovation?

Like it or not, government socioeconomic policies influence innovation.

Some of them, e.g., R&D tax credits and innovation grants, do that in a positive way. Others, such as the notorious Prohibition of 1920-1933, deeply damaged U.S. innovation.

Traditionally the bulk of attention is focused on economic policies while the importance of the social aspect is usually overlooked.

This should change: the growing body of data suggests that social policies implemented at both federal and state levels can have a profound effect on the innovation process.

The Liberalization Premium

Solid support to the above statement comes from the 2018 study by Keyvan Vakili and Laurina Zhang. Vakili and Zhang analyzed the impact of two social liberalization policies — the legalization of same-sex marriages and medical marijuana — on patenting rates across U.S. states.

During the period covered in the study, 1990-2007, six states and the District of Columbia legalized same-sex marriages (unions or domestic partnerships before 2004), and 11 states legalized medical marijuana.

Vakili and Zhang found that starting 2-3 years post-implementation, both policies led to increased state-level patenting. The increase was by 5% for same-sex marriages and 6% for medical marijuana.

The authors presented data suggesting that the introduction of liberal policies in the affected states influenced innovation through shifting public opinions to a more open and inclusive status. Consequently, that led to the formation of new collaborations composed of individuals with more diverse backgrounds.

Vakili and Zhang also found that many patents filed after the implementation of both policies were drawn upon novel technological cross-pollination, which resulted in these patents being more original and impactful.

Vakiri and Zhang’s results shouldn’t come as a total surprise. There is enough anecdotal evidence pointing to a correlation between liberal social policies and the innovation potential of a given U.S. state. For example, one of the most innovative states, Massachusetts, was the first in the country to legalize same-sex marriages in 2004.

The Anti-Liberalization Penalty

Vakili and Zhang also analyzed the effect of one anti-liberalization policy: abortion restrictions. In 1990-2007, 34 states have passed at least one new abortion restriction, ranging from extended waiting periods, mandatory counseling, and limitations in insurance coverage to near-total abortion bans.

The passing of one additional abortion restriction reduced patenting by 1%, which roughly translates to about 21 fewer patents per year at the state level.

Such a modest reduction may not sound like a big deal. And yet, it shouldn’t be taken lightly given the changing abortion law landscape in the United States. It’s quite possible that 22 states may soon not just restrict the access to abortions further but essentially ban all or nearly all of them.

The results of these actions on innovation output in affected states are difficult to calculate.

The Regional Growth Center Angle

The above results strongly suggest that social policies influence innovation at the state level and can create a regional advantage — or disadvantage.

This is especially relevant given the idea to create eight to 10 regional growth centers in the Midwest metro areas of the United States. Central to the idea is the infusion of about $100 billion of federal money over the next 10 years in the form of direct R&D funding, tax and regulatory benefits, and infrastructure support.

Interestingly, many of these prospective growth centers are located in the states that are planning to implement the most restrictive abortion laws.

Policymakers would be wise to take this aspect into account when calculating the potential innovation outcome of this massive investment of federal money.

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Innovation do’s and don’ts

Jeff Bezos once said: “Good intentions don’t work, mechanisms do.” I interpret this line as implicit support for my conviction that chasing the chimera of “culture of innovation” is a distraction, rather than an enabler, of corporate innovation.

Instead, firms should start identifying and implementing specific and actionable corporate policies boosting innovation.

Over the past few years, I’ve been looking for socio-economic factors favoring or obstructing corporate innovation. This post summarizes some of my findings.

I based my search on a theoretical framework created by Gustavo Manso in 2011.

Manso postulated that the optimal incentives motivating employees to innovate must include a combination of tolerance for failures in the short term and reward for success in the long term.

Tolerance for early failures allows the employees to take risks at the initial stages of the innovation process without incurring the negative consequences of failed projects.

The reward for long-term success encourages the employees to explore risky ideas that may allow them to achieve innovation breakthroughs in the more distant future.

Below, I’m listing some factors that I’ve identified in the literature organized into two groups: innovation do’s and innovation don’ts.  

Innovation do’s

Innovation don’ts

Admittedly, many of the factors listed above, such as employment or abortion laws, are largely out of corporate control.

Yet, firms might consider local bankruptcy codes when choosing the location of their innovation centers. And startups ought to be aware of the risk-tolerance level of VC investors they choose to work with.

Besides, firms may boost corporate innovation by modifying their termination and compensation policies, something that is entirely under their control. Here, I propose two specific recommendations:

  1. Placing employees involved in strategic innovation projects on fixed-term employment contracts (as opposed to employment-at-will). Alternatively, tenure-like positions may be created for the same employees. Whatever the arrangement, the employees should be assured that they have a fixed “window of opportunities”—say, three to five years—to make progress before any administrative decisions regarding their employment will be considered.
  2. Making stock option grants the principal incentive for engagement in innovation projects–as opposed to cash bonuses or non-monetary rewards.

A larger point that I’d like to make is that we must finally move from words to corporate deeds when dealing with innovation. Implementing specific corporate policies is a much better way to boost innovation than wasting time on “innovation theater.”

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3 Ways to Boost Innovation through Diversity

Have you ever heard about Employment Nondiscrimination Acts (ENDAs)?

I suppose not. An obscure and boring subject. And yet, you might be surprised to learn that ENDAs, the U.S. state-level laws that prohibit discrimination based on sexual and gender identities, boost corporate innovation.

A 2016 study found that U.S. public companies headquartered in states that have passed ENDAs experienced an 8% increase in the number of patents (and an 11% increase in their quality) relative to the companies headquartered in states without ENDAs.

The result was more pronounced for states with a large LGBTQ population and for firms in human capital-intensive industries, such as technology and finance.

I know of no data suggesting that the LGBTQ folks are intrinsically more innovative. Rather, the above study implies that innovation requires a certain degree of individual freedom, including the freedom to live and work openly and safely without being discriminated against for whatever reason.

Diversity Boosts Innovation and Performance

So here is a point: having a diverse and inclusive workforce that reflects our rapidly changing society is not only the ethical and socially responsible thing to do; it is also good for firms’ bottom lines.

Consider this:

  • Boston Consulting Group surveyed the innovative potential of 1,700 American firms and found that firms with above-average diversity produced a greater proportion of revenue from innovation (45%) than firms with below-average diversity (26%).
  • A study of 4,300 Spanish companies revealed a positive correlation between the number women these companies had on staff and their ability to introduce innovations into the marketplace.
  • Another study of 7,600 U.K.-based companies demonstrated that firms run by culturally diverse leadership teams were more likely to develop new products than those with homogeneous leadership.
  • A 2013 report by the Center of Talent Innovation showed that having a member of innovation team of the same ethnicity as a client dramatically increased the team’s ability to understand the client’s needs, a factor that could make the difference between winning and losing a new business.
  • Credit Suisse Research Institute found that firms with one or more woman board members had a higher average ROI and better average growth than firms with male-only boards.
  • Analysis of executive teams in more than 1,000 firms across 12 countries performed by McKinsey showed a strong positive correlation between financial performance and gender diversity and even stronger correlation for ethnic and cultural diversity.

Why Are Diverse Teams More Innovative?

In today’s business environment, meaningful innovations happen at cross-borders of different disciplines. Having teams composed of experts in several relevant fields becomes a key prerequisite for any successful innovation project.

It’s therefore easy to understand how the diversity of expertise and experience would boost innovation.

But why is the diversity of race, ethnicity, gender, and sexual orientation so important?

Because diverse people bring to the table their unique information, perspectives, and experiences. Besides, working with individuals who are different forces all members of the innovation team to reassess their own assumptions.

Of course, working in diverse groups isn’t easy. It requires individuals to adjust their own behavior and working styles, something that doesn’t come easy to many. But a better innovation product will eventually emerge from this hard work.

Are there “Shortcuts” to Diversity?

Building diverse organizations takes time and effort, as evidenced by the struggle of large tech companies to diversify their workforces. However, there are at least three approaches every medium to large firm can try:

  1. When entering a new market (or a new segment of existing market), create an innovation team with a demographic composition closely resembling that of the target customer population.
  2. Maximize the benefits of so-called cognitive diversity by bringing together people with different viewpoints and styles of thinking.
  3. Approach large and diverse groups of people through crowdsourcing. 

Of the three, crowdsourcing appears to be the most straightforward way to boost innovation through diversity.

Crowds assembled by established open innovation platforms, such as InnoCentive or HeroX, are composed of people of different ages, genders, educational and professional backgrounds, geographies, and cultures. By design, they are as diverse a workforce as one could only dream of having in any organization.

And they show the value of diversity by bringing, day in and day out, superior solutions to the world’s most pressing problems.

(A version of this post first appeared on Change Logic’s Viewpoint Blog.)

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Opening open innovation toolbox

Proposed by Ralph-Christian Ohr model of integrative innovation management is a set of practical recommendations helping firms adopt a disciplined approach to innovation. Central to the model is the idea that firms must build a balanced portfolio composed of both exploitation and exploration innovation projects arranged along the following three strategic horizons:

  • Incremental Innovation: improving existing products and business models for existing customers.
  • Adjacent Innovation: expanding into “new to the company” markets.
  • Transformational Innovation: creating principally new products and business models to serve markets that may not have fully matured.

The major benefit of the 3-horizon innovation framework is that it shows firms how to structure, govern, and fund innovation programs while successfully managing risks. However, as formulated, it provides little guidance on which specific innovation tools firms should use when reaching for different innovation horizons.

In my previous post, I proposed a classification of open innovation (OI) tools based on the identity of OI partners and the pattern of interactions between them. In this post, I’ll attempt to match the content of my OI “toolbox” to the three strategic innovation horizons.

Co-creation. I consider customer co-creation as most efficient when applied to Incremental Innovation, when firms deal with modest improvements to core offerings and slight tweaks to existing business models. This stems from the two-way partner interaction inherent to this tool, which provides firms with early customer feedback, including MVP validation.

This ability to provide the immediate feedback to MVPs might expand the usability of co-creation into Adjacent Innovation. However, its effectiveness here appears to be lower than in the Incremental Innovation horizon (as I tried to indicate by the length of the corresponding arrow), because customers may have trouble to articulate their unmet needs when it comes to new products. And it’s exactly for this reason—the inability to articulate a need for something, be it a product or service, that doesn’t yet exist–that co-creation becomes virtually useless in the case of Transformational Innovation.  

Startups. This pattern gets reversed for engaging startups: useless when applied to Incremental Innovation, gaining some strength in the Adjacent Innovation horizon, this tool is at its best when used for Transformational Innovation. By their very nature, startups—at least the best of them–are entities created for the purpose of transformational change of the existing technology and/or business landscape. By engaging startups, firms would hire actors with creativity, flexibility, and audacity to challenge status quo that can rarely be found within internal innovation teams in most mature firms.

Engaging startups in Transformation Innovation is far from being easy, but by creating a vibrant startup ecosystem, firms can make this type of innovation possible and, perhaps, even sustainable. I’d even go as far as to claim that for most large firms, engaging startups is the only Transformational Innovation tool they can use with repeated success.

Crowdsourcing. I know that I’m biased towards crowdsourcing and that what I’m going to say may sounds controversial. But I’ll say it: crowdsourcing stands out among other open innovation tools in that it can be used, equally successfully, in all three innovation horizons.

The reason for this lies in the very nature of crowdsourcing as an innovation tool. Crowdsourcing is essentially a question posed to a crowd of people, with the nature of the received answer being determined, first and foremost, by the nature of the asked question. By properly formulating questions addressing problems and issues of increasing difficulty, complexity, time horizon, risk, and ambitions—and helping crowds deliver plausible answers to these questions–firms can successfully apply crowdsourcing to all innovation horizons.

No, I’m not saying that applying crowdsourcing to Transformational Innovation is as easy as to Incremental; moreover, I’d be hard pressed to name right away a bona fide breakthrough innovation conceived by using this tool.  Yet, I’d argue, as I did many times before (e.g., here and here), that the limited success in using crowdsourcing is due more to the firms’ inability to formulate a proper question than to the crowd’s inability to answer it.

(I’d like to point out that all the above was pertinent to external crowdsourcing. The applicability of internal crowdsourcing, the one engaging firms’ own employees, is different from that of external. See, for example, this post.)

Lead Users. As I argued in my previous post, engaging lead users is essentially a co-creation tool, which, as co-creation itself, is most efficient when applied to Incremental Innovation. However, bringing together large numbers of independent solvers may turbocharge this tool with some power of crowdsourcing. I, therefore, speculate that engaging lead users may become more useful tool for Adjacent Innovation than “pure” co-creation. I, however, admit that no data to support this speculation is available to me.

Webscouting. It’s a relatively new tool, and a solid track record of its practical achievements is yet to be built. Netnography, in particular, would seem to be very useful in discovering unmet customer needs, especially given its ability to engage large numbers of potential customers in a manner that is less intrusive and expensive than ethnography and focus groups, two popular techniques in the co-creation basket. That should make netnography a formidable Incremental Innovation tool.

The ability of webscouting to be applied to higher innovation horizons seems to be unclear at this point. One intriguing possibility is to use webscouting for detecting so-called weak signals, indicators of emerging trends that may mature in the future. If used in this way, webscouting should become a useful source of radical ideas firms can use to launch Adjacent and Transformation Innovation projects.

Will this happen? We’ll see.

Image credit: Hunter Haley on Unsplash

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A map of open innovation tools

Open Innovation (OI) has made tremendous progress, both in theory and practice, since its major principles were articulated by Henry Chesbrough in a seminal 2003 book. Today, much better than in 2003, we understand OI’s value proposition, its governance and management, and the corporate culture supporting its implementation.

However, I feel that there is a topic that for all these years, hasn’t received attention commensurable with its importance. This topic is OI tools. As far as I know, a 2013 study by Chesbrough and Sabine Brunswicker remains the only publication presenting a systematic list of OI practices used by American and European companies. (I’d be very grateful to anyone pointing me to additional published data on the topic.)

Chesbrough and Brunswicker classified OI tools based on two parameters: the knowledge flow direction (inbound vs. outbound) and knowledge flow financial nature (pecuniary vs. non-pecuniary). Although I agree that the first parameter is of strategic significance, I don’t consider the second one being important from the operational point of view.

In contrast to Chesbrough and Brunswicker, I propose to classify OI tools based on the identity of OI partner(s). This leads to the creation of two major buckets of OI tools: co-creation and crowdsourcing.

Co-creation. When firms co-innovate (co-create) with their customers, suppliers, and academic and business partners, they deal with defined partners, the partners whose identity is known to them. (Which, of course, doesn’t preclude all engaged parties from signing legally binding NDAs.) Firms deal with defined partners, too, when they form joint ventures or get engaged in inbound and/or outbound licensing.

Crowdsourcing. In contrast to co-creation, crowdsourcing implies undefined partners (“an undefined, generally large group of people,” as worded by Jeff Howe in 2006), the members of a crowd whose identity is unknown to the firm, at least initially.

The presence of a large number of partners–and the need to ensure that they all act independently of each other to make crowdsourcing campaigns effective–dictates the use of online methods of aggregating the incoming knowledge. This is another difference from co-creation that still largely relies on face-to-face interactions. The need of dealing with complete “strangers” also forces firms to pay careful attention to confidentiality and IP rights (the exception to this being when firms are using internal crowdsourcing).

The main specific crowdsourcing practices include innovation contents (challenges), external innovation portals, and using open innovation intermediaries, such as InnoCentive, NineSigma, or HeroX.

Startups. Formally speaking, engaging startups falls into the co-creation category as it involves dealing with defined partners. However, I prefer to keep this tool separate because of the acute interest it attracts in business literature and because engaging startups helps firms address technical and business problems that are different from those tackled by “pure” co-creation. (I’ll come back to this point in a separate post.)

Launching corporate venture funds and setting up accelerators/incubators are two major forms firms use to engage startups.

Webscouting. I define webscouting as collecting knowledge and insight by targeted browsing of online content. What makes webscouting similar to crowdsourcing is that both deal with undefined, unknown open innovation partners. What sets webscouting apart from both crowdsourcing and co-creation is the one-way (passive) mode of interaction between the partners: firms collect knowledge from the content creators without providing them with feedback. (In contrast, crowdsourcing and co-creation both imply the two-way mode of interaction between the partners, either online or in person.)

There are two specific practices in the webscouting basket. The first is netnography (a hybrid of “internet” and “ethnography”): gathering insight (needs and wants) of existing and prospective customers by following their conversations and/or observing their behavior online. The other is the social media solution scouting, a practice very similar to–and in some cases overlapping with–netnography: searching already existing (i.e. generated by consumers) solutions to the firm’s problems. (Here, I leave aside potential ethical issues and IP complications that could result from using this tool.)

Lead Users. The last element of my map, lead users, lies at the intersection between co-creation and crowdsourcing. On the one hand, engaging lead users in the development of new products and services represents co-creation in its classic form. On the other, the large number of engaged lead users justifies the employment of online tools, as in the case of crowdsourcing, rather than face-to-face interactions. The Audi Virtual Lab, a project that involved 7,000+ customers in the co-development of the Audi in-car multimedia system, is a great example of an advanced lead user application.

Obviously, any map makes sense only if it helps reach the desired destination. Can my map help apply different innovation tools to specific problems? I’ll talk about it in my next post.

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