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.”

Image credit: Piret Ilver on Unsplash

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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.

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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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A house with a roof but no walls

Back in 2005 or 2006, I was on a business trip in Germany. One night, I was having dinner with a business partner of mine, an innovation manager at a large German chemical company. We chatted about this and that, and I casually remarked that while open innovation was making good inroads in business practices in the United States, its progress was significantly slower in Europe, Germany being no exception.

“I can easily explain that to you,” told my dinner partner, “the reason is our labor laws.”

I put down my fork. “What do your labor laws have to do with open innovation?” 

“Well,” was his response, “when you guys in the U.S. want to lay off people, you’re free to do so. But here in Germany, you can’t fire people at will. So, before launching an open innovation initiative, our management wants to make sure that all our own people are fully employed.”

While certainly amused by my partner’s take on the nature of labor relations in the U.S., I wasn’t totally surprised. The perception that open innovation was taking away R&D jobs was alive and well in many tech companies across America. Of course, such a perception didn’t make preaching the open innovation gospel any easier.

Times change and public opinions change with them. Today, no one seriously believes that open innovation takes away any jobs. (I guess, the honor now belongs to Artificial Intelligence.) Yet, the true place of open innovation in the corporate innovation toolbox remains far from settled.  

* * *

A friend of mine, an innovation manager, likes to joke: “Innovation is simple…but not easy.”

There is a reason for this uneasiness. Modern corporations, especially large ones, are obsessed with execution. Predictability of outcomes and the precise match between plans and achieved results are the metrics against which firms measure their performance and that of their employees. 

But innovation is messy. By its very nature, it’s highly unpredictable and relies on constant experimentation with most experiments ending up in failure. The lack of the predictability of outcomes makes innovation difficult to plan, especially when firms attempt to move their innovation goalposts beyond the incremental improvement of existing products.

Open innovation kicks it up a notch to this complexity by increasing the level of uncertainty: now, one needs to innovate with someone outside the corporate walls. This immediately triggers a round of additional concerns and complications.

First, internal innovation teams often interpret the introduction of open innovation as a vote of no confidence in their abilities to achieve the firm’s strategic innovation goals. So-called Not Invented Here Syndrome (NIHS), a rejection by internal teams of ideas and solutions that did not originate within the firm, almost inevitably ensue. (One should realize that the NIHS affects internal innovation, too, but this is a topic for a separate conversation.)  

Second, the perspective of working with “strangers” terrifies the firm’s legal department. Everyone who tried to initiate an open innovation project from within a private company would immediately remember a monstrous volume of paperwork and a ridiculous number of questions starting with “What if someone…?” A bordering on insane, the worst-case scenario speculation follows.

Finally, adding to the adoption problems is widespread confusion over open innovation tools. Some of them, such as crowdsourcing, are not terribly intuitive and need training and experience to use. Worse, what is often missing is a clear understanding that each specific open innovation tool is only good when applied to a matching innovation task. Tool mismatching—when a specific tool is being chosen without careful consideration of its applicability—is depressingly common. (I’ll return to this last point in a separate post.

* * *

At this point, many firms make a mistake that may appear tactical but in fact, can have a serious negative strategic impact: they create a separate open innovation team (that is, not formally a part of the larger corporate innovation unit).

Why do I think this is a mistake?

Corporate innovation requires extensive internal business development, a process by which members of the innovation team try to “sell” new ways of solving problems to other, often skeptical, corporate functions and units.

This isn’t easy by itself but with the added complexity that comes with open innovation, this internal business development often becomes a nightmare. A small open innovation team (it’s always small because open innovation teams are routinely under-resourced) is struggling to find internal clients to do things that sound complicated and often counterintuitive. It’s like going door-to-door around a neighborhood offering a product no one has heard of.

That’s why I strongly believe that in firms that are just starting using open innovation approaches systematically, the open innovation team must reside within a larger corporate innovation unit. This way, selling its “products” will become more organic and therefore more manageable.

Of course, as the open innovation program matures, the team will grow and at some point, may branch out. But starting with a separate open innovation team from the start is a sure way to set it up for failure. 

* * *

For someone who for the past 15+ years has been preaching the virtues of open innovation, this might be a strange confession to make. But I’ll make it nonetheless: there is no such thing as open corporate innovation.

There is only innovation, a process that drives the firm’s strategic growth. This innovation has a single body, one side of which is composed of tools utilizing the collective wisdom of the firm’s own employees. The other side of this body extends to the rest of the world trying to reach out to the diverse pools of global talent.

Creating open innovation programs without establishing internal first looks to me like a tree without roots. Or, if you prefer, a house with a roof but no walls.

No, no, and once again, no! I’m not saying that firms should postpone experimenting with open innovation until they establish internal innovation programs first (which may take years).  My point is that the full potential of open innovation can only be realized by the concerted effort of properly connected people within a firm capable of identifying and properly defining their own needs. Or, saying this differently, the power of open innovation comes from the strength within.

Image credit: https://thechurchwithoutwalls.com/believe/

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The last mile of the marathon

A few years ago, my daughter ran her first marathon. She then decided to take a short break from running: first, to get a well-deserved rest for her body, and second, to take care of business left neglected due to the rigorous schedule of pre-marathon training.

She returned to the trail 2-3 weeks later to run her first post-marathon routine, only 3-mile long. Although her body felt perfectly rested, my daughter was surprised how difficult it was to finish the distance. “You would expect that someone who’s just run 26 miles shouldn’t feel troubled with running only three,” complained she over the phone, “yet, I’ve barely made it.”

We talked a bit about that, and it became apparent to both of us that my daughter’s problem was mental, not physical. When she set her mind on running the whole 26 miles, the first 20 felt almost like a regular training; the real struggle began during the last few. But when she knew that the target was only three miles, the most difficult last mile began almost instantly.

I see an interesting parallel here with how firms set their corporate innovation targets.

Yes, I know: these targets must be realistic (SMART, CLEAR, PURE, you name it). Setting unrealistic targets are said to increase the probability of failure, which, despite our professed passion for celebrating it, still damages the innovation team’s morale and credibility, to say nothing about the team members’ bonuses and career prospects.

We therefore quietly settle on what is euphemistically called “early wins,” which are no more than easily achievable half-targets. And yet, we then often struggle to hit even these relaxed targets because…well, because the most difficult last mile begins almost instantly.

One can routinely hear complaints that corporate innovation is too incrementalas opposed to being disruptive. In fact, there is nothing wrong with incremental innovation: it represents a key part of any balanced innovation portfolio. The problem arises when incremental innovation is not a well-planned and carefully executed project aimed at improving the firm’s core offerings, but rather an aborted attempt at innovating something larger and more ambitious.

It’s like instead of covering the whole marathon distance, we run until we feel that our muscles are numb, and our lungs gasping for air. At which point, we walk off the trail and declare mission accomplished (and celebrate an early win).

In a recent HBR article, Antonio Nieto-Rodriguez argues that when evaluating and prioritizing projects, looking at the business case alone isn’t enough. Firms also need to understand how the project connects to what the author calls higher purpose. It is defining projects for their purpose that is the best way to understand whether or not they make sense strategically.

I fully agree. Successful corporate innovation requires many things: strong executive leadership, well-defined innovation strategy, functional innovation governance, tools and processes, talent management, etc., etc., etc.

But every innovation project begins with a goal, with a destination. And only after defining this destination it is possible to choose the luggage you’ll carry during the bumpy innovation journey.

It’s like when leaving your house in running gear in the morning, you should know what you’re up to: to run the full marathon or just to jog for a few miles before breakfast.

Image credit: https://blog.strava.com/london-marathon-hayley-carruthers-17902/

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The questions we ask

In my previous post, I argued that the proper definition of a problem is the most important part of any innovation initiative, in particular, crowdsourcing campaign. Inspired by the Pareto Principle, I call it the 80:20 rule of crowdsourcing: 80% of unsuccessful crowdsourcing campaigns failed because the problem presented to the crowd was not properly defined; only 20% did so because of a poor match between the problem and the crowd’s capabilities.

The process of problem definition isn’t easy, but it can be learned. Unfortunately, many organizations, especially those new to crowdsourcing, simply don’t understand the importance of this process. They mistakenly believe that they can ask the crowd almost anything, in any form, and then it will be up to the crowd to figure out what needs to be done.

This is the wrong approach, and although it may sound self-serving, having around someone with experience in running crowdsourcing campaigns would be helpful.

This reminds me of a project I once had with a client, a pharmaceutical company. My client wanted to design a high throughput screening (HTS) assay to study a specific type of cellular transformation, a process by which normal cells become precancerous.

To those unfamiliar with HTS assays, I will say that pharmaceutical companies routinely use them for drug discovery because HTS assays allow to screen literally tens or even hundreds of thousands of chemical compounds for biologic activity. Although HTS assays employ robotics and sophisticated software, at their core they are still a “regular” assay: you start with a normal cell, you add a test compound, and you watch for something that indicates that the transformation you’re interested in has taken place.

My counterpart at the client site, the head of the assay development group, confidently listed the most important parameters the future assay was expected to have: volume (the number of samples analyzed per hour or day), the ratio of so-called false positives and false negatives (two key parameters defining the assay’s accuracy), and the cost (as cheap as possible. But of course.).

While listening to her and taking notes, I began to sense that something very important was still missing. Finally, I found an opportunity to interrupt: “All right, everything is clear. But what about the endpoint? What is your endpoint?” (In most assays, the endpoint is the thing that the assay physically measures.)

For a split second, my client lost her confidence. She paused and then said, carefully choosing her words: “Well, we do not have an endpoint. We thought that finding it would be part of the whole solution.”

It was now my turn to carefully choose what I was about to say. “Well, perhaps, we’re asking too much. What if we start by looking for a suitable endpoint and then, after we have found it, we’ll run a follow-up campaign to design an HTS assay based on this endpoint?”

She broadly smiled in response: “Look, if we had a good endpoint, we wouldn’t need you: my in-house assay developers will design an HTS version of the assay in a matter of weeks.”

That ended our discussion. Shortly, the two of us put together a problem statement asking for a molecule whose change in quantity or structure within cells would signal that the cellular transformation in question had taken place.

We posted the statement online, and in about a week or two, I got a submission from a solver living in one of the small Eastern European countries. The submission described a protein (I had never heard of it before) that was overproduced by the cells that had experienced the transformation my client was interested in. This overproduction could be easily detected by measuring the intensity of fluorescence, a slam dunk for any assay developer.

Frugally written, only a half-page in length, the submission had a couple of paragraphs of text, a picture, and a reference. But it was nevertheless something I could share with my client.

Her response followed almost immediately: “I love it! We’re buying this solution.”

And that was it. I completed the paperwork transferring all intellectual property rights to the solution to my client. I never heard from her again: apparently, her in-house assay developers were indeed as good as she described them.

Image credit: https://www.criver.com/products-services/discovery-services/screening-and-profiling-assays/assay-development/ion-channel-assays?region=3601

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How to win a war

What do you need to win a war?

A few things. First, you need an army equipped with superior weapons and instilled with high spirits. Second, you need a vibrant economy capable of sustaining the hardship of continued military operations. Third, you need strong public support of the country’s political and military leadership.

Did I forget anything? Oh, one more thing: you need an enemy. And not just any enemy, a bogeyman created to justify the war, but the enemy, a thorn in your side that needs to be removed ASAP.

Finding the true enemy is usually (but not always) easier in the case of military operations. But we Americans love to launch wars against everything we consider a threat to our society. That’s where defining the enemy becomes tricky.

Take President Johnson’s 1964 War on Poverty. By failing to identify the root causes of poverty, the federal government has since been shelling the elusive enemy with 92(!) federal programs. According to a 2016 study, the federal government spent $668 billion on antipoverty programs, with state governments another $284 billion. The result? The poverty rate in the U.S. has been steady over the past 50 years, fluctuating between 10 and 15%.

Or take the War on Drugs launched by President Nixon in 1971. Since its inception, the initiative has received over $1 trillion in funding, but by focusing on fighting drug traffickers instead of treating drug addicts, the War on Drugs has miserably failed to eradicate illegal drug use.

The only arguably bright spot in our fight against social maladies has been President Nixon’s War on Cancer. By identifying molecular targets responsible for malignant growth and then designing drugs specifically attacking these targets, scientists have been able to dramatically decrease the death rate for many types of cancers. The total cancer death rate in the United States fell 25% from its peak in 1991. (An analogy with using special forces instead of regular troops immediately springs to mind.)

* * *

Now, I’m not a great fan of using military terminology for non-military topics (or the baseball terminology for non-sports conversations, for that matter). Yet, it’s tempting to compare a crowdsourcing campaign to a military operation.

To begin with, you need a large and competent crowd (your “army”), properly motivated, to solve a problem. But even more importantly, you must define this problem (your “enemy”) so that the crowd can attack it in the most effective way. Failing to do so will make your enemy elusive and your campaign unfocused and, inevitably, unsuccessful.

I call it the “80:20 rule”: in my experience, some 80% of unsuccessful crowdsourcing campaigns failed because the problem presented to the crowd was not properly defined; only 20% did so because of a poor match between the problem and the crowd’s competence.

* * *

Clients always come to me knowing what they want. Unfortunately, very often they don’t do enough preliminary work to understand what they need.

I remember a client who wanted to crowdsource a new design of a paint pump because it often clogged when dispersing paint. We investigated the problem a bit further and found that the cause of clogging was not the pump. Rather, the clogging occurred because the viscosity of the paint would sharply increase with a slight drop of the surrounding temperature (usually when using the pump outside in cold weather). The client fixed the clogging problem without running a crowdsourcing campaign by simply changing the composition of the paint.

I remember another client who wanted to crowdsource an additive that would prevent a food product they were manufacturing from losing sweetness upon processing. It took a lot of effort to persuade the client to leave the door open for solutions that would include modifications of the food preparation process itself. (“No, we can’t change the process; it’s too expensive!”). To my client’s great surprise, someone came up with a solution proposing a minor, inexpensive change in the preparation process that led to the same desired result: the preservation of sweetness.

It’s tempting to say that what clients want is a symptom of a disease whereas what clients really need is the cause of it. You can’t successfully cure the disease (solve the problem) unless you identify its real cause (define the problem).

But enough terminological exercises! Let me finish with formulating my first rule of crowdsourcing: know what you want, understand what you need.

Image credit: https://www.reddit.com/r/vexillology/comments/56mi3j/flag_in_an_old_painting

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A stranger in the room

Better decisions come from teams that include a “socially distinct newcomer

(Kellogg School of Management News, 2009)

What role do external consultants play in shaping corporate innovation?

Steve Blank, one of the greatest innovation thinkers of our times, seems to discount this role. In Blank’s opinion, “innovation won’t come from plans or people outside your company–it will be found in the people you already have inside who understand your company’s strengths and its vulnerabilities.”

I agree with Blank: like revolutions, innovation can’t be imported. The full potential of corporate innovation can only be realized by the concerted effort of properly connected people within firms capable of identifying and defining their own needs. Or, saying the same differently, the power of corporate innovation comes from the strength from within.  

And yet, I do believe external consultants may play an important role in helping firms innovate.

Sure, employees are vastly superior to any outsider in knowing their firm’s business. Besides, they have a strong vested interest in the firm’s future.

But outsiders have at least one undeniable advantage over insiders: they’re not exposed to the often-toxic fumes of internal politics. That helps them better deal with competing ideas and opinions, judging them on their merits rather than on their authorship.

And then, there is this luxury to be a “stranger in the room,” not knowing the ways things “have always been done here” and being naïve enough to keep asking stubborn whys when everyone else in the room already knows the right way.

I fully appreciated the magic power of a “naïve” question after having a memorable meeting with one client, a pharmaceutical company.

As often happens, the meeting was organized in haste, and the only thing I was told was that the client wanted to discuss phosphorus-containing detergents.

I thought I knew what that meant. This pharmaceutical company used phosphorus-containing detergents to clean production vessels after each manufacturing cycle. But phosphorus-containing compounds, notoriously environmentally unfriendly, had been steadily falling under regulatory scrutiny; it was only a matter of time before the regulatory authority, the U.S. Food and Drug Administration, would ban using them altogether.

I knew from my previous interactions with this client that they wanted to act proactively and switch to detergents based on more environmentally safe organic acids, as some of their competitors had already done.  Having assumed that the client wanted to crowdsource the optimal composition of a new cleaning solution, I spent my flight time reading relevant articles that I managed to collect before rushing to the airport.

The next morning, I was sitting in a room with five managers responsible for cleaning the manufacturing equipment. A nice breakfast was served, and, judging from my prior visits, a delicious lunch was to follow by noon.

After a few minutes of discussing the latest football scores, I got down to business: “OK guys, do you want to identify the best phosphorus-free cleaners?”

“No,” responded the gentleman in charge of the meeting on the client side, “there are plenty of commercially available cleaners based on citric acid. We know precisely what we want to use.”

I felt a bit puzzled: “So, what is the problem?”

“The problem is that there is a strong resistance inside the manufacturing unit to switching from a phosphorus-containing cleaner to the one based on citric acid. We tried, but it didn’t work.”

Feeling even more puzzled, I asked: “Who in the company has the authority to make this decision? Have you talked to this person?”

By the silence that followed, I realized that completely unwillingly I had put my hosts in an awkward position. They should have felt embarrassed that such a simple, obvious to even a stranger, solution had somehow escaped their attention.

The managers exchanged uneasy glances, and the one in charge uttered: “Well, we don’t actually know…”

Another manager rushed to help: “We’ll find out and bring this issue to the table. Perhaps, the situation isn’t as bad as it appears…”

Barely in its fifteenth minute, our four-hour-long workshop was over. We chatted for a few more minutes, discussing potential next steps, but I already knew that this team would never contact me again. (I was correct.) Apparently mindful of the fact that I was deprived of lunch, my hosts paid the cab fare to the airport.

I managed to change my mid-afternoon flight for an earlier one, and my watch was telling me that I would be home well before dinner. I was sitting in a half-empty airport terminal lit with the bright morning sun and sipped coffee bought from the nearby Starbucks. Life was good.

Image credit: https://well.blogs.nytimes.com/2009/12/01/why-loneliness-can-be-contagious/

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