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.

Image credit: Nadjib BR on Unsplash

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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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Traveling unchartered innovation waters with Innovation Charter

(An earlier version of this piece was posted last year to the HeroX blog)

A few years ago, I came across an innovation survey, sponsored by Wazoku. Its results shocked me. 

Full 85% of respondents to the survey–board members, senior and middle managers, and line workers at large UK enterprises–considered innovation important to their companies. So far, so good. Yet 53% of surveyed managers were unaware of their company’s definition of innovation and how it fit into wider corporate goals. And 38% said innovation wasn’t their responsibility because it wasn’t in their job descriptions.

So much for a popular corporate tune: in our company, innovation is everyone’s job!

A lack of understanding of what innovation means for firms remains one of the most serious problems facing corporate innovation. Even C-level executives aren’t immune to this disease, but at the lower organizational levels, almost everyone is infected.

Obviously, no single fix exists to solve the problem. However, for firms that are yet to develop a structured innovation process–and also the ones that struggle to run working innovation programs–I’d recommend a solution that may look deceptively simple (worse, outright bureaucratic) but may prove surprisingly effective. 

The solution is to create a corporate Innovation Charter.

There are three immediate reasons why the Innovation Charter can help firms innovate better.

The Innovation Charter defines corporate innovation strategy

The major objective of the Innovation Charter is to spell out what innovation means for this specific firm. Not humanity, not whole industry. This specific firm.   

It should start with explaining where the firm stands today and where it wants to be in the future. It should then describe how the gap between “now and then” is to be bridged, and what role innovation should play in this process.

The clarity about the place innovation occupies within the general corporate strategy will help select and support matching innovation programs (and not just a generic cocktail of hackathons, idea-generation extravaganza, and fast and often failure festivities).

Equally important, the Innovation Charter will help create a common innovation language, the lack of which often results in a communication wall between corporate innovation team and the rest of the firm.

The Innovation Charter extracts maximum (vis-à-vis innovation, of course) out of the CEO

CEOs are routinely blamed for the lack of attention to innovation, and I myself is guilty as charged.

But let’s face it: they are very busy people in charge of everything. It’s plain unrealistic to expect them to pay unwavering attention to innovation, a continuous, often behind-the-scene process, which lacks frequent “events” and shows no obvious need for day-to-day executive intervention.

So, instead of asking the CEO for constant checking in, the innovation team should create the Innovation Charter and ask the CEO to publicly endorse it. With this endorsement, the innovation team can claim executive support even when the attention of the executive leaders will inevitably shift to other priorities.

It’s tempting to call the Innovation Charter the innovation law of the land. Of course, like any other law, it will need periodic re-enforcement, but will still keep maintaining order even when there are no cops around.

The Innovation Charter makes innovation “everyone’s job”

Corporate innovation can become much more efficient if it’ll expand from traditional R&D or product development units to departments that are not directly involved in the innovation process (manufacturing, finance, HR, etc.). Unfortunately, very often, the corporate structure is too rigid, too “anti-matrix,” to allow innovation to become “everyone’s job.”

Realistically, not everyone in the firm will be willing to assume an extra load that participation in innovation activities demands—and that’s fine. But even those who want to get involved, often can’t do so because of the pressure of their regular jobs.

Besides, attempts at expanding innovation activities throughout the whole firm are often met with resistance at the level of all-powerful middle managers. Unwilling to sabotage corporate innovation initiatives openly (especially if endorsed by the CEO), they often resort to implicit sabotage by not allowing their reports to get engaged on the ground that those are “too busy.”

This is a series problem with no ready-to-go fix to it. But here, too, the Innovation Charter can help because it provides an explicit mandate to anyone in the firm to get their feet wet in the whole-firm innovation waters, something that even their managers can’t easily ignore.

Or, to say it differently, the Innovation Charter adds innovation activities to everyone’s job description at once. Kind of.

Image credit: https://www.britannica.com/story/which-waters-do-you-pass-through-when-you-sail-the-seven-seas

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Internal innovation: overcoming the dangers of remote work

Pessimists are said to be the happiest people on earth, for they celebrate when their own predictions don’t come true.

There was a shock wave of panic last spring when, due to the COVID-19 pandemic, firms around the globe had to switch to remote work, suddenly and en masse.

One can, therefore, easily understand the sense of relief, almost euphoria, filling the air when the captains of industry realized that switching to remote work hadn’t resulted in the immediate collapse of the corporate world.

Remote work works and has a future. That was a conclusion of a report composed by Upwork, a freelance marketplace, based on online surveys of corporate managers conducted at the end of April 2020. (Given that only a few weeks passed after the beginning of the remote work “experiment,” the conclusion of the report looks a bit rushed up, doesn’t it?)

Yet, voices of pessimists on the other side of the barricade were heard already, too. Some academics warned that online communications, a hallmark of remote work, were characterized by lower information sharing—and that meant the increased likelihood of poor decision-making in the short term and the reduced exchange of ideas between the employees in the longer term.

Now, just published data suggests that the pessimistic predictions about potential danger of remote work holds a lot of truth.

Innovation in peril?

A group of researchers from Microsoft analyzed communication practices of 61,182 U.S. Microsoft employees before and after Microsoft’s shift to firm-wide remote work. The major observations were as follows:

  • Remote work caused business groups within Microsoft to become less interconnected.
  • Remote work reduced the number of ties within the company’s informal collaboration network and caused employees to spend less time collaborating with the ties that remained.
  • Remote work caused employees to collaborate more with their stronger ties, which are better suited for information transfer, and less with weak ties, which are more likely to provide access to new information.
  • Remote work caused employees to communicate more via asynchronous media channels (email and IM), which are better suited for conveying information, and less via synchronous ones (video and phone calls), which are better suited for converging on the meaning of complex information.

Summing up their results, the authors concluded that shifting to remote work made Microsoft’s collaboration network more siloed, more static, and less “rich.” And although the authors didn’t directly measure any innovation outcomes, they fully expect that the effects on innovation of changing collaboration and communication patterns will be negative in the long term.

A sober conclusion, given that Microsoft postponed the employee return to the office—yet again.

Internal innovation networks to the rescue

Now matter what you think about the “letter” of the Upwork report, its “spirit” is right on point. Remote work is here to stay. So, the major question right now is how to minimize the potential negative consequences of remote work on innovation.

The answer lies in plain sight: internal innovation networks (IINs).

Although IINs provide organizations with many benefits, two are particularly relevant to overcome the shortfalls of remote work.

First, IINs provide a communication channel between different corporate functions and units that often have no institutional framework to discuss strategic issues. By providing such a channel, IINs create a common intellectual space, which not only allows to exchange complex information but also to facilitate an in-depth discussion of it.

Second, by hosting innovation contents and competitions, open to the whole company, IINs enhance and formalize existing weak ties. This may result in the creation of a new knowledge, which is often superior to the one created within established hierarchical teams.

This is not to say, of course, that firms should abandon or even scale down the existing external/open innovation initiatives. The point here is that the full innovation potential of any organization can only be realized by the concerted effort of connected employees capable of identifying and defining their own problems.

Regardless of whether we’re living in “normal times” or in the case of an emergency.

Image credit: https://www.newcybersource.com/network-solutions/

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Yes, size matters. It’s just not that the bigger is always the better

Among many of Jeff Bezos’s wisdoms, his two-pizza rule is one of the most famous. It states that every internal team should be small enough that it can be fed with two pizzas–to make meetings more effective and the teams more innovative.

When it comes to scientific research, the world seems to disagree with Bezos. As large-scale scientific collaboration become increasingly popular, research groups grow bigger and bigger. A world record seems to belong to a physics paper published in 2015: 5,154 authors. Only the first nine pages of the 33-page article describe the research itself; the rest (24 pages) lists the authors and their affiliation. Just imagine how many pizza parlors would have to work overtime to provide a single lunch for this tight-knit group of collaborators!

The proponents of “the bigger, the better” approach can point to at least one argument in support of their position: a positive correlation between a team’s size and a citation impact of a product that this team had produced. This correlation holds not only for STEM research, but also for social sciences, art and humanities, and patents. The bigger the team of collaborators, the greater the buzz their work is generating.

And yet, Bezos might have had the last laugh—as usual.

A group of authors led by James A. Evans of University of Chicago designed an advanced, more nuanced citation-based index capable of discriminating between “disruptive” and more conventional (“consolidating”) research contributions. Their logic was as follows: when future citations to a given article also reference a substantial proportion of that article’s own references, then the article can be seen as consolidating its scientific domain. However, when future citations do not acknowledge the article’s own references, the article can be seen as disrupting its domain[1].

Evans and his co-authors analyzed more than 65 million articles, patents, and software products generated over 1954–2014. They show that smaller teams tend to come up with more new ideas and opportunities (disruptive contribution), whereas larger teams tend to develop existing ones (consolidating contribution).


The authors also show that work from larger teams often builds on more recent and popular developments, so that attention to their work comes immediately. By contrast, contributions by smaller teams go more deeply into the past and, if successful, project further into the future.

My first impulse is to apply the result of Evans and his collaborators to the incremental vs. disruptive innovation dichotomy. When pursuing incremental (so tempting to say, consolidating) innovation, organization would seem to benefit from creating larger teams that could rapidly expand on recent product development gains. On the other hand, achieving disruptive innovation goals would be more plausible by establishing many small groups pursuing diverse projects—mimicking essentially the approach used by VC investors.

I also wonder if eating a particular type of pizza—say, Neapolitan vs. New York-style—would benefit a specific type of innovation.

Just kidding.

[1] For example, the index shows that articles directly contributing to Nobel prizes tend to exhibit high levels of disruptiveness; at the other extreme, review articles tend to be highly “consolidating.”

Image credit: https://adenuniversity.us/business-magazine/discover-the-two-pizza-rule-that-jeff-bezos-uses-to-have-more-productive-meetings/

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