A map of open innovation practices

A problem that I see with the current literature on open innovation is that while focusing predominantly on theoretical aspects of the concept (value proposition, strategic alignments, governance and management, human capital and culture), it pays little attention to the description of specific open innovation practices. As far as I know, a 2013 study by Henry Chesbrough and Sabine Brunswicker remains the only recent publication presenting a systematic list of open innovation practices used by American and European companies. (I’d be very grateful to anyone pointing me to the additional existing data on the topic.)

Earlier, I presented my own “map” of the existing open innovation practices. In contrast to Chesbrough and Brunswicker, who classified them based on the knowledge flow direction (inbound vs. outbound) and knowledge flow financial nature (pecuniary vs. non-pecuniary), I built my classification around the identity of the open innovation partner(s).

This distinction sets apart two major groups of open innovation practices: co-creation and crowdsourcing. When firms collaborate (co-create) with their customers, suppliers, academic and business partners or engage startups via innovation ecosystems, they deal with defined partners, the partners whose identity is known to them. In contrast, crowdsourcing involves undefined partners, the members of a crowd whose identity is unknown to the firm, at least initially. The major specific crowdsourcing practices include innovation contents, external innovation portals and the use of open innovation intermediaries.
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. At the same time, co-creation still largely relies on the face-to-face interaction.

Now, I’d like to add two more elements to my “map.” First, I believe that a better place for lead users (previously placed in the co-creation basket) would be at the intersection between co-creation and crowdsourcing. On the one hand, engaging lead users represents co-creation in its classic form. On the other, the large number of engaged lead users justifies the employment of online tools of knowledge gathering (like in 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.

Second, I propose adding the third group of open innovation practices: webscouting. One specific practice in this basket is netnography (a combination of “internet” and “ethnography”): collecting insight (needs and wants) of social-media-active consumers by following their conversations on various online forums. The other is the social media solution scouting, a practice very similar to – and in some cases even overlapping with – netnography: searching online venues for 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 such a mode of information gathering.)

What unites webscouting with crowdsourcing is that both deal with unknown, undefined open innovation partners. What sets webscouting apart from both crowdsourcing and co-creation is the one-way (passive) mode of interaction between the partners: collecting knowledge from the customers 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.

The proposed “map” may help in more precise matching between specific open innovation practices and different stages of business model innovation.

(I want to thank Kevin McFarthing for his suggestion to add inbound and outbound licensing to the co-creation basket).

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Don’t confuse crowdsourcing with brainstorming

eqb0011-blogphoto_0225_original-1024x547I try to follow what academic researchers have to say about crowdsourcing. As a crowdsourcing practitioner, I welcome the clarity, holistic approach and intellectual vigor that academic research brings to the table.

But not always. Take, for example, a recent Harvard Business Review article by Linus Dahlander and Henning Piezunka, “Why Some Crowdsourcing Efforts Work and Others Don’t.” Based on the data presented in their 2014 research paper, Dahlander and Piezunka set out to explain “why some organizations succeed to attract crowds and others fail.”

I have to say that the very choice of examples of successful and failed crowdsourcing campaigns Dahlander and Piezunka mention in their HBR paper is already confusing. They don’t seem to understand the difference between different crowdsourcing venues: open innovation competitions (Netflix’ 2009 $1 million prize), external innovation portals (Starbucks’ MyStarbucksIdea.com), open innovation intermediaries (NASA’s cosmic rays challenge) and online surveys (the German Pirate Party initiative). Sure, all four represent practical ways of using crowdsourcing, but the rules and conditions driving their success or failure are so different that throwing them into the same mix reminds me of the proverbial comparison of apples and oranges.

The confusion doesn’t go away when theauthors turn to practical recommendations on actions that managers could take to ensure success of their crowdsourcing campaigns. First, Dahlander and Piezunka suggest that instead of waiting for external contributions, organizations should first present their own ideas and then invite crowds to discuss these ideas. Dahlander and Piezunka argue that by showing to the crowds the types of ideas the organizations are interested in they motivate potential contributors to submit their own ideas.

Second, Dahlander and Piezunka insist that organizations should publicly discuss already submitted ideas and indicate which of them are most valuable. The authors argue that by showing to the current and future contributors their interest, organizations will further energize the submission process, ultimately resulting in the larger number of submitted ideas.

I see two major problems with Dahlander’s and Piezunka’s piece. To begin with, the authors seem to define the success of a crowdsourcing campaign predominantly by the size of the assembled crowd (“why some organizations succeed to attract crowds and others fail.”). This is completely misleading. Organizations turn to crowdsourcing to solve problems, and the only proof of success that really matters is whether the problem was solved or not. Of course, the size of the crowd plays an important role – in general, the larger the crowd, the higher the chance of solving the problem – by as any crowdsourcing practitioner would tell you, the major prerequisite for success is the ability to correctly define and articulate the problem you’re trying to solve by. If the problem is defined correctly, it could be solved even by a small crowd (I know such cases); if it’s defined incorrectly – so that you’re solving the wrong problem – no crowd, regardless of its size, will help (and I know such cases, too). By the way, are Dahlander and Piezunka aware of the fact that the winning solution for the Netflix $1 million prize, the one among 44,000(!) submitted, was never implemented? You call it success? I don’t.

Even more troubling, Dahlander and Piezunkaappear to confuse crowdsourcing with brainstorming. It’s brainstorming, not crowdsourcing, that requires throwing in an idea and asking other folks to comment on it – and it doesn’t matter whether you’re asking a few people in the room or a few thousands online. Now, I have nothing against brainstorming; yet one has to realize that by virtue of the collective discussion it implies, brainstorming almost always ends up with a consensus decision – or, worse, with a decision pushed forward by a vocal minority.

In contrast, when you crowdsource, you start with a problem you want to solve and then
provide your crowd with a clear sense of how a successful solution will be selected. Then you let the crowd do the job. Being unburdened with your prior “ideas”, the crowd will come with solutions that have only one goal in mind: to solve your problem. That’s why so often crowdsourcing campaigns deliver completely unexpected, even unorthodox, solutions.

Image credit: http://www.clixmarketing.com/blog/2015/06/18/why-good-old-fashioned-brainstorming-is-important-in-ppc/

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Missing in Innovation Action

miaI’m pretty sure that the authors of the recent PWC’s report on innovation wanted to paint a nice picture of the current state of corporate innovation. Having served 246 CEO’s from around the world with rather conventional (and, to my taste, softballish) questions, they conclude that “CEOs are now taking personal responsibility for directing and inspiring innovation.”

Indeed, the majority of the CEOs surveyed in the study sees innovation as a priority to their companies and regards it as equally important to operational effectiveness. Many of them consider themselves innovation leaders and visionaries as opposed to being simply “sponsors” of innovation programs. Better yet, the focus of corporate innovation activities is shifting from just product improvements to creating better business models. And I was almost elated when I read that the CEOs see strong business leadership and right culture as key ingredients for innovation success. Can it become any better, eh?

But this rosy picture has violently shattered in my face when I reached the last question of the survey: “Which of the following constraints is stopping you from being more innovative?” The three top answers to this question were: “Financial resources,” “Existing organization culture” and “Lack of talent.”

Wait a minute! Are the CEOs viewing these “constraints” as something that is completely out of their control, like a natural disaster or act of war? Is it not within the authority of a CEO to allocate enough financial resources to pursue innovation activities? Is it not the responsibility of a CEO to implement corporate policies fostering the culture of innovation? Is it not a CEO’s job to create conditions attracting and retaining innovative employees? Is that what it means to take personal responsibility for directing and inspiring innovation?

Over the past years, many CEOs have mastered the art of talking about innovation, delivering well-rounded answers to friendly questions in non-confrontational surveys and interviews. But a frighteningly large number of them still demonstrate what I call a “cloudy vision” of the very fundamentals of the innovation process. Too many CEOs take a hands-off approach to innovation management, proudly claiming instead that “in our company, innovation is everyone’s job.” And while talking non-stop about the culture of innovation, they neglect to introduce specific corporate policies encouraging and rewarding their employees’ innovation efforts.

I don’t count myself amount people claiming that innovation is “broken.” But I do believe that many problems of the modern corporate innovation process – and, definitely, the most serious of them – stem from the lackluster performance of people who are ultimately in charge of the innovation process: the CEOs. Yes, it’s nice having them learned innovation vocabulary; it’s time, however, for them to get into action.

Image credit: http://www.shutterstock.com

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Building your innovation “dream team”

dream_team(A longer version of this piece was originally posted to the Qmarkets blog)

You’ve heard this cliché many times before: innovation is all about people. Even if you’re an avid AI fan, you hardly expect robots replacing humans as innovators any time soon. And if you agree with another popular cliché, the one saying that innovation is a team sport, you will come to a natural conclusion that in order to pursue a corporate innovation project, you need to create a dedicated innovation team.

Or maybe not. Many people don’t believe in structured innovation arguing that any “structure” kills creativity and stifles innovation. Even some innovation experts argue that “innovation is everyone’s job.” The notion that “innovation is everyone’s job” happens to be quite popular in many companies too. Why? Because it allows its leadership adopt a hands-off approach to innovation process. It obviously takes time and effort to formulate the company’s innovation strategy, align it with corporate strategic goals and identify key problems to solve. In contrast, it’s so easy to just announce an open season for “ideas,” launch an innovation hackathon (or two) and then claim that the collective wisdom of the whole company has been harnessed.

And yet, the majority of corporate leaders do understand the value of creating a dedicated innovation team. Sure, every employee in your organization should ideally take part in innovation projects, but it’s the ultimate responsibility of the innovation team to take ownership of the process: to make it efficient, measurable and accountable. Anyone with a glimpse of corporate experience knows that when “everyone” is responsible for something, no one is.

And here we come to a crucial question: how this innovation team should be built? Several approaches to addressing this question exist.

The first approach emphasizes the personal skills of the team members. That’s why you will often hear that the best way to staff your innovation team is to hire…innovative people; great advice, but with limited practical value. Fortunately, more specific directions are available. For example, recently we were told that each member of the innovation team is supposed to possess five “innovative” qualities, of which the first is having a leapfrogging mindset: a desire to view the world with the goal of changing it. Although I agree in principle with this idea, I nevertheless suspect that the majority of corporate HR departments, even equipped with advanced Myers-Briggs tests, will have troubles with finding enough candidates meeting such a high standard.

The second approach pays little attention to the individual skill sets of the team members, but it stresses the need of an optimal mix of individuals the team is composed of. In particular, this approach focuses on the functional roles each member of the team plays in the project. For example, it was suggested that each innovation team should include nine innovation roles, such as Revolutionary, Connector, Magic Maker and Evangelist. This approach is obviously much more practical than the first; in fact, many organizations have already adopted the “spirit” (if not the exact “letter”) of this approach by creating innovation “joint task forces” composed of representatives from different corporate units and functions: R&D, sales and marketing, customer service, accounting, legal, HR, etc.

Implicit in the formation of an innovation team composed of members belonging to different parts of an organization is a belief that this team can only be successful if it includes people with diverse professional expertise and experience. In recent years, the concept of diversity was augmented by a growing body of scientific evidence (summarized in a 2014 article in Scientific American) showing that socially diverse groups (that is, those with a diversity of race, ethnicity, gender and sexual orientation) are more innovative than socially homogeneous groups. Multiple studies have found that socially diverse groups are better at solving complex problems not only because people with different backgrounds bring new information, but also because the mere presence of individuals with alternative viewpoints forces group members to work harder to get their own points across.

This is good news for HR managers in charge of innovation teams: in our rapidly globalizing workforce environment, finding people with diverse professional, personal and social attributes is much easier than chasing rare individuals with nebulous qualities such as the leapfrogging mindset.

There is the third approach to the formation of innovation teams. This approach emphasizes not the team composition or individual skills of its member, but the way the team operates. The logic behind this approach was eloquently articulated in a 2015 article describing team building at Google. The article argues that the composition of a team matters much less for its success than how the team members interact, structure their work and view their contributions. The article listed five key factors that set successful Google teams apart; the most important factor of the five was psychological safety, the ability of team members to take risks without feeling insecure or embarrassed.

The power of this particular example obviously emanates from the fact that it comes from Google, arguably one of the world’s most innovative companies, for the very notion that innovation requires taking risks without fear of negative career repercussions is hardly new. We all used to hearing calls to “fail fast and fail often” (or even to “celebrate failure”) as a surrogate invitation to innovate. Unfortunately, while voiceful in advocating risk-taking, relentless experimentation and learning from mistakes (all being parts of the elusive “culture of innovation”), companies nevertheless fail to introduce specific corporate policies that would encourage and reward such a behavior of their employees.

Previously, I suggested two such corporate policies. First, I proposed to make stock option grants – as opposed to cash bonuses and other monetary rewards – the principal incentive for engaging employees in innovation projects. This proposal is taking cue from a 2015 finding that companies offering stock options to non-executive employees were more innovative and that the positive effect of stock options on innovation was more pronounced with longer-term grants. Second, I proposed to place employees involved in innovation projects on fixed-term employment contracts, as opposed to employment-at-will. This proposal is based on a 2001 study showing that labor laws making it more difficult to fire employees increase their participation in corporate innovation activities.

In other words, companies should first provide all of their employees with incentives to engage in innovation activities along with immunity for failed innovation projects. With these policies in place, they may well discover that the number of qualified people willing to innovate is larger than they expected.

Image credit: http://www.hoopsvibe.com/features/281877-this-week-in-nba-history-1992-dream-team-dominates-tournament-of-the-americas#/slide/1

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What can crowds do?

Since the publication, in 2004, of James Surowiecki’s highly influential book, “The Wisdom of Crowds,” the idea that large groups of people are smarter than a few individuals, however brilliant, has been gradually gaining prominence in academic circles, business communities and, most importantly, public opinion.

The practical application of this idea has taken shape in the approach called crowdsourcing which was defined as “the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call.” Numerous organizations, including corporations, government agencies and non-profits, are now using crowdsourcing as a problem-solving, new product development, operational improvement and marketing tool. Crowdsourcing has also been successfully applied to public policymaking: from writing state constitutions to creating “smart cities.”

Another approach that engages crowds in important socioeconomic activities is crowdfunding. Although the idea of raising monies from the public (i.e., for charitable causes or disaster relief) is nothing new, the invention of the on-line crowdfunding platforms, such as Kickstarter and Indiegogo, has made this process substantially more streamlined and cost-effective. Equally importantly, crowdfunding has democratized the process of raising capital to start a new business or to launch a new product. It does so by allowing entrepreneurs to present their cases to larger audience of potentially interested parties, in addition to a limited number of professional investors.  

However useful crowdfunding might be to startups and early-stage ventures, it doesn’t solve all of their problems. For example, crowdfunding appears to be more relevant to mid-stage pre-market products, when potential buyers can already recognize existing market opportunities, but its benefits might be less obvious in the early stage product development.

Moreover, for a small company trying to do something truly innovative, the primary benefit of crowdfunding is not always the money; very often, it is the community. Having financially invested in the company, people become emotionally invested too. This emotional investment prompts them to help the company in some other ways: by providing feedback, sharing ideas or even their time (as beta testers and early users). It is this offer of additional human resources that startups and early stage projects often need more than money. However, so far no systematic way for small businesses to raise human capital has existed.

Enter crowdraising, an approach allowing crowds to pledge time instead of money to support causes they like. CrowdRaising.co, a startup founded by a NYC-based team that is passionate about open innovation, is building the world’s first crowdraising platform. (Full disclosure: I’m a member of the CrowdRaising.co Advisory Board.) Any project with a creative or innovative goal can use this platform to hire a “crowd” to perform business-related activities. These activities could be as simple as taking part in a survey, beta testing, giving a feedback on pricing or social media shares. But they also could involve more complex tasks, such as coding, design work or strategic advice. After completing their work on the project, the members of the crowds are expected to be rewarded: from a website mention or a free product for simpler tasks to cash or equity for more complex activities.

Crowdraising is a new and exciting idea, whose full potential is yet to be realized. However, it’s tempting to speculate that at the very least crowdraising may create a new paradigm of finding and hiring employees in the gig economy. But one thing is certain: new ways of exploiting the wisdom of crowds will keep emerging.

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When many experts are too many

slide1In my earlier posts (here and here), I argued that when facing a complex technical or business problem the majority of organizations have a natural inclination to begin the problem-solving process with engaging experts, either internal (employees) or external (consultants).

This approach isn’t without peril, however. If you approached a person, who is an expert in Method A, don’t expect her to tell you that using Method B, and not A, might be a better option to deal with your problem. And if you approached an expert in Method B, don’t expect to hear that this method won’t work–you’ll get at least some of Method B in your solution. And then, there might exist Methods C, D or E, but you never heard about them and therefore don’t know appropriate experts to approach. In other words, when asking for an expert opinion, you immediately narrow the scope of potential solutions to what your experts know.

Is there any empirical evidence showing that experts can actually hurt group performance? There is. In a Harvard Business Review article, “When Having Too Many Experts on the Board Backfires,” András Tilcsik and Juan Almandoz analyzed the role of the so-called domain experts (people whose primary professional experience is within a specific industry) on the performance of corporate boards. In particular, they wanted to know how the proportion of domain experts affected the board performance.

Tilcsik and Almandoz looked at the financial performance of 1,300 community banks and found that when banks faced increased levels of uncertainty, the higher proportion of domain experts on the board resulted in the higher likelihood of banks’ failure. The major problem with having too many domain experts on the board was “cognitive entrenchment,” the inability of expert-dominated boards to effectively respond to new information or unfamiliar situations.

I see a clear parallel between the above finding and the negative experts can have on the problem-solving process. By definition, problem-solving is a process with increased levels of uncertainty. Having too many domain experts on the problem-solving team could result in a preferential choice of old solutions (“we’ve always done it that way”) over new, untested approaches.

In my previous post, I discussed evidence showing that heterogeneous groups of people (i.e., composed of individuals with diverse professional, personal and social attributes) are more innovative than homogenous groups. I further argued that organizations can start reaping the innovation benefits of diversity in another way: by using crowdsourcing.

Here, I’d like to argue that using crowdsourcing to solve complex problems have clear advantages over relying on the intellectual power of experts. First, crowdsourcing is agnostic on the sources of potential solutions. If you engaged a large and sufficiently diversified crowd, you eliminate the very need to know whom you have to approach. You just announce that you have a problem, and then solutions will come to you.

Second, crowdsourcing is also agnostic on the nature of responses. Unless you specifically indicate that you’re interested in certain approaches only, incoming solutions will be focused on solving your problem, not the way of solving it. That’s why crowdsourcing often results in the delivery of completely unexpected, unorthodox solutions.

No, it’s not my intention to pit experts against “amateurs” when pointing to the virtues of crowdsourcing. In fact, crowdsourcing is impossible without experts. Only experts can identify and properly formulate the problems to solve; only experts can go through incoming external submissions to select those that make sense; only experts can integrate the external information with already available knowledge.

Besides, it’s just wrong to assume that people participating in crowdsourcing campaigns are just “amateurs.” In reality, crowds are composed of experts. They simply are not experts working for your company, or in your industry – or having your immediate area of expertise. Moreover, academic research shows that the likelihood of someone solving a problem increases with the distance between this person’s own field of technical expertise and the problem’s domain.

Sure, crowdsourcing isn’t an intuitive way to solve problems; you have to learn how to use it. And yet, if you’re looking for diversity of solutions, crowdsourcing is your best bet.

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Voter Education

live_map_presidentForbes published a list of the most and least educated states in the U.S. (based on the attainment of degrees and the quality of the education). When looking at the specific state names on the list, I felt that I already saw these exact groups before – and very recently.

Following this hunch, I went to the 2016 Presidential Election Map. I was right with my feeling. The 10 most educated states (Massachusetts, Maryland, Colorado, Connecticut, Vermont, New Hampshire, Virginia, Minnesota, Washington and New Jersey) all voted against Trump in the 2016 presidential election. Of 10 least educated states (Oklahoma, Texas, Tennessee, Alabama, Nevada, Kentucky, Arkansas, Louisiana, Mississippi and West Virginia), nine voted for Trump; only Nevada voted against.

Any additional comments needed here? I don’t think so.

Image credit: http://www.realclearpolitics.com/elections/live_results/2016_general/president/map.html

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