Are crowds stupid?

We have been talking about the wisdom of crowds for so long and with such a passion that it was only a matter of time that someone would decide to call crowds stupid. And here it comes: Aran Rees, “a creativity coach, facilitator and communicator,” published what looks like a bona fide anti-crowdsourcing manifesto, “The Stupidity of Crowds.”

As a proof that crowds are stupid, Rees cites two recent examples. First, he mentions an attempt by a British government agency to crowdsource a research ship’s name, a process that ended up with the public having chosen a completely ridiculous option. Rees’s second example is Brexit, a decision by the British public, expressed during a 2016 referendum, to leave the European Union.

To me this sounds like shooting the messenger when you don’t like the message. Crowdsourcing is, first and foremost, a question that you ask a crowd; the quality of the question is the most important determinant of the quality of the answer. You ask the crowd a smart question–you have a chance to get a smart answer. You ask the crowd a stupid question–the answer will almost certainly be stupid.

I’d agree with Rees that asking crowds to come up with names and then vote for them is a stupid idea. So, in my opinion, was the idea of putting to a referendum the U.K.’s membership in the EU. But why should the blame rest with the crowds? Blame crowdmasters, the people who have posed these stupid questions to the crowds! Besides, as a matter of sheer decency, should we automatically call stupid people who have tastes, sense of humor and political preferences different from ours?

Rees’s criticism of crowds and crowdsourcing troubles me for two additional reasons. The first is his habit—unfortunately, a very common one—of overemphasizing the “crowd” part of the word “crowdsourcing.” Rees and many others tend to call crowdsourcing almost any activity involving a large group of people, especially if these activities happen online. But the original—and still, in my opinion, the best—definition of crowdsourcing, proposed by Jeff Howe in 2006, describes it 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.”

In other words, crowdsourcing is not just about a crowd; it’s about outsourcing a job. Asking people to vote in a survey or referendum is not outsourcing a job, at least not in the sense most organizations and reasonable people would define the term “job.” That’s why, by the way, in contrast to what Rees thinks, Facebook and Twitter are not crowdsourcing venues. (As Henry Mintzberg shrewdly suggested, ask your Facebook friends to help paint your house.)

The second problem is that Rees reduces crowdsourcing to simply generating ideas and/or voting for them. He thus rhetorically asks: “Do you suppose that someone taking five minutes to respond to a survey and someone else taking ten second to vote is likely to result in deeply thought out insights?”

Is this how Rees understands crowdsourcing? Has he ever heard about NASA using crowdsourcing to crack previously intractable space exploration problems? Has he ever heard about tremendously successful “Ebola Grand Challenge” sponsored by the USAID? Has he ever heard about open innovation boutiques, such as InnoCentive and NineSigma, which turned crowdsourcing into commercially viable business opportunities by serving, with very impressive success rate, their corporate, government and non-profit clients?

Crowdsourcing is extremely powerful problem-solving tool, but as any other tool, it requires knowledge and experience to be properly used. Those who know how to use crowdsourcing will succeed in harnessing the proverbial wisdom of crowds. Those who don’t won’t. It’s this simple.

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Applying open innovation tools to business model innovation

Recently, I proposed a “map” of existing open innovation tools based on the identity of open innovation partner(s) and the mode of interaction between them. Three large “baskets” were included: co-creation (known partners, two-way interaction), crowdsourcing (unknown partners, two-way interaction) and webscouting (unknown partners, one-way interaction). I further suggested that the proposed map may help in matching specific open innovation tools with different types of innovation.

In the first example of such matching, I looked at the usefulness of internal and external crowdsourcing at three stages of business model innovation, the latter being defined by C.M. Christensen, T. Bartman and D. van Bever”as follows:

  • Market-creating innovations, the type of innovation that takes place at the first stage of business model formation when firms search for a meaningful value proposition,g., product or service that would fulfill unmet customer needs (“job to be done”).
  • Sustaining innovations, the type of innovation, which is an improvement in the firm’s core offerings, involving the creation of better products or services that can be sold for higher prices to existing customers.
  • Efficiency innovations, the type of innovation that kicks in when sustaining innovations no longer generate additional profitability and the firms turns to cost reduction, mainly by optimizing internal processes.

Here, I want to explore a match between stages of business model innovation and two other major open innovation tools: customer co-creation and webscouting.

The usefulness of both customer co-creation and webscouting is the highest when applied to market-creating innovations, the process of designing new products and services. Webscouting – in particular, netnography – would be indispensable in discovering unmet customer wants and needs. Its benefits include the ability to scout large numbers of potential customers and being less intrusive and expensive than ethnography and focus groups, two popular techniques in the customer co-creation basket. At the same time, the two-way interaction nature of customer co-creation provides opportunities for early customer feedback, allowing firms to test hypotheses and MVP’s. Using both tools in parallel may have a synergistic effect on the productivity of internal R&D teams.

Customer co-creation and webscouting are still highly effective when applied to sustaining innovations, allowing firms to collect customer feedback to their products and services. Again, using both tools in parallel would be the most beneficial as the depth of interaction with customers obtained through customer co-creation would be augmented by the large number of data points collected with the help of webscouting.

Webscouting, which, by definition, is the collection of customer insight on online forums, simply doesn’t apply to efficiency innovation. But customer co-creation, too, completely loses its power at this stage of business innovation: no customer, however close and trusted, can possess enough relevant information to be able to provide valuable insight with regards to the firm’s internal operations and cost structure, the hallmark of efficiency innovation.

The usefulness of customer co-creation and webscouting closely mirrors that of external crowdsourcing, which, too, is very efficient at the market-creating innovations stage, but gradually loses its efficiency at later stages. So far, I’m aware of only one open innovation tool that could be successfully applied to the efficiency innovation stage: internal crowdsourcing. That being said, I fully realize that the very classification of internal crowdsourcing (i.e., crowdsourcing conducted within the legal boundaries of the firm) as an open innovation tool could be questioned.

I’d also like to add that when talking about customer co-creation I had in mind the group of techniques specifically engaging existing and prospective customers, lead users (and, to a lesser extent, suppliers and academic and business partners). Left aside were approaches involving engaging startups (startup incubators/accelerators, joint ventures, etc.) that I also consider tools in the larger co-creation basket. Matching these open innovation tools to different types of innovation deserves separate analysis.

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Why does your doctor hate crowdsourcing?

One of the signs of the growing popularity of crowdsourcing is its steady expansion into gated professional communities dominated by experts. Take, for example, medical diagnostics, an area that has for centuries been a fiefdom of medical professionals. Now, a bunch of platforms (CrowdMed being, perhaps, the most prominent) has emerged to provide patients with online medical diagnosis, especially diagnosis of rare conditions that have been missed by doctors.

Hardly surprisingly, the visitors aren’t particularly welcome. Back in September, I wrote about Dr. Joshua Liao, a resident physician in the Department of Medicine at Brigham and Women’s Hospital and a clinical fellow in medicine at Harvard Medical School, who used the pages of the Boston Globe to express his grudge against crowdsourcing.

Dr. Liao was approached by son of his patient, asking the doctor about CrowdMed as a potential help in establishing diagnosis for the patient’s mother. Dr. Liao’s response was no. He explained that a solid diagnosis requires not only patient’s medical history, which supposedly can be provided to a crowd, but, more importantly, direct medical examination of the patient, which can be not. For this reason, in his opinion, services like CrowdMed “produce more questions than answers, and more confusion than direction.”

I see Dr. Liao’s point, because I do understand the value of in-person medical examination. What troubles me with his argument is at least a dozen of “patient success stories” posted to the CrowdMed website, the testimonies by the people who were apparently helped by the crowd after their own doctors failed to do so. How are we to treat these “success stories”? As a fluke? As fake news, a popular accusation these days? Or as examples that in some cases, in spite of what Dr. Liao says, crowdsourcing can really deliver something that a single expert, however accomplished and experienced, can’t?

(And, mind you, I’m not even touching upon a sensitive issue of diagnostic mistakes committed by doctors themselves – a whopping 12 million a year of them – that account for 210,000 to 440,000 U.S. deaths annually).

As you can imagine, Dr. Liao isn’t the only doctor who hates crowdsourcing. Just a few days ago, I came across a piece written by Dr. Jeff Russ, a pediatrician. Dr. Russ’s criticism of crowdsourcing (which he attributes to the rise of medical “populism”) is arguably more grounded and sophisticated than Dr. Liao’s. And yet, when Dr. Russ insists that “crowdsourcing [relies] on the hope that sufficient quantity will outweigh…quality”, I can’t stop from asking myself whether Dr. Russ understands what crowdsourcing really is.

Crowdsourcing is not about quantity; it’s not even about quality. It’s about diversity. Crowdsourcing works not because crowds can generate numerous responses of varying quality, but because crowds can come up with unexpected, often completely unorthodox, solutions. And it’s the lack of diversity – diversity of opinions, sources of information and experiences – that forces professionals, in the medical field and elsewhere, to commit mistakes.

So I have a simple advice for Dr. Liao, Dr. Russ and his colleagues: don’t reject crowdsourcing; embrace it. Accept crowdsourcing as one of the many diagnostic tools in your repertoire. Obviously, there is no need to run a crowdsourcing campaign in case of a simple cold. However, when dealing with a complicated, potentially life-threatening, case (as the one described by Dr. Russ in his piece), use crowdsourcing as means of last resort, after all other diagnostic approaches have been exhausted. You may come up with nothing – well, no harm is done then. You may come up with a bunch of trivial ideas that you already tried and rejected – well, you know now that at least you haven’t missed something obvious. Or you may come across a suggestion that you never thought about – because it’s so unexpected and unusual. It might not work in the end, true, but it will push your thoughts in the direction you didn’t envision before.

Worse a try, if a patient’s life is in danger (if you ask me, a patient).

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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’, 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.

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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.

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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.

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