Great point about creating financial incentives for participants who aren’t just “looking for contracts”. As you correctly infer, there really aren’t available funds for providing direct compensation to innovators — not to mention the fact that it’s hard to properly value an idea if it isn’t directly connected to some sort of end application. The way that a lot of government organizations have gotten around this is by creating crowdsourcing competitions with a lump sum of cash given to the contributor who offers the best idea for solving a specific problem that the organization is facing (e.g., we will give $10,000 to whomever comes up with the best design for the newly renovated city hall).
What’s challenging for the MBTA is that there are so many issues facing the organization that no one problem merits its own crowdsourcing competition, per se. What is more valuable to the organization is the ability to field a lot of ideas that touch many different areas of the organization, then implementing the ideas that are feasible to execute and produce some sort of tangible benefit to the organization. Which still begs the question of how to compensation the generators of these ideas — maybe the next innovation challenge should be to field ideas on how to properly compensate contributors!
Thank you for laying out so thoughtfully such an important problem facing Facebook and our society in general.
The most intriguing part of your essay arrives near the end during your discussion of the “echo chamber” effect. This effect is in fact created intentionally by Facebook’s algorithm — Facebook engineers have designed the news feed algorithm with the specific intent of giving you more of what they think you want to see. Bad actors who wish to spread fake news exploit this algorithm by creating polarizing content that those at the far ends of the distribution are more likely to read, share, and react to, which in turn makes those same people more likely to receive similar content.
As a result, it seems to me that Facebook is in some ways battling itself on this issue. Constantly supplying new training data so that Facebook engineers can refine their fake news-detecting algorithms will be a continuous uphill fight. The simplest solution would be for Facebook to use a separate news feed algorithm for sharing news articles versus the one used for curating friends’ statuses and photos, an algorithm that selects news articles from a set of pre-approved and accredited news sources (not according to “likeliness to read”). That would mark a return to the old-fashioned days when the set of available news sources was much narrower in scope. But alas, I doubt Facebook would do something so drastic that could impact their growth and profitability.
Thank you for providing a glimpse into how additive manufacturing (AM) is being employed by one of the premier advanced manufacturers in the world.
The challenge you highlight for Siemens at the end of your post – determining which applications will not benefit from additive manufacturing due to structural factors – seems to be the most pressing one, not just for Siemens but for all who hope to take advantage of this new technology. Thus, I found Siemens’ roll-out of its additive manufacturing network (AMN) to be impressively strategic. By hosting a co-innovation platform for designers, engineers, and producers to collaborate on the various applications in which AM might be successful, Siemens is gathering some very valuable market intelligence (and if I’m not mistaken, people either voluntarily join or pay Siemens to participate!). I’m curious as to how successful Siemens has been in attracting collaborators onto AMN, given potential concerns around intellectual property and proper compensation for contributors’ ideas.
Nike’s use of 3D printing in its rapid prototyping process is fascinating and makes a lot of sense for executing upon the two pillars of the “Triple Double” strategy that you mention, 2X Innovation and 2X Speed. By speeding up the prototyping process, Nike can experiment and bring innovative products to market much faster. But I think you pose a very important question at the end of your post — to what extent can Nike really utilize this new technology to execute upon the 2X Direct promise for consumers?
Given current constraints on additive manufacturing in terms of cost and scale-ability, Nike may risk disillusioning customers by marketing this technology too quickly and causing consumer expectations to exceed reality. Nike does want to showcase how it is innovating with 3D printing in certain ways (e.g., prototyping and creating custom shoes for elite athletes), but the company has to strike a delicate balance between creating excitement among loyal customers and creating unrealistic expectations in the short term.
I found your discussion of Heineken’s “Idea generation” vs. “Idea selection” innovation framework to be very helpful for understanding how a large company like Heineken can capitalize on open innovation opportunities. However, I disagree with you recommendation that Heineken devote a greater share of its innovation efforts to the bottom right quadrant of the matrix, “Approval contests” in which ideas are generated internally by Heineken and then subjected to some sort of popularity contest among consumers.
As a Food & Beverage/CPG company in mature market, I consider Heineken’s primary challenge to be innovating outside of its current product categories and into new or adjacent categories in which there is more opportunity to gain market share. The problem with internal idea generation is that you limit the scope of possibilities a priori before you engage with the outside world — you pick the options first and then present them to consumers. In my opinion, the primary advantage of open innovation is that it allows a company to field ideas that are far outside its previously conceived realm of possibility. These kinds of ideas provide the basis for the kinds of groundbreaking innovations that could enable Heineken to achieve step-function growth in the face of a maturing market.
I agree that WHOOP should begin to release its data publicly, perhaps in a controlled fashion to credible researchers. In my opinion, the company’s primary competitive advantage is in its proprietary algorithms that translate a wearer’s health data into meaningful and informative metrics like “Strain” and “Recovery” — not in the quantity or quality of the data collection itself. Thus, WHOOP could benefit from releasing these data to a broader audience in order to gather valuable external feedback how accurate their predictive claims on health measures like “Strain” and “Recovery” are, without compromising their competitive advantage in the marketplace. And in turn, the company could work to refine its algorithms to increase their predictive power on health outcomes.
It seems that Airbnb uses its customer feedback platform(s) as a forum for open innovation, with ideas that are sourced from hosts and users. I’m curious as to the “intrinsic” motivations that these hosts and users have to contribute their recommendations outside of “extrinsic” motivations like financial reward, as Airbnb does not seem to compensate contributors for the innovations they incorporate into their business model. Does Airbnb provide any form of recognition to the hosts and users whose ideas they incorporate into product changes?
Furthermore, while customer feedback is always important for a company that wants to continually refine its products and services to maximize customer value, I might worry that relying too heavily on these forums would give the company an unrepresentative view of their customers’ pain points. To overcome this, most companies (perhaps Airbnb as well) typically perform market research surveys that gather feedback from a representative sample of customers — that way, a company’s view of what customers care about is moderated by the proportion of the customer base they represent and not distorted by a disproportionate response rate from “super hosts” and “super end users”.