Innovation Lessons Learned From Failure

Studies of innovation usually focus on success stories – what worked and therefore what others should do. The National Science Foundation (NSF), specifically the National Center for Science and Engineering Statistics (NCSES), has recently released a study that takes the opposite approach: what can we learn from failures. Carried out by team of researchers from Center for Innovation Strategy and Policy at SRI International, the study (Understanding Unsuccessful Innovation) looks at 19 case studies of failures (see list below) and pinpointed the root cause of the failure.

Of course, it is somewhat problematic to draw conclusions from such limited sample of case studies. But they do provide an illustration of the various ways that an innovation can fail. And it should be noted that not all of these “failures” ultimately turned out to really fail. Some of these pivoted to a different market use that originally conceived (often much more specialized and narrower than the original target market).

Thus, the framework developed is probably more important a finding than the statistical evidence provided.

The framework identifies five root causes of innovation failure:

No market demand. A product or business process was developed and brought to market, but there was little market demand for it.

Poor performance. A product or business process was developed and brought to market, but it failed to function as intended.

Insufficient complementary assets. A product or business process was developed and brought to market, but the adjacent business inputs required for its successful customer use were not sufficiently available.

Poorly defendable position. A product or business process was developed and brought to market and met with positive market interest, but the innovator was unable to secure the innovation’s market position, for example, by way of intellectual property protection.

Regulatory restriction. A product or business process was developed and brought to market, but regulatory restrictions on its use limited its economic value.

Note that the study includes a breakdown of the “no market demand” category into innovations that are not useful, price point that are too high for the market, failure to meet investment expectation, and wrong market targets.

Those failures can manifest itself during one of the three time periods of innovation: launch, growth, or maturity. The root cause failure, however, occurs one of the earlier 5 stages: ideation, product development, launch, growth, and maturity. The model thus is as follows:

The model helps pinpoint where the fail occurs, rather than when it occurs.

For example, the paper concludes that iTunes Ping failed during launch due to poor performance that was the result of failure in the product development stage (specifically not having a data-sharing agreement with Facebook in place). Hoverboards failed in the transition to maturity due to a poorly defendable position in the growth stage. Google Wallet failed in the growth stage due to insufficient complementary assets that should have been addressed during product development.

The Google Wallet case study (along with the Wii U, Google Glass, Segway, Iridium Satellite Phone, and other cases) points out one of the limitations of the study. Each of these innovations are still in use – either as part of another innovation (Google Wallet as part of Google Pay; Wii U as part of Nintendo Switch) or as a scaled back version (Google Glass, Segway, and Iridium Satellite Phone). Over half of the cases resulted in this pivoting of the innovation to new markets and/or new uses. A more complete study would look in greater depth at the process of pivoting from apparent failure to at last limited success.

Another concern with the study is its focus on a sole root cause of failure. It seems to me that the root causes are not mutually exclusive. For example, the failure of Segway seems to be a combination of no market demand (due to a high price point) and regulatory restrictions. A look at the multiple causes, and their interactions, would strengthen the model. Especially important is how the lack of complementary assets can create low market demand and poor performance.

I come away from reading the case studies with three insights. [Note that in keeping with my concern over the small sample size, my comments are based more on the model and the insights from the case studies rather than statistical analysis of the case studies.]

The first insight concerns the failure to meet a market demand. It should come as no surprise that no market demand, especially not useful, is a root cause of an innovation failure. Yet, most of our public policy seems to ignore that point. All innovations are seen as beneficial. Innovations fail because of the lack of funding or some other barrier to adoption – not because they are not useful. I call this the “electronic swizzle stick” syndrome:  just because we can build an internet-connected battery powered swizzle stick that can stir your cocktail in the perfect manner does not mean that there is a market need for such an item (although I keep watch to see if such a product appears in the airline in-flight catalogs). The Juicero case illustrates this point.

The second insight is that all of the causes of failure can be addressed somewhere in the innovation process. But the causes of failure need to be identified early and steps taken to avoid the failure. As the saying goes, an ounce of prevention is worth a pound of cure.

This maybe the hardest insight to operationalize. Such proactive measures do not come easily. The whole fail-fast ethos is built around the notion of rapid learning rather than pre-emptive action.

Fortunately for the rapid learning approach, the third insight from the case studies is that failure do not mean failure. As noted earlier, many of the innovations were at least partially implemented – just maybe not in the way or to the extent originally envisioned.

The study does not delve into policy proposals. As befitting its sponsor NCSES, the study looks at the implications of the model for statistics on innovation collected as part of the American Business Survey, and at issues for future research. Let me therefore speculate on some policy implications.

I believe there are public policy programs already in place to address the innovation failure. Directly targeted to the issue of market demand is the NSF’s I-Corps program (and its many offshoots). The I-Corps process forces innovators to confront real world applications and market needs. The Manufacturing Extension Partnership (MEP) and the Small Business Innovation Research (SBIR) – Small Business Technology Transfer (STTR) programs exist to address technical issues of poor function. But I-Corps reaches only a limited audience and MEP and SBIR/STTR programs are narrow in focus.

Let me suggest a more “rough and ready” approach. As part of any assistance to companies’ innovation activities a checklist could be consulted. It would a rudimentary checklist just to get people thinking about the possible problems just as the I-Corp process forces innovators to think realistically about the market needs. I realize that some may claim that this is just setting up another series of barriers to innovative activities – the creation of a way to say “no.” But it could be useful overcoming barriers by addressing the failure points proactively. And it could also force the naysayers to explain their objectives.

Obviously, such a checklist would not be a silver bullet to ensure that all innovations succeed. But it might be a small step toward helping prevent more innovations from failing due to a lack of foresight. Worth a try at least.

Case studies

  • Google Glass
  • Microsoft Windows Vista
  • Samsung Galaxy Note 7
  • iTunes Ping
  • DVD-Audio
  • Hoverboards
  • Boeing 737 MAX
  • Zozosuit
  • Juicero
  • Google+
  • Ubuntu Phone
  • Sedasys
  • Google Wallet
  • Segway
  • Iridium Satellite Phone
  • 3-D Television
  • Wii U
  • Laundroid
  • Sony BMG Extended Copy Protection (XCP)

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