Failing, Learning, Innovating

From startups in Silicon Valley to big tech companies and corporate innovation hubs: It seems that “failing” is widely accepted these days. Entrepreneurs celebrate “Fuckup nights” and startup employees are excited about how they “embrace failure”. Sounds like a relaxed way of working, right? No responsibility, no accountability, no consequences. The opposite is the case. But let’s start from the beginning.

Today’s business environments are characterized by a high level of uncertainty. Accelerating technological progress, blurring industry boundaries, volatile markets and increasing regulation, to name only a few aspects. In this context, innovating means leaving the familiar ground behind and entering unknown terrain. The more ambitious you are, the more radical your ideas are, the further you have to leave your comfort zone. Past experience does not provide you with good guidance anymore and traditional tools might no longer be appropriate. The consequences of your actions are highly uncertain.

In this setup, failure – in the sense that “things do not work out as intended” – is unavoidable. What sets successful innovators apart from the average is how they fail. Companies like Google or Amazon have strict mechanisms and metrics in place that ensure that they fail fast, cheap and – most important – that they extract as much relevant insights as possible out of failure. Some of these companies advertise their “failure culture”. However, even more, all of them foster a strong “learning culture”. Navigating in uncertain terrain, they focus on quickly learning everything they need to finally succeed. In fact, these companies compete on the rate of structured experimentation, learning, and acting on learnings. In doing so, they acknowledge that some ideas will not work out, will fail.

Harvard Professor Gary Pisano characterizes such learning cultures with two main elements (see Link): First, a “tolerance for failure, but no tolerance for incompetence,” and second, a “willingness to experiment, but highly disciplined.” A Google manager will accept failure if, despite reasonable assumptions and promising first customer feedback, the development of a new product is stopped once the success indicators turn red. At the same time, he will not accept failure due to sloppy market analysis, missing customer involvement or ignorance of technical problems. Also, he will drive experimentation with new product ideas, however, always in controlled and structured ways, directed to maximize relevant learning.

At ZEISS Digital Innovation Partners, we also aim for a strong learning culture. And as a part of that, we accept that sometimes, things do not work out as initially planned.

Every project is conducted with our partners form the ZEISS Business and starts with a product- or service idea. The first step is usually to identify underlying assumptions for success, in the three dimensions feasibility (tech), desirability (customer need) and viability (business). A critical assumption for a personalized product recommendation service would be the availability of necessary input data for the recommendation engine (feasibility). Furthermore, customers would need to be interested in receiving respective recommendations in the first place (desirability). Finally, we would assume that the service benefits our business (viability). The next step is to validate the assumptions, for example by assessing the availability and quality of data, conducting interviews with potential customers and calculating a business case. Working in sprints, we timebox this validation phase to focus on the essential questions. If we can confirm all assumption, we move on. If not, we might agree to stop our activities, or – much more often the case – adjust the scope of the product / service according to what we have learnt. Similarly, we continue to iteratively build the product. Start with basic and most essential functionalities, test them with potential customers, incorporate our learnings. Formulating reasonable and testable success indicators help to verify progress. After every iteration, an open discussion is necessary regarding next steps – and at every point there needs to be the possibility to stop the project or to significantly pivot if success indicators are not met anymore.

It is painful to realize that an innovation project that started promising turns out to not meet the expectations anymore. Agreeing to eventually stop it early on might feel like failure. However – and this is the whole point around a failure culture – it is okay, it is actually the only right thing to do. After acknowledging that the initial plan did not work out, there is the possibility to formulate a new product idea based on all the insights from the past weeks. The good thing: Now you start with a much better understanding of what you are doing and where you want to go. What has been unknown terrain three months ago is now familiar ground. For me, innovation is fun – but it is definitely not relaxed. It is hard work that requires high levels of commitment, discipline and critical thinking from everyone involved. In the end, I personally do not care if people celebrate failure or learning – as long as those are two sides of the same medal. What I do care about, however, is that people accept failures as a fact in innovation activities. As long as you learn from them, they are not bad at all.

© Sergey Nivens – stock.adobe.com

About Post Author

Alexander Sayer

Alex joined Digital Innovation Partners in early 2019. As a Business Analyst, he spends his days thinking about new business models, interviewing potential customers and coordinating development activities. He enjoys working in close collaboration with his tech and design colleagues, because “sometimes it feels like they can do magic”. In his leisure time you will probably find him in the mountains, hiking, skiing or eating Kaiserschmarrn.

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