Let’s talk about the ‘F-word.’ Yes, we’re talking about ‘failure’. Despite calls to ‘fail fast and fail forward’, it remains a much-maligned occurrence and even a source of shame. Fortunately, this model might help to challenge that view.
Return on Failure is represented in a ratio, with the actionable learning and insights gained from a failed experience, over the resources you’ve invested into it.
REDUCE RESOURCES INVESTED.
Simple maths tells us that you can increase your RoF by reducing the resources invested into failure. This might include using Prototypes, generating a Minimum Viable Product, and simply finding ways to test out ideas quickly and cheaply before heavily investing in an option.
INCREASE LEARNING AND INSIGHTS.
Unfortunately, organisations and individuals alike prefer to ignore and brush over failure. By contrast, the other aspect of increasing RoF involves squeezing the maximum amount of learning and insights from the experience as possible.
If you’ve experienced a colossal failure, in fact especially when you have, you should be asking ‘how might I gain from this? What has it taught me?’ As Julian Birkinshaw and Martine Haas, the creators of this model, point out: “Failure is less painful when you extract the maximum value from it.”
Achieve that maximum value and learning by running a root cause analysis with the 5 Whys and/or Fishbone Diagram. You can also use deep reflective practices, such as Double Loop Learning, to reframe your failure as feedback and use it to challenge your hypothesis, mental models, and assumptions.
IN YOUR LATTICEWORK.
We’ve already mentioned how you can reduce investment by using Prototyping and Minimum Viable Product. You might also want to add Split Testing and even Agile Methodology into the mix for ways to invest less and learn more.
In terms of increasing learning, we’ve mentioned the 5 Whys, Fishbone Diagram, and Double Loop Learning. Other models worth considering include the Lean Startup, and of course the gold standard in learning — the Scientific Method.
In terms of learning from failure more broadly, this model plays well with Black Box Thinking. Finally, in terms of building deep lessons, consider how to use this approach to challenge your mental models and build a more effective Latticework of Mental Models.
Reframe how you view failure.
Use this model to reframe failure as something necessary and valuable to innovating and achieving anything worthwhile.
- Minimise your investment.
Consider how you might fail fast and cheaply by reducing your investment. Use Prototypes and Minimum Viable Products to gain feedback and fail with lower costs.
- Maximise your learning.
Take time to talk about failure and analyse it. Build in root cause analysis, reflection, and retros into your process so you’re constantly improving on what you did last time.
Challenge your mental models.
Rather than take superficial, discreet lessons about a failure, take the time to think about the broader consequences. Have a terrible clash with your child? Rather than just take a parenting lesson from it, consider how to increase your insights and RoF by considering how that lesson might apply in other contexts. Essentially you’re using the process to update and improve your mental models.
Share your learning.
Often you’ll be working in teams and collaborating — so be sure to uncover and share your learnings. Talking candidly about your failures and what you’ve learnt and do differently as a result, will provide value for others and help build your own credibility as a continuous learner.
Venture capital firms.
The original HBR article that outlined this model cited the example of Venture capital firms like Hoxton Ventures, who take half a day every quarter and consider their investments. They try to see beyond one big and notable success or failure, and seek out patterns and data to identify whether something should be considered as a failure and what can be learnt from it. The article quotes Silicon Valley investor Steve Jurvetson who noted that: “You have to strive for a process of decision making that over a large number of decisions gives good outcomes."
The Shuttle disaster.
We discussed the 2003 Columbia shuttle disaster in our Psychological Safety summary In Practice section. It was an example of how root cause analysis went beyond initial learning (that the tile on the shuttle was a weak point) and dug deeper into that tragic failure, revealing bigger lessons (that NASA had a blame-based culture of fear). It serves as an example of extracting deep lessons from big, in this case terrible, failures.
We couldn’t see many limitations with reframing, and gaining more value from failure. The only criticism of this model we could think of is that it is reasonably self-evident and of course is more a principle rather than something that you can put numbers to easily and calculate.
This term Return on Failure has been around for a while, indeed a 2011 Forbes article by Deborah Mills Scofield and Kristi Hedges defined it as ‘failure identification + failure analysis’ repeated over and over. However, we prefered the version put forward by Julian Birkinshaw and Martine Haas in this 2016 Harvard Business Review article.
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