Failure is a strange thing in innovation management nowadays.
For established like corporations, failure is something they try to engineer out of their processes, since failure of a project (even an innovation project) reflects badly on the company financially, as well as the people who suggested it and approved it.
However, in the world of startups and entrepreneurs, failure is sometimes seen as a necessity.
Check out the video above to see what I am talking about.
Companies will spout phrases like “Fail Fast” or “Move Fast and Break Things”.
Many founders even see past failure as a badge of honour, as it shows they tried something.
But all of these situations still treat failure the same way:
They assume that a failure is an end point.
Something failed (whether it was a launch, new idea or experiment), and therefore the team knows that it wasn’t good, and should move on.
However, what I teach clients is fundamentally different.
I teach that the perception of failure can immediately change if you reframe it in the way that a scientist looks at an experiment.
Traditional view of failure: A failure is an end state, after which nothing more should happen.
Scientist’s view of failure: A failed experiment provides valuable information on what doesn’t work about the current solution, which can be used to improve the next version of the solution.
The core principle is about validation and progress.
If you were to set up your “experiment” to be 100% dependent on the success of a single result (such as a launch of a new product), then there is very little margin for error. This is how many large companies still approach their innovation challenges, where they will work for months (sometimes years) developing them in-house before they are “ready” to be released to the world. If the market then doesn’t see the value in them and the launch doesn’t return the required investment, then all of the work leading up to it was in vain. This would ultimately count as a true failure. And unfortunately, up to 96% of all innovation projects actually end up failing in this way.
On the other hand, by adopting the perspective of a scientist, you can reframe the work and emphasis that happens before the final launch.
If you have a hypothesis about how the innovation will add value, then with a scientist’s mindset, you can perform a large number of small experiments to either validate (prove) or invalidate (disprove) your hypothesis.
No matter the result of each experiment (success / proven, or failure / disproven), each result is a point of data which gets you closer to an improved final solution. Importantly, the experiments should assess action and reaction to something (like whether people will pay money in advance), rather than just asking people for their opinions (which usually have no correlation on how those people would actually act).
This is where the change in perspective truly adds value.
Each experiment gets your innovation closer to what the customer actually cares about, and further away from what they don’t care about.
If you continually run lots of small experiments throughout the development of your innovation, you will have built up a large body of validation as to what works and what doesn’t. This means that by the time you are finally ready to launch your innovation, it is much more likely to be accepted by the end customer.
And even after the launch, a mindset of experimentation will allow the team to continue gathering feedback to continue improving the solution into the future, making it even more valuable as time goes on.
So how can you run so many small experiments? Of course, it will vary by industry, but here are a few recommendations:
- Go out into the field and validate your initial assumptions with target customers, before even beginning design or development.
- Bring in people to test prototypes
- Accept advance orders and measure uptake
- Use landing pages and small advertising budgets ($100 or so) to test whether people are interested enough in a concept to want to find out about the solution
- Use split testing to see which messages resonate more with target users
- Bring target customers and existing customers into the design process
- Do a small scale local test pilot in a specific region to see how the market reacts.
There are many more ways to run experiments. Ask your team how they would suggest doing it.
But most importantly, go out there, get your (metaphorical) lab coat on, and start doing some more experiments.
What experiments have you run to validate your innovation? Let me know in the comments below.
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