Demystifying Innovation

It’s time to cut the cord between “innovation” and “failure”

One of the biggest challenges with embarking on any innovation initiative in a large financial services organisation is the inherent risk of failure. Our relationship with the word “failure” is both institutionally and emotionally charged; the term is embedded into the wordstock of financial services inside concepts such as “banking failure” (the collapse of trust supporting an entire institution), trade and settlement failure , regulatory failure , investment failure and operational, systemic and technical (IT) risk failure.

“Failure” is a toxic term in large financial services organisations.

When we begin to talk about innovation-driven change in financial services, we learn that small startups have a different relationship with failure; they routinely “embrace failure” and are “failing forward”. We learn that we can’t be truly innovative if we can’t fail. Which is where the story usually ends. We might be ok with failure, but that means nothing if our peers, bosses and shareholders can’t do the same, because our job security depend on forgiveness of failure.

So we outsource innovation instead. We organise hackathons and we toy with the idea of buying overinflated startups. Or we avoid any risk at all by simply sponsoring innovation events and simply market ourselves as innovative: innovation astroturfing.

But the truth is that “failure” in the context of innovation does not mean being any less fixated on success. Nor does it mean “trial and error”, abusing responsibility for outcomes or abandoning discipline or standards. In innovation engineering, we find creative ways to create intelligent business experiments based around hypothetical customer-driven outcomes (aka hypotheses). We use rigorous, disciplined scientific method to conduct these experiments, exploring all possible attempts to make the idea fail, using deductive reasoning rather than inductive reasoning.

The process looks something like this:

• Define a question
• Gather information and resources (observe)
• Form an explanatory hypothesis (design an experiment)
• Test the hypothesis and collect data in a reproducible manner (perform the experiment)
• Analyze and interpret the data, draw conclusions, make small changes
• Return to step 3

Where we are able to disprove the hypothesis, to cause it to fail, we discard it and move on to another experiment. And we do this by testing early and widely, securing faster, more accurate feedback, and in doing so, we tune and calibrate a business and its software solution to become much more successful much more quickly. This kind of “safe-to-fail” experiment does not sacrifice the potentially creative response to a business opportunity, instead it provides a platform for creativity that is methodical, disciplined and transparent.

So failure in the innovation sense really means learning.

When combined with other innovation engineering methods such as value driven analysis, flow, controlled change and minimising work in progress to maintain cadence, such an approach can be incredibly powerful in realising successful innovation in risk averse, highly disciplined environments such as corporate financial services.

The main challenge to applying successful financial services innovation remains linguistic: decoupling the idea of “innovation” from the negatively pre-loaded “failure”. We suggest removing “failing” from the lexicon of innovation engineering and replacing it with “learning”.