Activating Innovation: diversity & experimentation

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The benefits of diversity in the workforce are widely documented.

Opinion Piece by Analah Fawcett, Principal Consultant, CSR Lead

Gender diversity within research and development teams is positively related to radical innovation and having innovators who better understand your marketplace – by representing the diversity of potential customers – is only logical.

In fact, just being in the presence of someone different to you, makes you think differently; it helps to make the invisible visible.

While it seems simple – and to a large extent it is – it’s not enough to only include diversity at the conception phase of an innovation or product life cycle.

Let’s explore the role of experimentation.

We know to innovate you must experiment, and to lower the risk of innovation we want to fail fast. The problem here is we often set ourselves up to fail, even when we succeed.

Unconscious – and in particular, confirmation – bias plays a big part in this, and without ensuring diversity in experimentation design to help challenge it, companies can find out far too late what they could have realised early on: the idea should have been killed.

A solution to this is the ‘killer experiment’.

As Albert Einstein said, “No amount of experimentation can ever prove me right, but a single experiment can prove me wrong.

To avoid wasting time and money (and to achieve the fast fails that you want) innovators need to design a killer ‘killer experiment’ – which requires diversity in thought – to create ‘the one’ that will successfully set you up to fail.

This allows you – if you do fail – to adapt or move on to something else that will produce a worthy return on investment.

Once designed, undertake your experiment on a diverse audience to ensure different perspectives and experiences are represented and tested.

Listening to the ‘siren call of sameness’ as they say, will not allow you to find that ‘single experiment’, and without it you may run into disappointment after the implementation phase, when faced with incorrect product distribution and poor adoption.

And if you succeed? All the better.

How can I find out more?

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