The devil lies in the data.

Research and effectiveness of proposed design solutions was driven very differently when I studied design 20 years ago, than what I see around me today. It should be, since ‘how’ the world consumes has changed considerably. We used (and still use) a precarious combination of qualitative and quantitative research to evaluate the success of proposed design solutions. We tested on users, tweaked and fixed, then tested our hypotheses again before we refined, tweaked and tested yet again. That however is now replaced by ‘drop-off rates’, ‘reach’,’clicks’ and ‘hits’. The D word. Data.

We once had a client for whom we had done some branding & packaging who asked us to use specific colours on our packaging design because they ‘worked’ on the web. Out of the window went hours of conceptualisation, debate & discussion on perceived connotations & associations with the colours chosen. We were being asked to pick colours based on what was ‘popular’. I was flummoxed to say the least. We were being asked to throw out our commitment to the brand idea (the very one we were asked to create), its’ values, and create packaging that was a huge departure from what our research indicated (and what we had agreed) would convey our brand values in the best way possible.

‘Data’ is a blessing when used discerningly, and catastrophic when interpreted as a sure-shot route to success. One needs to strike a balance between the qualitative and quantitative.

Our design process is very welcoming of consumer and market research. These methods have their flaws too, but it’s the best known guidance we have that is indicative of consumer mindsets, and so we interpret it with careful judgement, rarely applying it in its’ absolute form. The new age of instagram and digital marketing has enabled gathering a whole host of very useful insights and information. But data has always presented itself in multiple forms: surveys, white papers, academic writing, consumer feedback, historical patterns observed and documented, user studies, and external validation of a concept by proof of its existence elsewhere. The more dangerous type is finding a ‘consensus’ based on arbitrary groups (friends & family). Yet we as designers embrace all of these findings as a part of the many elements in consideration whilst designing for brands. The key word being ‘consideration’.

What happens when all businesses in the same sector and price band make the same inferences, with the same information?

Albert Einstein is widely credited with the saying, “The definition of insanity is doing the same thing over and over again, but expecting different results.”

This could be interpreted to say that if many are doing the exact same thing, expecting a different result would be foolish. Every business that considers data valuable can gain access to it. In fact, so much of it is available freely in the public domain. The approach isn’t ingenious, certainly not when so many businesses are led by e-commerce. Numerous other brands would have thought of the same route to satiate the majority. If the data/findings are the same for many/all in the sector, then it would be safe to assume the output would be similar, playing to the same consensus, or based on the same data sets.

This method inhibits disruptive ideation, and that obstructs branding studios from fulfilling their mandate to the best of their abilities. Putting it extremely, that’s like asking a creative team to flog a dead horse differently, in the hope of a different outcome. The creative output of any brief, is only as good as the inputs.

Thinking back to some of the biggest innovations in history - so many of them were a result of deviations from standard protocols and/or serendipitous accidents. They were a result of ‘lateral thinking’, which according to Edward De Bono (who incidentally invented this term) was defined as problem-solving using indirect reasoning, or methods that are not obvious using traditional logic.

While data should enable lateral thinking, the reality is that business owners hold design studios ransom to these findings. This could stifle the possibility of creative lateral thinking (design output) that may not be obvious. Innovation will be evaded.

As a design studio that is regularly presented with consensus-based-feedback, it becomes very hard to make a case for going a different way - For instance, how do you explain WHY surprise should be an integral part of the packaging experience? How do you support that surprise adds to memorability? Surprise can underline the very nature of the brand personality we wish for a consumer to identify us with. The very definition of the word ‘surprise’ is ‘the unexpected’ - and research can rarely support that which is unexpected, or in other words, never been done before. Research is based on evidence of historic behaviour. Therefore it can not predict what innovations will work. This is where the designer’s judgement and experience needs to come into play.

At the core of this is a simple four-letter F word:

Fear.

Fear of failure. Fear of rejection. Fear of mediocrity. It’s at the heart of entrepreneurship, and it’s also the one thing that can hurt it most. R.L Adams, author of ‘Entrepreneurship and small business’ says in this article that ‘You’ll always play it safe when you’re living in fear’. That in itself is the danger.

Fear doesn’t create unicorns. Isn’t that an injustice to the massive risks taken to bootstrap a business to begin with? It’s an injustice to the sacrifices made to give up that corporate job and take the supposed foolish plunge into entrepreneurship. It’s an injustice to the expertise of the team you have so carefully handpicked. It’s an injustice to the pivot that you’re considering, or the new vertical you’re betting on with your pre-existing business. It’s an injustice to the legacy left to you by your forefathers.

Idealistic as it may be, businesses will do themselves a favour by not playing into the hands of this particular devil. Stop the injustice.