Big Data is receiving a lot of attention and investment at the moment, with the combination of technology and analytics generating enormous possibility. As Greg Satell rightly points out, businesses that neglect Big Data will be left behind.
Data, and smart ways of generation, can potentially identify new patterns as well as test new hypotheses and simulations. So data are extremely useful, and Big Data will help enormously; but it’s not the concept itself, it’s what it will enable companies to do.
It’s also essential to bring qualitative knowledge and understanding to complement quantitative data; indeed some of the richest sources come from ethnography, observing what customers actually do. This should be a core activity but, as Jorge Barba suggests, it may not be widespread very soon.
It starts to become interesting when we recognise that data bring knowledge and understanding. This is when we can start answering the “why” questions with “because” answers based on data. It becomes really exciting when we take the understanding from quantitative and qualitative sources and deduce insight. There are many definitions of a consumer or customer insight. I like these:
- “A revelatory breakthrough in your understanding of people’s lives that directs you to new ways in which to serve your customers better” – Helen Edwards
- “A key piece of in-depth understanding about a target audience that will unlock a true business potential” – Christian Dossel
- “Wow, you really understand me, better than I understand myself.” - Brainjuicer
And the best way to describe the impact comes from Jeremy Bullmore. Why is a good insight like a refrigerator? Because the moment you look into it, a light comes on.
A good example of an insight came over forty years ago from Theodore Levitt: “people don’t want quarter-inch drills, they want quarter-inch holes.” In one category on which I worked, a revelatory insight was that consumers didn’t really care about all the features, benefits and claims in the same way we did. What really bothered them was when the product didn’t work as well as they expected it to. They didn’t expect wonder and delight, they wanted no problems. It sounds simple, but this insight became the foundation for a highly successful advertising campaign and a series of product innovations.
With Pampers, P&G had always assumed that a lack of leaks when the baby was active was the key benefit of nappies/diapers. They then realized that whenever a wet baby started to cry at night, the parents were also disturbed. The insight was that sleep for the parents is the key benefit and they adjusted their innovation program accordingly.
Insights should then act as inspiration for ideas. Of course there are many other sources of inspiration for ideas. A great technology may excite the innovator, invention can be original and creativity is very effective. Whatever the source, an idea is much more likely to succeed if it is based on a relevant insight that resonates with the consumer or customer. Indeed it could be argued that an original insight is more valuable than an original idea.
Whilst there is no inherent advantage in quantitative data per se, there are ways in which data can provide competitive advantage, for example if one company can gain exclusive access to data sets that provide unique knowledge. Ethnography brings the potential for advantage as subjectivity and interpretation are involved; so the companies that do it well may have more understanding to generate superior insights. In general though, I suggest that long-term competitive advantage is less likely to come from data or knowledge. It will become a “qualifier”; something you must have to play the game and will leave you at a disadvantage if you don’t have it.
What about radical innovation where the end customer has no experience of the product?Insights are still fundamental, whether generated at a pre-development stage or when testing prototypes. It’s another good reason to get to the minimum viable prototype as soon as possible.
The best ideas become projects that, if executed well, go on to become successful innovation. Data are very important but are not an end; they are the means to generate insights. They can model and simulate scenarios, and thus help to estimate the potential revenue; but it’s the insights that differentiate innovation.
image credit: thoughtful image from bigstock
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Kevin McFarthing runs the Innovation Fixer consultancy, helping companies to improve the output and efficiency of their innovation, and to implement Open Innovation. He spent 17 years with Reckitt Benckiser in innovation leadership positions, and also has experience in life sciences.