Big Data, Small Insight, and Magic Beans

Big Data, Small Insight, and Magic Beans

Big Data, Small Insight, and Magic BeansMarketing and sales teams are spending more and more time and on the acquisition and processing of data. Yet I’m not sure that there is any clear correlation between the amount of data available, and the quantity and the quality of the insight created by these teams. Whilst there are of course many organizations who are bucking that trend, I wonder if too many organizations are focusing on big data and analytics, and not on insight creation.

A parable about big data, insight and magic beans

Once upon a time*, a king realized that to be truly successful and win all battles, he needed something special, and that something special was magic, and that magic came in the form of magic beans. He called his magic bean expert to the throne room, and demanded more magic beans.

“If we had a little more quality soil, then perhaps we could find more magic beans” suggested the advisor.

Sure enough better soil was acquired, and the magic bean expert found a few more beans. So the king ordered more soil to be delivered. And then more. Soon they were employing people to manage the soil, to make sure the soil was of the highest quality possible. An entire wing of the palace was given over to the Soil Management Department. The magic bean expert retired and wasn’t replaced because he didn’t really know much about soil management anyway.

Each day the king received reports on the quality of the soil; and any adviser who reported a deterioration in soil quality was soon to lose his head.

Reports came in that other kingdoms were acquiring more soil. The king demanded more.

“We will have more soil, and better quality soil than anyone else in the world” he demanded.

And so the people of the kingdom came to revere soil. They became the best soil managers in the world. They won awards, and built monuments to the greatest soil managers of their time.

And as for the beans? Well… who needs magic beans when you have the best soil in the world?

So enough on beans and soil: just as kings need to focus on magic beans and not soil; marketers need to focus on insights and not data (no matter how beautiful and plentiful that data is). So how should a marketing or sales leader ensure that his team keep focused on insights, and don’t lose themselves in big data?

How to keep the focus on high value insights and not just on data

  • Be careful what you call an insight. It appears that anything can be an insight these days. Noticing that people who buy chips also buy beer is labelled an insight. Is it? If it is, then any observation about behavior could be. For me, it has to be new, it has to have that whiff of surprise, and it has to lead to massive change versus what has gone before. Challenge your team as to what they really mean by an insight, and guard the use of the word jealously.
  • Measure the returns on soil management. Don’t get me wrong, data is great. But it isn’t everything. Like any investment the returns need to be measurable and measured. Ensure that the KPIs refer to the insights and their value, rather than merely the management of the data you have.
  • Acquire with care. Most data could, in theory, add value. But in my experience, most of the data organizations have is barely used. Before acquiring more data, check that current data is being used as much as it can, and create a plan (which can be reviewed) as to how the new data will be used, by who, and when.
  • Keep an eye on data redundancy. More and more potential data sources become available every day. To keep up the resources and funds to manage it would have to increase perpetually, which isn’t desirable or practical. Consistently reviewing data sources against their historic and future application is key (and by this I mean their actual usage and value, not just the theory)
  • Blend in qualitative. Qualitative research seems to have been relegated somewhat in this world of big data, yet without qualitative research, quantitative research often lacks the ‘why’ required to be a big insight. The recent example of L’Oreal’s Ombre launch, built out of analyzing search data, has its roots in qualitative observation of what was happening on fashion runways and in salons.

Data is one thing. Analysis is another. Insight is quite another. Are your team getting the best insight out of the data they have? Let me know what you think in the comments below.

*courtesy and kudos to the excellent Colin Harper for getting me started on magic beans, which he may now regret!

 

Image: Flickr

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