If culture eats data strategy for breakfast, what’s for lunch?


If culture eats data strategy for breakfast, what’s for lunch?

With the democratization of data, open source tools and everyone hiring data scientists, what is left to differentiate on?

Implementation of a well laid-out business strategy is unfortunately effectively hindered by an organization that is not ready to adapt.

Who is to blame?

When the dust has settled, the history-writing is often focused on the shortcomings of the strategy or the ones responsible for the implementation. The outcome is that everyone else can keep calm and carry on. Status quo remains, and relief can spread.

With this context, what is different when implementing a data strategy?

A new initiative in your organization that aims to capitalize on the new opportunities within analytics and data science might be a welcome initiative in a traditional business that is struggling with growth - at least so in the boardroom. Hiring some data scientists, create an analytics team and let them have a go at your massive datasets could be a natural starting point.

But what are the odds of this bringing in new revenue streams or the less radical hope of many: reviving the existing products and services, or bringing efficiencies and massive cost reductions?

How to succeed

For a new initiative to succeed there are basically one of two prerequisites that must be in place:

1.    Your organization already has an innovative, agile, test-and-learn culture. 
2.    You set up a separate entity, disconnected from “business as usual” with the mandate to innovate and possibly disrupt the current business and cash flow/cow.

If none of this is true, you will see your data strategy consumed by old traditional inner friction by the residing culture. Your talented and ambitious data scientists will soon get bored and start calculating their next career move.

The sexiest job on the planet alone can´t save the party

Frustrating as it is, even when applying the latest technology involving the sexiest job on the planet (Harvard Business Review, Oct. 2012), some things remain. The reason why disruptors overrun incumbents, typically at every technology change, is not their new take on technology, methods and competency alone. The reason for their winning combination of these elements is their culture of agile development, pragmatic use of any tools available, test and learn approach and genuine excitement of what is possible now, not in 2020. So, getting carried away by one of the parts alone, a specific tool, method or hardware, will bring you nothing near of halfway to the speed of your competition.

Support and set free

The foundation must be an environment that is receptive and supportive of the new things your data scientist can spin out - or there must be no environment at all. Meaning, provide the resources and support for the analytics team to have a new business unit they can build up from scratch and get out of their way. Then follow up like a startup investor. After all, the secret sauce is still culture.