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Challenges with Data Driven Decision Making


Randy Bean and the Wavestone team have delivered another fascinating set of insights into the organizational dynamics of “Delivering Business Value from Data and Analytics Investments”.

Coincidentally, this is the subtitle title of their latest annual data leadership survey.

Whilst “data, and the ability to make sense of it, has been one of the greatest drivers of innovation in both business and society in recent decades”, big challenges remain in making “data driven decision making” a Business As-Usual operating model.

How do we develop/change individual habits to use data insights for decision making, rather than rely on the HiPPO (the highest paid person’s opinion)?

Despite the continued heavy investments in data technologies and techniques, the human side of data continues to challenge companies. A massive 79.8% report that “cultural issues” are the greatest obstacles to realizing business value from data initiatives.  Every year, we hear the same reports that the principal challenges to becoming a data-driven organization are human—culture, people, process, or organization—rather than technological.

Paradoxically, it seems that too much of the focus of data executives is on non-human issues — data modernization (modern databases), data products, AI and ML, data quality, and various data architectures. All sounds a bit like an overly technical focus to a problem we seem to all admit is not primarily a technical one!

Less than 2% of respondents ranked “data literacy” as their top investment priority. But that may be because this is such an awful, pejorative term. I suggest we would be better to refer to “data habits” and the Change Management required to acquire and develop them!

Investments in data and analytics capabilities and initiatives are greater than ever, but organizations are coming to the growing realization that embedding these capabilities within their firms and transforming the cultures of their organizations will take time.

If we are not delivering business value in some measurable form in short cycles, what have we accomplished and what should we be doing differently?

I worry somewhat that the rise of the Chief Data Officer (CDO) and Chief Data & Analytics Officer (CDAO) may be counter-productive in this regard.  It may be an essential role to spearhead the required broad change initiative, but in many cases, I think we run the risk of CxO proliferation that reminds me of the rise of “Chief Electricity Officers” in the late 19th century. As electricity became a utility, a shared resource essential to business operations but inconsequential to competitive differentiation, it no longer required a separate staff to watch over it. It became a routine and largely invisible element of operations, marketing, product development, purchasing, and other traditional functions. Chief electricity officers disappeared, their work complete.

We should aspire to a state where “Data is everyone’s business. It IS the business”.

The challenge we have is that the very separation of “data” topics to a perceived “Ivory tower” may paradoxically reduce the chances of success in driving the required business outcomes on a broad scale.

Perhaps this accounts for the low level of overall success of the CDO/CDAO function found in the survey.

Surely the answer is to focus on solving business problems and harnessing opportunities fast and effectively?

Lets make the data insights discussion a business conversation with business context.

And to bring things full circle, the context of data is “end to end business process”.

You can read the Wavestone survey results and report here . . .

Thanks for reading . . .