3 Challenges of Big Data in Boardroom Decision-Making

Kerie Kerstetter

A strong majority of companies are now relying on big data analytics in understanding customer needs and formulating concurrent strategies. Nearly 60 percent of companies are at this point, according to a 2018 study by Dresner Advisory Services.

"This trend shows a strong indication of mainstream adoption," says Vice President and Research Director Jim Ericson.

Even as organizations increasingly find themselves relying on big data, it remains a complex resource to leverage effectively. It's hard to distill critical insights—from what is often a massive pool of data—in time to act. Simply collecting relevant, high-quality metrics can be a challenge in an age when information flows at unprecedented speeds. Gartner Research found that up to 85% of big data projects fail, not because the technology wasn't up to scratch, but because teams are generally ill-prepared to interpret and leverage the information. In other words, they fail to address the three pivotal pitfalls in effectively synthesizing actionable insights:

  1. Failure to achieve a holistic vision for data analytics.
  2. Inability to implement the insights from analytics across the entire organization.
  3. Lack of proper presentation of these insights at the board level.

Boards Need a Holistic Vision for Big Data

Before diving into the data, board members must decide what exactly they wish to learn. It's easy to wind up with poor results if questions are not carefully honed for useful answers. Asking very broad questions yields answers that lack the specificity needed to be applicable. Asking very specific questions often leads to answers that lack sufficient context.

How directors and their advisers choose to frame their questions plays a critical role in formulating a holistic strategy with which to approach their analysis. Decision-makers and their advisers must afford proper consideration for the intent of their analysis and the context (of internal and external conditions) acting upon their search for data.

In most cases, an effective application of big data is one which is successful in informing boardroom decision-making—either supporting a course of action upon which directors are already deliberating or laying a new course of action on the table for consideration. This almost always requires a comprehensive understanding of market conditions, competitive behaviors, strategic positioning, and other such factors which contribute to the development of a holistic vision for the analysis of "big data".

Implementation Across the Organization

In the modern information environment, no company can indefinitely sustain silos of information within any single department. Acting upon an actionable insight is a team effort.

Insights should set management moving to make changes, getting the complementary information from various departments and setting priorities so a cross-organizational effort is made to address changes as efficiently and effectively as possible. Too many companies simply set goals without providing the means to reach them, as Gartner Research is quick to point out.

Acting quickly and effectively on big data from the top down will almost certainly involve a change of organizational culture. Businesses often lack a culture that is focused on the type of trends and insights that the data provides. Then, when data initiatives are put into motion, they fail because the organization is not able to adapt to this new decision-making process. Given ideas, but lacking the sense of how to make them work, some executives simply make a half-hearted effort.

It is, of course, difficult to benchmark culture as one might benchmark production volume or profit margins. The strongest way to impose cultural change is, first, for the leadership to adopt it themselves, and second, for management to work closely with each part of the organization where change is needed.

"You can't build a culture of analytics in a short time," warns SAS Software. It is, however, possible to become an organization that an organization that puts analytics and business intelligence at the forefront of its decision-making; one which is supported at all levels in acting upon that intelligence.

To achieve this, management needs a kind of feedback loop that goes from mid-level management right to the top leadership. Find out where the issues are, right from where they occur. Mid-level managers, for example often see not only the problems but the fastest route to solving them. Giving them the benefit of insights driven from the data might save time and money.

Presenting Insights in the Boardroom

Finally, there is no use in getting insights from the data based on good questions from the board, and then returning to the board with the answers that the board won't even be bothered to read. Insights must be presented in a form that board members—who are gravely pressured for time—can understand quickly and digest easily.

Directors demand clear relevance to issues right from the start, if they are to keep reading. Presentation of insights should begin with identification of the issue in question, with a short breakdown of the what, where and why. Then, in a nutshell, the presentation should explain what the solution proposed is and why it will work. What's needed is a "story," that is, a coherent piece of intelligence which does not support the positive side of the issue without also considering the potential negative effects.

The rest of the story should consist of a balanced presentation of the prospective solution and the consequent risks of adopting it. This balanced narrative should then be backed up with information based on the data. In this way, the board can, without wasting time, take up the issue, discuss it and make a decision.

Most board members will then be able to start discussing the insight and its attendant proposal without difficulty. The result should be a decision at the board level that management can then put right to work.

When boards and management take on these three challenges in adopting big data analytics, the chances of success are considerable. But the support of technology should be invoked as part of the entire process. Digital transformation begins at the board level as directors themselves not only make greater use of technology but also display the kind of understanding of processes like big data analytics that enables them to look forward and perform better.