Data Alone Won't Influence Decision-Makers

             

Big data and the analysis that accompanies it is big news. Today's world runs on data, and whether you're a data analyst, research scientist, process engineer, or marketer, your job involves data. A lot of data. But once you've gathered and parsed all this information, what do you do with it?

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VentureBeat explains that communication is one of the main stumbling blocks that might be preventing your big data from reaching its full potential. All your work gathering data might be for nothing if you can't communicate what it means to the relevant stakeholders.

The point of data analysis is to induce positive change in some way. To do that, you need to communicate the analytic findings to the right people. Unfortunately, those stakeholders or decision-makers are unlikely to have the patience or analytic interest to wade through raw numbers. What you need is a good storyteller.

A Harvard Business Review article notes that managers must do more than hire enough people to provide data analysis: they also need to hire those who can relay it.

Case in point: according to the article, the head of a data science group at Intuit that analyzes and creates product features based on data collected online explains that the group's data stories consider the following points:

  • The business problem
  • How to measure the business impact of the proposed solution
  • The available data
  • The solution, both as an initial hypothesis and as proven by the data

When you fail to communicate these elements effectively, the point of all your hard-earned analysis can be lost among the numbers.

So why doesn't everyone invest in good data storytelling? Tom Davenport, independent senior advisor for Deloitte Analytics, notes several possible reasons why organizations fall down in this regard:

  • Lack of motivation or inability to tell a good data story
  • Lack of storytelling instruction
  • Lack of understanding of the value of telling a data story
  • Lack of time

Davenport goes on to explain that, despite these roadblocks, using stories to relate and communicate data analytics is vital. Stories, he points out, are the oldest means of communicating the human experience and of passing on important information. We're wired to find them more interesting than raw data and numbers. For all of human history, even before recorded history, stories have been the way people make sense of a complex world. They provide the context, insight, and interpretation that ensure your data makes its point and achieves your goals.

What are the best ways to tell your data story? Davenport suggests creating narratives that incorporate both data-based evidence and real world examples. Standardizing around a few different storytelling templates can also help streamline communications and expand your story's reach.

If your organization is having trouble getting decision-makers to swallow all the big data you collect, stories can make data delivery easier to digest.

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