Customer Engagement
Delivering Creativity and Effective Story Telling

Where Data and Story Meet: The Modern Data Scientist and Modern Marketer

Randa McMinn
January 09, 2017

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Data is rapidly transforming the way companies are transacting and engaging with customers. Gone are the days of not having enough data, now we are being inundated with too much and are struggling to find ways to make sense of it. As a business leader, your success is heavily reliant on making sense of data, so it is becoming imperative to build and nurture a great data storytelling capability.

In a new research report, my colleagues and I explore the increasing demands in skill sets for the modern data scientist and marketer. Further, we explore the mindset of data scientists and whether or not that mindset differs from a group of analytics professionals who have been identified as great data storytellers – revealing different ways to build the data storytelling capability.

Historically, analysis- and building-focused data scientists were enough to accomplish most all data science requirements; however, we now need data scientists to understand how the data and systems actually apply to the business. This additional requirement calls for a third type of data scientist: consulting-focused.

There are a number of category iterations of the traditional marketer, and those can be summarized into the context of either being left-brained (scientific) or right-brained (artistic). However, the modern marketer must not only use both the scientific and artistic parts of the brain; but also, a third part: consultative.

We teamed up with Talent Analytics, Corp., an organization that specializes in understanding how to hire and retain top talent by creating customized benchmarks to help companies predict how candidates will do in their jobs, pre-hire. These benchmarks are mostly built around the soft skills and mindsets of candidates, of which companies find difficult to both articulate and assess during the hiring process. Talent Analytics, Corp. and the International Institute of Analytics conducted a study on Analytics Professionals in order to see if the “mindset” of the data scientist differed from the mindset of other professionals. The initial study revealed an undeniable “raw talent mindset” of the Analytics Professional.

Our goal of the Talent Analytics partnership was to compare data scientists, who had been identified as great data storytellers, against the Analytics Professional benchmark to help us determine whether or not great data storytellers are governed by a mindset or skill set. We found these five definitive steps can help organizations build and nurture an environment of great data storytelling:

  • Be open and build a data storytelling team with people who embody a diverse mix of hard and soft skills.
  • Empower the team with corporate support and training to further develop business judgment and consultative skills.
  • Collaborate and team with key business units to determine which questions are the “right” questions the team should be asking and answering in their data story.
  • Integrate all participating team members into the line of business. Your teams will be unsuccessful if you assume each contributing function should stay in their “box” of job responsibilities and do not allow them to fully comprehend the intricacies of your business.
  • Make sure the data story is applicable to your business challenge, is relatable to how the company can grow its business, and is simple enough for every business unit to understand and apply.

Great data storytelling is not one size fits all. It requires an open mind in how one might structure the team responsibilities, and it also requires on-going engagement to support the data storytelling capability. Instead of trying to find the “magic bullet” or “unicorn” of the great data storytellers, it is recommended to build a team of diverse individuals who can bring a variety of interest, skill, and perspective to the table.

Read the full report, here.

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