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It pays to be a data scientist, and not just financially. Data scientists have the best jobs according to Glassdoor’s 50 Best Jobs in America for 2018 report, which marks the third year it took top honors.
But as good as a data scientist gig may be, it's not all about crunching data. One of their key responsibilities is communicating deep business or customer analytics to business people, which is a skill that many still need to learn. Not everyone can be a data scientist, and not everyone has a “beautiful mind” when it comes to data analytics. "Data citizens," those people in organizations who lack deep analytics skills but need analytics to improve their jobs performance, rely on data scientists to relay their analysis in clear and accessible language.
The ultimate goal? To have your organization’s data scientists discuss analytics in a way that inspires action among your data citizens.
What Is a Data Scientist?
Let’s start by looking at what a data scientist actually does. According to TechTarget, a data scientist leverages advanced analytics, machine learning, predictive modeling and other techniques that allow them to take analytics beyond basic statistical analysis. They collect and crunch vast amounts of data to help improve internal processes and customer programs.
A large part of their time is currently devoted to prepping data. According to a 2017 Harvard Business Review article, analysts spend roughly 80 percent of their time discovering and preparing data.
Related Article: Data Scientists vs. BI Analysts: What's the Difference?
What Is a Data Citizen?
TechTarget also reported on data citizens, referring to them as employees who, like data scientists, leverage information to help make business decisions and do their jobs. However, they lack the skills of data scientists and rely on data scientists to mine structured data. Data citizens have access to more business intelligence tools than ever before, but still require a helping hand when it comes time to analyze.
We caught up with some experts to discuss how data scientists can communicate and establish strong relationship with their data citizens.
Related Article: Three Tips When Hiring Data Scientists
5 Steps to Successful Communications for Data Scientists
Speak the Same Language
The first step for data scientists to become better communicators is to recognize that while everyone needs data-driven insights in order to make the right decision for your organization, not everyone speaks the same language, said Ben Gaines, group product manager at Adobe.
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“Data citizens who don't spend all day living in the world of stats can be overwhelmed by the esoterica of advanced analytics,” Gaines said.
Use Empathy for Compelling Data Storytelling
Engage business stakeholders in a way that captures their attention both emotionally and logically. Gaines said he’s seen data science courses offered by universities that include classes on data storytelling. "Analysts can learn how to craft a compelling storyline around the facts and figures that’s easy to understand for anyone,” said Gaines.
You could give your business partners a table of data, the result of complex modeling. But sharing those same insights through a compelling story increases empathy and creates an emotional connection which makes employees want to solve customer experience issues said Gaines. "In my experience, that's the No. 1 thing that data scientists can do to communicate more effectively with data citizens.”
Related Article: How to Get One of Those Great Data Science Jobs
Speak the Language of the Business
When discussing data with business people, utilize the language of the business as opposed to the language of IT, said Danny Sandwell, director of product marketing at data governance company erwin. When you describe data within the frameworks of storage or management, it lacks the business context and prevents business people from being active participants in the conversation, he said. It can often be intimidating, he continued, and onerous for business people to become fluent at this level. It also inhibits their ability to participate effectively in ideation and verification of results. “If you speak a business language to business people, they feel more comfortable, they feel empowered and are much more willing to invest their time into the process,” Sandwell added.
Focus on Outcomes and Value
Outcomes and value make more sense to business people than process and complexity, according to Sandwell. “Most business folks,” he said, “aren’t interested in the mechanics or wizardry of analytics but are driven by what it can deliver to them in terms of potential business impact. They need to have confidence in the inputs and the process, but don’t need to be bogged down in the details of the steps to get there.”
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Focus on the Opportunity at Hand
Recognize that as a data professional you are trying to build a relationship of trust and engagement, Sandwell said. Focus on the business priorities and keep it as simple and prescriptive as possible in the early stages. Sandwell suggests identifying something of value for the business person and focus on delivering and proving it. “This,” he said, “will be a stepping stone to building an ongoing relationship where the business person becomes a much more eager and willing participant and most importantly sees you as a trusted enabler for the business.”
Remember, every job “starts with sales,” Sandwell said. Effectively sell yourself and your potential value in order to get active engagement, trust and a true partner in enabling analytics to effectively drive the business.
