What’s an Analytics Translator? Data Storyteller?
The Age of Analytics: Competing in a Data-Driven World. McKinsey Global Institute, Dec 2016. The translator is the “link between analytical talent and practical applications to business questions…. We estimate… demand for approximately 2 million to 4 million business translators in the U.S. alone….”
You Don’t Have to Be a Data Scientist to Fill This Must-Have Analytics Role. Nicolaus Henke, Jordan Levine, and Paul McInerney in Harvard Business Review, 5-Feb-2018. Translators synthesize complex, analytics-derived insights into actionable recommendations for business users. Domain knowledge and presentation skills are essential, combined with general technical or STEM understanding.
Why Your Company Needs Data Translators. Chris Brady, Mike Forde, and Simon Chadwick in MITSloan Management Review, Winter 2017. Often we see a consistent disconnect between data scientists and the executives they support. That’s why it’s time for a new role: the data translator closes the ‘interpretation gap’ between quants and decision makers.
The Translation Layer: The Role of Analytic Talent. Lori C. Bieda (formerly Executive Lead of Customer Intelligence at SAS). “Analytics teams must step outside of their functional silos. They need to start looking at the business more holistically and connect the dots…. They need to evolve from data providers into insight integrators.”
In praise of “light quants” and “analytical translators”. Tom Davenport finds that “almost every organization would be more successful with analytics and big data if it employed some of these folks…. A ‘light quant’ is someone who knows something about analytical and data management methods, and who also knows a lot about specific business problems. The value of the role comes, of course, from connecting the two.”
The Changing Talent Landscape: Enter the Data Analytics Translator. Vicky Matthews explains how finance and insurance firms are delivering more value from data analytics activities.
Communicating insights to decision makers
Data is Easy, Deciding is Hard. Tracy Allison Altman, founder of Ugly Research, explains why subject matter experts struggle to communicate effectively with executive decision makers, and how to improve the process by focusing on specific questions and the insights that answer those questions.
Big Data for Boundary Spanners course at the Analytics Academy (Amsterdam). Topics include determining and defining business questions for data science.
Data Storytelling: The Essential Data Science Skill Everyone Needs. Brent Dykes explains that “Data storytelling is a structured approach for communicating data insights, and it involves a combination of three key elements: data, visuals, and narrative.”
The Talent Dividend: Analytics talent is driving competitive advantage at data-oriented companies. Sam Ransbotham, David Kiron and Pamela Kirk Prentice in MITSloan Management Review, 2015.
Analytics in Action: Breakthroughs and Barriers on the Journey to ROI. Accenture study reveals the urgent need to translate data-driven insights into actions and outcomes.
Machine Learning: Bridging Between Business and Data Science. White paper by Altexsoft. Companies stumble over talent acquisition barriers, internal leadership difficulties, and… the rigidity of overregulated corporate culture.
Becoming an Analytics Translator. Raef Lawson in Strategic Finance. “Finance professionals must learn to communicate with data scientists and technology specialists, helping them ask the right questions and translate data into business insights.”
The Power of People: Learn How Successful Organizations Use Workforce Analytics To Improve Business Performance. Nigel Guenole, Jonathan Ferrar, Sheri Feinzig. Put simply, translators turn the technical outcomes from analytics projects into insights that business leaders can understand and act upon.