It’s no secret that organizations have been increasingly turning to advanced analytics and artificial intelligence (AI) to improve decision-making across business processes — from research and design to supply chain and risk management.
You Don’t Have to Be a Data Scientist to Fill This Must-Have Analytics Role
Success with AI and analytics requires not just data scientists but entire cross-functional, agile teams that include data engineers, data architects, data-visualization experts, and — perhaps most important — translators. Translators are neither data architects nor data engineers. They’re not even necessarily dedicated analytics professionals, and they don’t possess deep technical expertise in programming or modeling. Instead, translators play a critical role in bridging the technical expertise of data engineers and data scientists with the operational expertise of marketing, supply chain, manufacturing, risk, and other frontline managers. Given the urgent need for translators, hiring externally might seem like the quickest fix. However, new hires lack the most important quality of a successful translator: deep company knowledge. As a result, training existing employees often proves to be the best option for filling the translator void.