Abstract
As organizations increasingly rely on AI, informatics, and analytics for decision-making, a persistent challenge remains: the communication gap between technical teams and business leaders. Many data-driven initiatives fail because insights and processes do not effectively translate into business impact. This paper examines the emerging role of analytics translators, professionals who bridge this divide by ensuring data, models, and algorithms align with organizational objectives. We explore how design thinking principles—empathy, iteration, and prototyping—enhance analytics translation, making insights more actionable and strategically relevant. McKinsey estimates a global need for 2–4 million analytics translators by 2026, but structured frameworks for developing these roles are lacking. Using real-world case studies, this paper illustrates how analytics translators drive value by optimizing supply chains, enabling digital transformation, and enhancing AI-driven forecasting, maximizing the return on informatics investments.
https://ror.org/01n002310 
