From Raw Data To Smarter Decisions: Decision Intelligence Best Practices

InnovationFrom Raw Data To Smarter Decisions: Decision Intelligence Best PracticesByDustin Johnson,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)May 28, 2026, 07:15am EDTDustin Johnson is the CTO at Seeq, responsible for the advanced technology infrastructure, vision and roadmap of Seeq software solutions. getty​Industrial organizations today are drowning in data yet starving for actionable decisions. Sensor streams, maintenance logs, lab results and operator notes sit in disconnected systems and dashboards, while the practical know-how to interpret them is scattered across people’s heads, reports and emails. As veteran engineers and subject matter experts retire, teams simultaneously struggle to connect siloed, multimodal data into a coherent picture of what happened and why. The result: critical decisions are delayed, second-guessed or never made at all. The impact is real. Among data and analytics teams already grappling with poor data quality, more than a quarter estimate annual losses above $5 million and 7% put the figure at $25 million or more. At the same time, the sheer volume of data and the lack of trust in it leave many business leaders unable to make timely, confident decisions, exactly when speed and alignment matter most in today’s industrial environment. The Rise Of Decision Intelligence Closing this “insight-to-action” gap has given rise to the field of Decision Intelligence (DI). Gartner defines DI as “a practical discipline that advances decision making by explicitly understanding and engineering how decisions are made and how outcomes are evaluated, managed and improved via feedback. By digitizing and modeling decisions as assets, DI bridges the insight-to-action gap to continuously improve decision quality, actions and outcomes.” Importantly, DI is not just about automation for automation’s sake. I...