How to Align Predictive AI with Business Metrics
Predictive AI has the potential to revolutionize industries, yet many initiatives fail to deliver real value. The crux of the issue lies in the disconnect between data professionals and business stakeholders. Often, the technical performance metrics that data scientists focus on do not resonate with decision-makers, leading to stalled projects and wasted resources.
To bridge this gap, its essential for both data scientists and business leaders to establish a common understanding of value. By aligning machine learning models with business outcomessuch as profit and savingsteams can effectively communicate the potential impact of their work. This alignment not only facilitates project buy-in but also ensures that predictive AI initiatives are designed with clear, measurable goals in mind.
As we move forward, the challenge remains: how can we ensure that predictive AI projects are not just technically sound but also strategically valuable? The answer lies in fostering collaboration and focusing on outcomes that matter to the business.
Original source: https://www.predictiveanalyticsworld.com/machinelearningtimes/how-to-un-botch-predictive-ai-business-metrics/14041/