{"id":2361,"date":"2026-10-28T13:22:07","date_gmt":"2026-10-28T13:22:07","guid":{"rendered":"https:\/\/www.epw.com\/blog\/?p=2361"},"modified":"2026-10-28T13:22:09","modified_gmt":"2026-10-28T13:22:09","slug":"machine-learning-business-decision-framework","status":"publish","type":"post","link":"https:\/\/www.epw.com\/blog\/artificial-intelligence-machine-learning-articles\/machine-learning-business-decision-framework","title":{"rendered":"Machine Learning for Business Decision-Making: A Practical Framework"},"content":{"rendered":"

Machine learning can produce an accurate prediction and still fail to improve a business decision. The usual cause is not the algorithm. It is a gap between the model\u2019s output, the action available to a decision-maker and the outcome the organisation actually values.<\/p>\n

A sound machine-learning business case therefore begins with a decision, not a dataset or a fashionable model. It identifies who must act, what choices are available, when the prediction is needed and what a useful improvement would be. Only then should a team decide whether machine learning is the right intervention.<\/p>\n

This article presents EPW\u2019s practical DECIDE framework<\/strong> for framing, evaluating and implementing machine learning for business decision-making. It is designed for managers, analysts and technical teams who need a common method for moving from an operational problem to measurable value.<\/p>\n

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