{"id":38986,"date":"2026-04-08T10:55:39","date_gmt":"2026-04-08T09:55:39","guid":{"rendered":"https:\/\/www.argonandco.com\/?post_type=whitepaper&p=38986"},"modified":"2026-04-08T10:55:39","modified_gmt":"2026-04-08T09:55:39","slug":"machine-learning-demand-planning-how-predictive-algorithms-are-transforming-sales-forecasting-in-the-pharmaceutical-industry","status":"publish","type":"whitepaper","link":"https:\/\/www.argonandco.com\/en\/news-insights\/whitepapers\/machine-learning-demand-planning-how-predictive-algorithms-are-transforming-sales-forecasting-in-the-pharmaceutical-industry\/","title":{"rendered":"Machine Learning & Demand Planning : How predictive algorithms are transforming sales forecasting in the pharmaceutical industry"},"content":{"rendered":"
In the pharmaceutical industry, inaccurate forecasting can lead to far more than a simple inventory gap: supply disruptions, lost revenue, lower fill rates, and increased pressure on teams.<\/div>\n
At a time when demand planning processes still often rely on limited statistical models, Machine Learning<\/strong> makes it possible to integrate a wider range of signals, better capture complexity, and automate part of the forecasting process while maintaining explainable results.<\/div>\n
In this white paper, Thibaut Dyen, Micka\u00efl Voyiatzis, Franck Kakal, and Guilhem Delorme<\/strong> share their analysis of pharmaceutical demand planning challenges, the technology levers to activate, and the concrete results observed in the field:<\/div>\n
    \n
  • +3.5% revenue<\/strong><\/li>\n
  • -8.2% finished goods inventory<\/strong><\/li>\n
  • 80% forecast automation<\/strong><\/li>\n<\/ul>\n
    Download the white paper<\/strong> to discover our approach.<\/div>\n","protected":false},"excerpt":{"rendered":"

    In the pharmaceutical industry, inaccurate forecasting can lead to far more than a simple inventory gap: supply disruptions, lost revenue, lower fill rates, and increased pressure on teams. At a time when demand planning processes still often rely on limited statistical models, Machine Learning makes it possible to integrate a wider range of signals, better […]<\/p>\n","protected":false},"template":"","region":[],"class_list":["post-38986","whitepaper","type-whitepaper","status-publish","hentry"],"acf":[],"yoast_head":"\nMachine Learning & Demand Planning : How predictive algorithms are transforming sales forecasting in the pharmaceutical industry - Argon & Co<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.argonandco.com\/en\/news-insights\/whitepapers\/machine-learning-demand-planning-how-predictive-algorithms-are-transforming-sales-forecasting-in-the-pharmaceutical-industry\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Machine Learning & Demand Planning : How predictive algorithms are transforming sales forecasting in the pharmaceutical industry - Argon & Co\" \/>\n<meta property=\"og:description\" content=\"In the pharmaceutical industry, inaccurate forecasting can lead to far more than a simple inventory gap: supply disruptions, lost revenue, lower fill rates, and increased pressure on teams. 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