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Intermittent demand where demand occurs sporadically with many periods of zero sales, presents a unique challenge for forecasters and supply chain planners. Traditional metrics for forecast accuracy can be misleading when applied to slow-moving items, and focusing solely on these can lead to suboptimal inventory decisions. This article explores which metrics to use for evaluating forecasts of intermittent demand, including accuracy measures (and their limitations) and invento

The Game-Changer You’re Not Using... Yet Imagine identifying early signs of customer dissatisfaction before they decide to leave, how investors feel before they act, or what your employees truly think before they leave. Sentiment analysis is the key to unlocking these insights, yet many businesses still underutilize its potential. Sentiment analysis, also known as opinion mining, uses AI and machine learning to analyze text data and determine whether the sentiment is positive

Can social media predict product demand?  Many supply chain professionals still rely on traditional forecasting methods, but what if social media could give us real-time demand signals before sales even happen? In my recent research, we found that analyzing social media sentiment and engagement can improve demand forecasting accuracy by 42%, especially for new products with no historical data. Let’s break it down. Image generated by AI (DALL·E) The Challenge: Forecasting New