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The fashion industry is investing huge amounts of money in artificial intelligence systems that can provide what is called “sentiment analysis”, which is similar to customer feedback, except that it’s indirectly acquired. Typically, sentiment analytics systems can gather information from social media pages as well as through natural language processing, perhaps through listening to customer phone calls. A massive number of data points can be collated and analysed – a quantity of information that only an AI system can process. And after processing it all, conclusions can be drawn. For example, sentiment analysis can help discover whether people are speaking positively about some products or negatively about others; or it can collate and organise all reviews; or it can monitor the news media to see if the brand is being mentioned, and in what context. Usually, all of the information collected and then what might be called “real” intelligence ultimately needs to be applied. While an AI system can make simple judgments, such as if an item is being positively discussed and reviewed, it’s obvious that the item in question could do well if it was continually stocked. However, it is ultimately a human who will have to make decisions about how to respond to stories in the media, for example. And anyway, it’s not often the case that products are universally liked or disliked – the human will probably have to decide what to do about the balance. But whether it’s a human or AI that makes the decision about which products to manufacture, the supply chain aspect of the operation needs to be fast enough to take the product to the market and customer before tastes and fashions change. The warehousing aspect of the supply chain, in particular, is a critical part of the product’s journey. A […]