Forecasting Demand – How Machine Learning Helps Drive Retail Success

Yet, if they are working with flawed data and inaccurate forecasting techniques, they will end up with too few or, too many staff on the shop floor and in the warehouse, and not enough stock to meet sudden surges in demand. This typically results in unfulfilled sales opportunities and increased costs and abandoned shopping baskets. Conscious that this situation is unsustainable, retailers are increasingly focused on using artificial intelligence and machine learning to more accurately forecast demand. With computing and data processing power escalating all the time, the more-forward thinking are already assessing the benefits that more accurate forecasting could have on their sales and profitability. Key to the success of any forecasting system is the data fed into it.