Management Practice Insights

Abstract

Online shopping demand has outpaced the development of supporting infrastructure and resources. This might seem to be a good problem for e-tailers and warehouses. However, if this demand is not fulfilled efficiently, it can have costly consequences, even for the biggest and best brands. Order delays and errors mean customer satisfaction suffers, and costs inflate – a combination which squeezes an organization’s bottom line. This increasing pressure on efficient order fulfillment has led to advances in warehouse design and automation. However, new research suggests that warehousing efficiencies can be increased a further 20% or more by using an algorithm that combines two datasets – demand for a product, and its affinity to be ordered with other products. This research, by Masoud Mirzaei, Nima Zaerpour and Rene de Koster, found these gains in warehouses that use automated order picking – where robots bring entire racks with products to human operatives.¹ We believe that the core insight can change the game for all warehouses – regardless of the degree of automation – by reducing order-picking time, enabling faster delivery times and improving space utilization