In today’s competitive business landscape, predictive analytics has emerged as a game-changing tool that revolutionises decision-making . By harnessing the power of Big Data, predictive analytics empowers organisations to forecast trends, uncover patterns, and gain invaluable insights.
This research was undertaken by scholars from Universities of Michigan and Wisconsin, Emory University and WHU Vienna. It was set within a large US-based automotive parts retailer and investigated whether and under what circumstances giving corporate analysts (i.e., the “human in the loop”) discretion to override the product stocking recommendations from a centralised predictive analytics model improves retail assortment planning decisions at retail locations.
The findings suggest that (1) the value of human intervention depends greatly on analysts’ ability to obtain diverse sets of information that cannot be captured by the model (2) specialist analysts, with a dedicated role in the assortment planning process, make lower quality decisions than generalist analysts and (3) the effectiveness of predictive analytics depends not just on the of the quality of the predictive model, but also organisational design choices (i.e., who does what) and the management controls and incentives that shape the relationship between the organisation and its external stakeholders.
This research provides important insights on the usage of predictive analytics in the business world and show that as businesses strive to navigate an increasingly complex landscape, the integration of human expertise and predictive analytics emerges as a key strategy for achieving superior outcomes.
It also suggests that management accountants, because of their central role in planning, have a unique vantage point to identify and correct weaknesses in management control systems to facilitate these choices.