A new study by a University of Arkansas logistics researcher confirms that relying on retail point-of-sale data can increase the accuracy of predictions and reduce forecasting error. But contrary to recent findings, the new study also revealed that in specific situations point-of-sale data might not be as accurate as simple order data from client stores.
The so-called “bottom-up” approach to forecasting demand for goods relies on point-of-sale data, or raw sales information, which retailers share with each other and manufacturers. This approach allows manufacturers to plan production based on overall consumer demand.
In contrast, “top-down” forecasting refers to a forecasting approach in which manufacturers do not have access to point-of-sale data and therefore must depend on order data from client stores and distribution centers. In these cases, the manufacturer must create a single forecast for a retail company’s total demand and then disaggregate that forecast for each distribution center or store.
Manufacturers and industry analysts assume that point-of-sale data consistently leads to greater accuracy, but the new study found that simple order data may be more useful for forecasting demand at the account level, which includes individual retail stores and distribution centers. This top-down approach is also more useful, the researchers found, when manufacturers are trying to accurately predict long-term issues such as production and capacity planning.
“Conventional wisdom holds that suppliers can exploit point-of-sale information to improve forecasting performance and supply-chain efficiency,” said Matt Waller, logistics professor in the Sam M. Walton College of Business. “While this is true for the most part, it doesn’t tell the whole story. In most cases, order forecasts based on point-of-sale data exhibit lower forecast errors than those based on order data, but there are specific conditions when a top-down approach based on order data can achieve more accurate demand forecasts.”
Waller and Brent Williams, assistant professor at Auburn University, empirically tested claims about the performance of top-down versus bottom-up forecasting. They then investigated whether a given supplier’s demand forecast, when based on shared, point-of-sale data, might be more accurate than forecasts based on order data. Overall, the researchers found that sharing the right data in appropriate contexts leads to greater accuracy when forecasting demand in the retail supply chain. In other words, the choice of a method – top-down or bottom-up forecasting – depended on the availability of shared, point-of-sale data.
“We find that the superiority of the top-down or bottom-up forecasting as the more accurate method depends on whether shared, point-of-sale data are used,” Waller said.
Firms benefit from a top-down approach to demand forecasting when they do not have access to point-of-sale data and must rely on order data for long-term planning for production. Furthermore, in this same context, a top-down approach should be used for short-term planning and shipping forecasts to distribution centers. When available, point-of-sale data can increase forecast accuracy and improve performance of short-term issues, such as inventory and transportation planning, the researchers found.
The study also gives retailers new insights. For example, large retailers share their point-of-sale data with suppliers generally because they have the technology and resources to do so, but this type of sharing may be even more beneficial for small retailers.
The researchers’ findings were published in the Journal of Business Logistics.
Waller holds the Garrison Endowed Chair in Supply Chain Management.CONTACTS:
Matt McGowan | Newswise Science News
RWI/ISL-Container Throughput Index ending 2017 on a positive note
24.01.2018 | RWI – Leibniz-Institut für Wirtschaftsforschung
Uncovering decades of questionable investments
18.01.2018 | University of Texas at Austin, Texas Advanced Computing Center
For the first time, a team of researchers at the Max-Planck Institute (MPI) for Polymer Research in Mainz, Germany, has succeeded in making an integrated circuit (IC) from just a monolayer of a semiconducting polymer via a bottom-up, self-assembly approach.
In the self-assembly process, the semiconducting polymer arranges itself into an ordered monolayer in a transistor. The transistors are binary switches used...
Breakthrough provides a new concept of the design of molecular motors, sensors and electricity generators at nanoscale
Researchers from the Institute of Organic Chemistry and Biochemistry of the CAS (IOCB Prague), Institute of Physics of the CAS (IP CAS) and Palacký University...
For photographers and scientists, lenses are lifesavers. They reflect and refract light, making possible the imaging systems that drive discovery through the microscope and preserve history through cameras.
But today's glass-based lenses are bulky and resist miniaturization. Next-generation technologies, such as ultrathin cameras or tiny microscopes, require...
Scientists from the University of Zurich have succeeded for the first time in tracking individual stem cells and their neuronal progeny over months within the intact adult brain. This study sheds light on how new neurons are produced throughout life.
The generation of new nerve cells was once thought to taper off at the end of embryonic development. However, recent research has shown that the adult brain...
Theoretical physicists propose to use negative interference to control heat flow in quantum devices. Study published in Physical Review Letters
Quantum computer parts are sensitive and need to be cooled to very low temperatures. Their tiny size makes them particularly susceptible to a temperature...
15.02.2018 | Event News
13.02.2018 | Event News
12.02.2018 | Event News
20.02.2018 | Power and Electrical Engineering
20.02.2018 | Materials Sciences
20.02.2018 | Life Sciences