The IdeaA mathematical model helps firms capitalize on advance supply information.
Supply chain managers work in a constant state of uncertainty: demand uncertainty, or how much a firm’s customers are going to ask for, and supply uncertainty, or how many components or raw materials a firm’s suppliers can provide at a given point in the future.
While demand uncertainty is one part of the puzzle, understanding supply uncertainty is critical for managing production efficiently. Firms are subject to a variety of factors that can leave them unable to meet demand from customers: a supplier might have promised some of its capacity to another firm, or might need to temporarily slow or stop delivery to maintain its manufacturing equipment. Fluctuations in supply can paralyze a firm, which may find itself unable to produce a key product or to plan for future production.
Such fluctuations may sometimes be known in advance to the supplier, but not to the firm. Some suppliers have agreements with downstream firms to share forecast information about their capacity to deliver, and firms often welcome such collaboration. But firms don’t typically have an easy way to factor the forecast into decision making or to calculate exactly how much better off they are with the information.
Professor Alp Muharremoglu and doctoral student Mehmet Sekip Altug examined a supply chain setting with capacity forecast sharing and devised a simple formula that can be used by managers to incorporate the forecast information into their replenishment decisions. They also analyzed supply collaboration scenarios to determine when advance supply information is most useful. The researchers found that, overall, such supply forecasts are most valuable to a firm when the ratio of the firm’s average demand to the supplier’s average capacity is moderate.
Supply chain managers
You can use this research to determine how to incorporate advance supply information into replenishment decisions. For example, if the forecast indicates a low level of capacity availability next month, the formula indicates how much the firm should increase the current month’s order in order to plan for the upcoming shortage.
You can use this research to determine how cost-effective it would be for your firm to purchase, install and operate information technology to receive and to use advance supply information.