Matching Supply and Demand: Delayed Two-Phase Distribution at Yedioth Group-Models, Algorithms, and Information Technology

This paper details collaboration between the distribution organization within the Yedioth Group, the largest media group in Israel, Technion-Israel Institute of Technology in Haifa, Israel, and the Massachusetts Institute of Technology in Cambridge, Massachusetts. This collaboration has led to fundamental changes in how Yedioth distributes print magazines and newspapers. In our work, we developed and implemented decision support tools that are based on new models and algorithms, which were enabled through an electronic data interchange system, and in the future will be enabled with a specialized radio-frequency identification technological solution. The underlying concept is to use real-time information about the sales at the retail outlets to enable pooling of inventory in the network. In particular, we leverage this information to implement an additional redistribution period during the week, delaying the distribution of some magazines until after we receive partial sales data. We model the system as a two-stage stochastic optimization problem. Moreover, we show that the resulting cost is jointly convex in the decision variables. This approach gives rise to a multidimensional dynamic program. By formulating the second-stage subproblem as a linear program, we develop an innovative stochastic gradient-based optimization algorithm that finds the optimal solution in a matter of seconds. The changes resulting from this collaboration generated substantial cost savings at Yedioth-from both a reduction in magazine production levels and a reduction in the return levels. These savings were achieved while maintaining the same sales levels.