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Improve Inventory Accuracy through Optimal Cycle Counting – CDP-06 OU/OSU Collaborative



Research Team:

Yongpei Guan, Tieming Liu, Zhili Zhou, Simin Pulat

Universities Involved:

University of Oklahoma

Start Date:


End Date:



The objective of this project is to develop optimal policies, develop a scheduler software written in Java (eclipse) that has an interactive interface, database, intelligent engine, graphical output, and user manual to help manage inventory and reduce counting costs.
Problems with inaccurate inventory records have significant and expensive consequences. Inventory record inaccuracy can lead to a substantial decrease in profits due to lost sales, higher inventory carrying costs and loss of customers. Inaccurate inventory records can mean carrying too much inventory without realizing it, or carrying too little inventory and not reordering it – a problem that reduced profits at Gamma by more than 10 percent. Inaccurate inventory records may also have a long-term negative impact on a firm’s brand image. For retailers like Gamma who rely on computerized replenishment systems for managing store inventory, these execution problems may result in inaccurate demand forecasts. Demand forecasting systems rely on historical sales data to estimate future demand for each item in the store. If an item is out of stock at a store and no sales transactions take place, since the system may not detect the out of stock in the system due to inaccurate inventory record, then the new forecast for the item may be inaccurately low, sometimes causing the retailer to drop what may actually be a popular item.
Online Cycle Counting Scheduler Available at