Database Analysis to Improve U.S. Transportation Command Forecasting Processes

The United States Transportation Command (USTRANSCOM) facilitates air, land, and sea transportation for the DOD. On a periodic basis, a myriad of different agencies within USTRANSCOM project future workload to facilitate resource planning, budgeting, and reimbursable rate identification. Within USTRANSCOM, there are a variety of databases and metrics utilized for workload forecasts; neither a standard nor a preferred technique is prescribed. Currently, USTRANSCOM faces challenges in producing accurate workload forecasts [1]. These challenges can lead to unreliable budget requests and, ultimately, hinder the effectiveness and efficiency of USTRANSCOM [1]. For the purpose of routine aircraft movements of cargo and personnel, this research seeks to answer (1) whether any data sets are dominated with respect to data quality, allowing for their removal from consideration and (2) the degree to which any data set is superlative with respect to informing high quality air workload forecasts. Furthermore, this research identifies a possible major problem with USTRANSCOM\u27s current forecasting procedure and provides recommendations on how to best utilize the data sets readily available for use