As second generation biofuels approach commercial scale production, a large fleet of harvesting equipment is required to meet feedstock demand. In the Midwest United States, agricultural residue, such as corn stover, has been identified as a readily available feedstock. Multi-pass corn stover harvest requires the in-field operations of shredding, baling, and stacking. Proper management practices are required to keep machines running at maximum efficiency in order to reduce cost and harvest enough material to meet processing demand. This need for management becomes increasing important as production levels reach commercial scale levels. This study looked at management practices of several individual harvest crews across an entire harvest season. Data was collected from multiple machines, including balers, shredders, and stackers during the 2013 and 2014 fall harvests. The controller area network (CAN) bus system was utilized to record machine data that was linked to specific GPS coordinates within a given field. The information was then analyzed to identify controllable metrics, such as machine productivity, daily bale production, and bale density. Recognizing these controllable metrics will improve overall logistics as production reaches full scale and reduce overall costs. A techno-economic analysis was executed to quantify cost as performance and quality changed.