Resource allocation is a critical decision for manufacturing companies with limited resources. This paper presents empirical analyses of case studies exploring how resource allocation impacts key performance metrics in different industry contexts. A case study of an automotive parts manufacturer examined the effects of allocating most machining capacity to higher-value precision components versus a more balanced approach. Production data showed this initially reduced throughput of standard parts and hurt on-time delivery. Reallocating 10% of capacity improved delivery without compromising quality. Additionally, regression analysis of a dataset from five electronics manufacturers showed that workforce composition, in terms of more experienced operators, significantly correlated with lower defect rates. Assigning senior staff to production lines consistently led to better first-pass yield. Taken together, these studies provide empirical evidence that even modest tweaks to resource allocation levels can meaningfully influence outcomes like quality, throughput and on-time performance. The results inform both tactical short-term decision-making and more strategic long-range production planning and capacity management