Dell pioneered the direct sales model by offering its customers technology solutions through full-system configurability. In 2007, Dell launched several strategic initiatives to drive channel transformation by offering fixed configurations through online channels, retailers, distributors, and other channel partners. Dell's center of excellence (CoE) in analytics developed solutions that apply operations research (OR) to address key challenges across the value chain and enable profitable growth in the new channels. These solutions include (1) a configuration optimizer to reduce product complexity by identifying fixed hardware configurations (FHCs), which Dell builds and stocks, (2) an online conversion rate accelerator to improve the online customer purchase experience, leading to increased revenues and customer satisfaction, and (3) a retail margin maximizer to improve forecasts, mitigate inventory risk, and recommend promotions to increase margins. Since 2007, OR has helped Dell solve complex business problems and has facilitated its growth in the FHC business to $15 billion. Since 2010, these OR solutions have delivered a margin impact of more than $140 million by reducing markdown expenditures, improving online conversion rates, increasing ocean shipments, and enhancing customer satisfaction.

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As data production, collection, and analytic techniques grow, emerging issues surrounding data management and storage challenge businesses and organizations around the globe. The US Army Training and Doctrine Command’s Analysis Center (TRAC) is no exception. For example, among TRAC's many tasks is the evaluation of new materiel solutions for the Army, which typically necessitates the use of computer simulation models such as COMBAT XXI. These models are computationally expensive, and they generate copious amounts of data, straining TRAC's current resources and forcing difficult, suboptimal decisions regarding data retention and analysis. This paper addresses this issue directly by developing "big data" solutions for TRAC and evaluating them using its organizational values. Framed in the context of a use case that prescribes system requirements, we leverage Monte Carlo simulation to account for inherent uncertainty and, ultimately, focus TRAC on several high potential alternatives.