Understand
While data-driven decision-making is transforming modern operations, most large-scale data is of an observational nature, such as transactional records.
- These data pose unique challenges in a variety of operational problems posed as stochastic optimization problems, including pricing and inventory management, where one must evaluate the effect of a decision, such as price or order quantity, on an uncertain cost/reward variable, such as demand, based on historical data where decision and outcome may be confounded.
- Often, the data lacks the features necessary to enable sound assessment of causal effects and/or the strong assumptions necessary may be dubious.
- Nonetheless, common practice is to assign a decision an objective value equal to the best prediction of cost/reward given the observation of the decision in the data.