Obtaining Conservative Assessments of Profitability for Current Period Based on Target‐Adjusted Achievable Capacity Index With SARIMA Prediction

The achievable capacity index (ACI) is an effective tool for measuring and estimating the profitability of a single‐period product, where profitability is the probability of achieving a target profit under optimal ordering quantity. Setting a reasonable target profit (or corresponding target demand) is crucial, as it can impact profitability measurements and result in misguided decision‐making for the next period, especially when demand fluctuates over time. This study applies the seasonal autoregressive integrated moving average (SARIMA) to time‐series data to account for time dependencies in predicting target demand for the next period. We then developed a new ACI, referred to as t‐ACI, which incorporates the predicted target demand. In estimating the t‐ACI, we may encounter the risk of overestimation due to sampling error. Therefore, we derived the lower confidence bound for the t‐ACI (LCBtA) to provide a conservative assessment of profitability. Finally, we explore the conservative profitability evaluation using LCBtA to identify profitable products. Some generic tables and procedures of decision‐making for evaluation are provided. Regarding insights and implications, variations in Type‐I errors for prediction and estimation significantly influence the direction of decision‐making in evaluations. For instance, increasing the Type‐I error for estimation or decreasing it for prediction can positively steer the evaluation.