| Current inventory theory is based on the economic order quantity (EOQ) model. This model is based on use of simulated data and unrealistic formulae. Inventory replenishment processes are therefore commonly disrupted, and out-of-stock (OOS) events are unnecessarily frequent. In this quantitative, quasi-experimental, single-case study, OOS events at a large-volume, long-term care pharmacy in North Carolina were compared among four sequentially applied methods of inventory control: (a) a manual system without Six Sigma protocol, (b) a manual system with Six Sigma protocol, (c) a computer-assisted system with Six Sigma protocol, and (d) an automated system with Six Sigma protocol. Daily OOS rates were recorded for approximately 11 weeks during the implementation of each method, for a total of 256 cases, or 64 per group. Between-group comparisons were performed using an independent samples t test and a one-way analysis of variance. Within-group time-series analyses were performed during each implementation to determine the significance of the change in OOS rates over the evaluation period. In terms of the two manual systems, OOS rates were lower for the system for which a Six Sigma protocol was applied, t(109) = 3.46, p = .001. In terms of the three systems for which a Six Sigma protocol was applied, mean differences were significant, F(2,189) = 101.70, p < .001. The highest mean OOS rate (M = 4.95) occurred for the manual system without Six Sigma, and the lowest rate (M = 1.87) occurred for the computer-assisted system with Six Sigma application. All OOS rates were significantly reduced over an 11-week period except, paradoxically, in the case of the manual system with Six Sigma application. Six Sigma was found to be an effective process improvement strategy in the selected pharmacy setting. The study was the first inventory analysis performed with OOS events used as an empirical measure, in contrast to the simulated data used in prior studies. The study therefore contributed to existing inventory theory by providing an alternative to the EOQ model, which was based on flawed and unrealistic assumptions. Further experimental research is needed in more pharmacies and in retail settings in other industries. |
