Optimal base-period data for productivity measurement

The profit-linked total-factor productivity measurement models, such as the American Productivity Center model, use base-period data as the standard against which the current-period performance is measured. Hence, the design and development of accurate and appropriate base-period data is critical in analysing performance. This paper presents a linear programming model to generate the optimal base-period data as well as to provide valuable information through sensitivity analysis that is not possible by the measurement model. This information can lead to an investigation of the causes of problems such as resource inefficiencies, in addition to the validity and the flexibility of consumption and production figures.