Optimization of the promotion mix in the healthcare industry

Abstract

Purpose – The purpose of this paper is to propose data mining techniques to model the return on investment from various types of promotional spending to market a drug and then use the model to draw conclusions on how the pharmaceutical industry might go about allocating promotion expenditures in a more efficient manner, potentially reducing costs to the consumer. The main contributions of the paper are two-fold. First, it demonstrates how to undertake a promotion mix optimization process in the pharmaceutical context and carry it through from the beginning to the end. Second, the paper proposes using directed acyclic graphs (DAGs) to help unravel the direct and indirect effects of various promotional media on sales volume. Design/methodology/approach – A synthetic data set was constructed to prototype proposed data mining techniques and two analyses approaches were investigated. Findings – The two methods were found to yield insights into the problem of the promotion mix in the context of the healthcare industry. First, a factor analysis followed by a regression analysis and an optimization algorithm applied to the resulting equation were used. Second, DAG was used to unravel direct and indirect effects of promotional expenditures on new prescriptions. Research limitations/implications – The data are synthetic and do not incorporate any time autocorrelations. Practical implications – The promotion mix optimization process is demonstrated from the beginning to the end, and the issue of negative coefficient in promotion mix models are addressed. In addition, a method is proposed to identify direct and indirect effects on new prescriptions. Social implications – A better allocation of promotional expenditures has the potential for reducing the cost of healthcare to consumers. Originality/value – The contributions of the paper are two-fold: for the first time in the literature (to the best of the authors’ knowledge), the authors have undertaken a promotion mix optimization process and have carried it through from the beginning to the end Second, the authors propose the use of DAGs to help unravel the effects of various promotion media on sales volume, notably direct and indirect effects.