Abstract
Outsourcing of information technology (IT) infrastructure and business processes (BP) is a significant aspect of the business landscape. Recently, attention has moved to variable capacity contracts linked to business or IT metrics for medium to long term (two to ten year) deals. This new emphasis on variability is accompanied by a growth in interest in the accompanying pricing schemes. A basic tension in the design of these pricing schemes occurs between the objectives of the outsourcing provider (hereafter Provider) and the company whose IT or BP is being outsourced (hereafter Client). In other words, their utility functions on contract attributes differ. For example, the Client may desire utility-style pricing, while the Provider may be interested in the certainty with which it achieves a given margin. This paper characterises and solves the price design problem (PDP) for variable capacity IT/BP outsourcing contracts within a descriptive multi-attribute utility theory framework from the point of view of the bid team, ie they know costs and must negotiate prices. In these situations, costs are usually granular, non-linear and history dependent. It is shown that the PDP, ie the general problem of choosing a price structure to optimise the joint utility function of the Provider and of the Client for arbitrary cost functions, can be formulated exactly as a stochastic program. The formulation imposes no restrictions on the form of the price functions a priori. A solution method is introduced based on decomposition of the event space (where events are, for example, Client requirement histories) using a basis of linear functionals. The resulting linear (and quadratic) mixed integer optimisations can be solved numerically using standard software. The solution yields Pareto-efficient outcomes with respect to the Provider and the Client. The frontier of Pareto-optimal designs serves as an appropriate space for practical contract negotiation.
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Kenyon, C. Optimal price design for variable capacity outsourcing contracts. J Revenue Pricing Manag 4, 124–155 (2005). https://doi.org/10.1057/palgrave.rpm.5170135
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DOI: https://doi.org/10.1057/palgrave.rpm.5170135