A logistic regression framework for information technology outsourcing lifecycle management

We present a methodology for managing outsourcing projects from the vendorʹs perspective, designed to maximize the value to both the vendor and its clients. The methodology is applicable across the outsourcing lifecycle, providing the capability to select and target new clients, manage the existing client portfolio and quantify the realized benefits to the client resulting from the outsourcing agreement. Specifically, we develop a statistical analysis framework to model client behavior at each stage of the outsourcing lifecycle, including: (1) a predictive model and tool for white space client targeting and selection—opportunity identification (2) a model and tool for client risk assessment and project portfolio management—client tracking, and (3) a systematic analysis of outsourcing results, impact analysis, to gain insights into potential benefits of IT outsourcing as a part of a successful management strategy. Our analysis is formulated in a logistic regression framework, modified to allow for non-linear input–output relationships, auxiliary variables, and small sample sizes. We provide examples to illustrate how the methodology has been successfully implemented for targeting, tracking, and assessing outsourcing clients within IBM global services division.