IT Offshore Outsourcing: Supplier Lessons on the Management of Expertise

Abstract

On our figures, revenues from offshore outsourcing of information technologies exceeded US$25 billion by 2008, and will experience compound annual growth averaging 20% over the next five years (Willcocks and Lacity, 2006; Willcocks and Cullen, 2005). For IT executives this means off-shoring, either directly, through a captive, or indirectly through a domestic supplier, has become a serious option; indeed many have already embarked down this path. For outsourcing vendors this means a growing number of clients will offshore outsource their IT systems expecting the vendors to maintain and in some cases to continue developing their IT applications from remote locations. But client executives already ponder a major question: where do you draw the line on outsourcing knowledge and expertise? How can a selected vendor develop knowledge and expertise of the client’s domain, systems and practices, not only to maintain continuity of service, but also to achieve the much vaunted targets of innovation and transformation? At the same time, we find executives of IT outsourcing vendors themselves asking: how can expertise be quickly developed around new areas, particularly where teams are remote and dispersed? How can we retain knowledge when people, in which it resides, move on? This chapter describes ongoing research into how one IT outsourcing vendor built expertise management systems in order to ensure the diffusion of client knowledge and the sharing of learning across the entire organization.1 Our research experiences point to major lessons for client and supplier organizations. At a big picture level, we show how, in order to compete and deliver on client expectations, over the next five years a supplier will need to make operational a transactive memory system for managing knowledge and expertise — in several ways something clients themselves could learn from.KeywordsSubject Matter ExpertExpertise ManagementReusable ComponentCapability Maturity ModelTransactive Memory SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.