A process for post-implementation IT benchmarking

摘要

Post-implementation learning involves continuing improvements in how effectively information technology (IT) is utilized. This kind of IT learning is a core competency that may determine the competitiveness of firms in information intensive industries. While many chief information officers (CIOs) may have some experience with infrastructure, user satisfaction, or business process benchmarking, few firms benchmark how effectively IT is utilized or its impact on the user's work. This paper proposes a web-enabled process for benchmarking IT outcomes (effective use and impacts) and diagnosing problems with the user's learning. This process is based on an explicit causal model of how induced and autonomous learning factors drive IT usage and impacts. The proposed process enables internal versus "best-in-class" causal analysis. We discuss the common considerations and key issues involved in implementing this IT benchmarking process.