Contrasting roles of measurement knowledge systems in confounding or creating sustainable change

Abstract

Sustainable change initiatives are often short-circuited by failures in modelling. Unexamined assumptions about measurement and numbers push modelling into the background as a presupposition rarely articulated as an explicit operation. Even when models of system dynamics are planned components of a sustainable change effort, the key role of measurement is typically overlooked. The crux of the matter concerns the distinction between numeric counts and measured quantities. Mistaking the former for the latter confuses levels of complexity and fundamentally compromises communications. Reconceiving measurement as modelling multilevel distributed decision processes offers new alternatives aligned with historically successful efforts in creating sustainable change. Five conditions for successful sustainable change are contrasted from the perspectives of single-level vs multilevel modelling: vision, plans, skills, resources, and incentives. Omitting any one of these from efforts at creating change result, respectively, in confusion, treadmills, anxiety, frustration, and resistance. The shortcomings of typically implemented single-level approaches to measurement result in the widespread experience of these negative consequences. Results show that new potentials for creating sustainable change can be expected to follow from implementations of multilevel distributed decision processes that effectively counteract organizational amnesia by embedding new learning in an externally materialized knowledge infrastructure incorporating a shared cultural memory.