Developing a Maturity Model for Knowledge Management (KM) in the Digital Age

This paper arises from a work-in-progress academia/industry collaborative research project to develop a knowledge management (KM) maturity model as a component (critical capability) of the IT Capability Maturity Framework (IT-CMF). The aim of the project is to develop a knowledge management (KM) maturity model that is ‘fit for purpose’ for organisations in the digital age. In undertaking this work it became clear that, outside of the fundamental challenges of KM, new significant challenges and questions are becoming apparent arising from the digital transformation and subsequent changes in how data, information and knowledge are stored, disseminated, analysed, communicated and used. The research questions we address in this paper are as follows. 1) How does digital transformation impact on approaches to KM? 2) What are the implications of digital transformation for how we should develop KM maturity models/practice advice? Within the first research question some of the significant issues that have arisen during our work include the distinction and relationship between data, information, and knowledge in the light of data analytics and other related technologies. Social media has also changed the nature of knowledge creation and communication in, for example, facilitating commentary and opinions. The increasing volume of knowledge being created and the pace of change influences organisational learning. Is it always the case that stored knowledge will still be pertinent to understanding the next problem that arises as dynamic and improvisational capabilities, rather than core capabilities, become increasingly important? In terms of the second research question the changing nature of the KM context influences how guidelines can be developed and implemented. The rise of data analytics, for example, requires new relationship building and analytic capabilities in terms of liaising with the increasing number of organisational units that collect and analyse data. The increasingly ubiquitous nature of knowledge sharing also raises different issues in terms of assessing quality and currency as the central control of knowledge collection is losing ground. These, amongst other changes, may mean that previous ‘truths universally acknowledged’ within KM as ‘best practice’ now require re-examination. It may be increasingly difficult to prescribe certain practices that will be appropriate in most organisations or in most cases. This, therefore, has implications for how maturity models to support KM in the digital context are developed.