Knowledge management (KM) was recognised as a discipline in the 1990s, but is it still fit for purpose in the 21st century? What, if anything, needs to change?
A NetIKX seminar held at the British Dental Association, London, 25 May 2023
Does knowledge management (KM) need to change? This was the question posed by Steve Dale at NetIKX’s first face-to-face meeting since lockdown. Setting out the agenda, Steve invited us to consider a range of questions, starting with the fundamental issue of what KM is. It’s still frequently confused with information management (IM) and may be found in different departments in various organisations, depending on what it is perceived to be.
Steve describes KM as being about “getting the right knowledge to the right person at the right time”. Knowledge in this context refers to both explicit knowledge (that which is documented and ready to be shared, such as books and databases) and tacit, or implicit, knowledge (that which is inside our heads). The process of sharing and creating knowledge was described by Ikujiro Nonaka and Hirotaka Takeuchi in their influential 1995 book The Knowledge-Creating Company as a ‘knowledge spiral’, and has become known as the SECI model (Socialisation, Externalisation, Combination and Internalisation). In this model, implicit knowledge is externalised to become explicit knowledge, and is then re-internalised into implicit knowledge.
Is a discipline from the 1990s still fit for purpose?
While Nonaka and Takeuchi’s model gained widespread acceptance in the 1990s, a decade in which several large consulting firms began to offer KM as a service, there is still considerable debate about the exact relationship between knowledge, information and data. Anyone venturing into the world of KM will encounter a bewildering array of definitions and diagrams, with differences of opinion apparent even among ‘big name’ KM consultants.
Steve pointed out that, while areas such as manufacturing have seen huge changes in the past 70 years, the way we work in offices, despite automation, has not developed as radically as we might have expected. If KM has continued relevance today, what does it mean to be a good knowledge manager, or to use KM to provide added value to an organisation? One sign that KM may have come of age is the production of the first international KM standard, ISO 30401:2018 – but will this lead to organisations simply following the letter of the law rather than embedding KM into all their processes?
Four knowledge eras: how far have we come?
The earliest forms of KM were largely concerned with leveraging explicit knowledge – artefacts, libraries and knowledge repositories – and with connecting people to content via search and taxonomies. In the early 2000s, the emphasis shifted to managing tacit knowledge, with a focus on communities of practice and after-action reviews (AARs). The following decade saw a growing interest in leveraging collective knowledge, with the development of collaborative tools such as Sharepoint and Google Docs.
Now, in the 2020s, we are seeing a trend towards KM as sensemaking, with agile methodologies, design thinking and complexity being major themes. Storytelling is widely recognised as a valuable tool for understanding how we make sense of the world, as well as acknowledging that our stories may be different from those of other groups and individuals. And of course, we are also now entering the era of augmented knowledge, with AI and machine learning coming to the fore.
Can AI help or hinder KM?
Recent rapid developments in AI and machine learning have had an impact on all disciplines, and KM is no exception. Indeed, there are areas in which AI is already being used, such as legal data management and current awareness. The rise of ChatGPT and similar tools, however, have led to often justified concerns about the generation of inaccurate information and ‘fake news’, as well as the potential for plagiarism.
With awareness now growing of the way in which generative AI can replicate the bias fed into its training sets, there is a potential for KM experts to step in and address some of the ethical concerns around AI and machine learning. The field of augmented intelligence, in which humans and AI work together to enhance learning and decision-making, presents a huge opportunity for KM professionals: after all, as Steve pointed out, “KM gives you a better chance of making the right decisions”.
Our changing experience of KM
The group discussions centred around the theme of what systems, processes, procedures and technologies could (or should) be part of KM. These ranged from those traditionally associated with KM (librarianship, communities of practice, knowledge banks) to broader topics such as listening, communication skills and learning from experience – suggesting that our human (tacit) knowledge is now increasingly in demand. The importance of technology was also emphasised, with participants listing AI, chatbots and robotic process automation (RPA) as issues of concern for KM practitioners.
It was also noted that, while we still measure the impact of KM in a corporate context using cost-benefit analyses and metrics, we tend to use terms like ‘culture’ and ‘communication’ to describe what we feel KM should be about. Organisational culture, regardless of the size of the organisation, often determines what kind of knowledge and whose knowledge is valued: as one participant stated, “often the least listened-to people in the organisation have the most tacit knowledge”. We need to examine the gap between the world we know and the world we don’t know (also factoring in that we don’t always know what we don’t know!).
While it’s clear that KM has already evolved considerably in the last 30 years, maybe the question is now whether KM needs to change, but whether we as KM practitioners need to change our concept of what KM is. There is scope for an ongoing conversation around these issues, and we’re grateful to Steve and all who participated for initiating this conversation.