Stepping Higher - Reflections on the Knowledge Age

In knowledge management (KM), explicit knowledge – what’s written in documents and stored in files or other forms of media – has often had a bad reputation, and for good reason. Over years, KM has wrongly focused on documents and was busy building databases and repositories, when – as David Snowden put it – it shouldhave been focusing on connecting people instead . This preference is understandable. After all, explicit knowledge is just the tip of the iconic knowledge iceberg. Below the surface lies implicit knowledge, thoughts in people’s heads, rich with context and application insights, and accessible only through relationships and trust. However, I believe what we have been experiencing in 2023 with Generative AI marks a significant shift that could see explicit knowledge get its long-awaited moment in the sun. The Limitations of Content-focused KM and the Rise of AI Traditionally, KM never succeeded to fully leverage the knowledge that’s supposedly „stored“ in all the document...

I was recently reviewing a number of texts which my organization collected from past projects and initiatives (some through an internal mandatory monitoring tool, others gathered as part of After Action Reviews or Lessons Learned Papers), which all meant to capture ‘lessons learned’ from specific experiences. And while these texts were not wrong per se, I realized that there seems to be a fundamental misconception what constitutes a good lesson, and what doesn’t. Here are a few typical examples of what we often collect as part of such lessons learned exercises: “Ensure that the [Team] Manager has excellent leadership, project and team management skills, understanding of programming and experience working in [the subject matter].” “Project outputs must be compatible towards project goals. Throughout the project there is a need for careful identification of project goals and outputs to ensure that they are compatible with each other. This can be only ensured through a consultativ...