Project Knowledge and Information Management Fundamentals
This domain tests whether you can separate data, information, knowledge, and wisdom, and distinguish information management from knowledge management in a temporary project setting. Projects create both explicit knowledge (documents, models, logs) and tacit knowledge (judgment, relationships, know-how). The exam expects lifecycle thinking: capture, organize, share, apply, retain, and govern.
Core distinctions
- Data: raw symbols; information: data with context; knowledge: actionable understanding; wisdom: judgment about when to apply it (the DIKW hierarchy).
- Explicit knowledge is codifiable; tacit knowledge is personal and context-bound, so it transfers through interaction, observation, and storytelling more than through repositories.
- Information management controls accuracy, timeliness, completeness, relevance, confidentiality, and version. Knowledge management adds interpretation, experience, and reuse.
- The SECI cycle-socialization, externalization, combination, internalization-explains how tacit and explicit knowledge convert.
- A project knowledge management plan should name knowledge assets, owners, capture points, repositories, sharing events, and retention rules.
Worked example
A team stores meeting minutes but engineers still ask a senior engineer how a design decision was reached. The minutes are explicit information but lack rationale, alternatives, and assumptions. Fix: add a decision log capturing context, options, criteria, decision, owner, and date; hold a short after-action review to surface tacit reasoning; link the log to the design file and index it by phase. Reasoning: the gap is tacit rationale, not document volume.
Traps
- Treating a document repository as knowledge management.
- Capturing everything without retrieval value.
- Confusing information quality with knowledge usefulness.
- Ignoring tacit knowledge because it is hard to see.