Review cycle
A review cycle is the agreed rhythm and set of triggers for checking whether captured knowledge — processes, instructions, decision rules — is still correct, and for confirming, correcting or retiring it. A good review cycle combines a fixed rhythm based on risk with events that force a review immediately.
What is a review cycle for captured knowledge?
The rhythm follows the risk: knowledge behind safety, quality, customers or money is reviewed more often than stable routine. The triggers are events after which knowledge may be wrong: a new system, a changed customer agreement, an incident, a person leaving or joining the process, or an answer that turned out to be wrong.
A real review checks the knowledge against a recent case, records who confirmed it and when, and keeps earlier versions rather than overwriting them.
Not to be confused with a revision history, which only records changes, or an audit, which is an independent check at a moment in time. A review cycle is the owner's routine that keeps knowledge current in between.
Why it matters for SMEs
For example: a food producer reviews its allergen procedures every quarter against a real production run, and immediately when a new labelling machine arrives — not at the next scheduled date.
For SMEs, a light review cycle is what keeps captured knowledge from becoming another document nobody trusts. See how often to revalidate captured knowledge.
Review cycle in the MentX approach
MentX captures how your company really works: the knowledge of your key people and the processes they run. We offer both a hands-on service approach — mapping your processes and capturing the knowledge behind them, from meetings, workshops and a guided intake — and our own personality-aware knowledge base, with full source attribution, in your own Knowledge Space. We build on the tools you already use and add best-practice solutions where they fit.
In the MentX knowledge base every statement keeps its source and its date, and newer knowledge replaces the old without erasing it — the temporal knowledge graph. Owners and triggers are agreed when you capture your operations.