The COMPEL Glossary Graph visualizes relationships between framework terminology, showing how concepts interconnect across domains, stages, and pillars. Term nodes cluster by pillar affiliation while cross-references reveal semantic dependencies — for example, how risk appetite connects to control effectiveness, model governance, and assurance requirements. This network representation helps practitioners navigate the framework vocabulary and understand that COMPEL terminology forms a coherent conceptual system rather than isolated definitions.
COMPEL Glossary / reinforcement-mechanism
Reinforcement mechanism
A structured means by which behavior change persists after the formal transformation phase — incentives aligned to new behavior, visible leadership modeling, communities of practice, and continuous feedback loops.
What this means in practice
Corresponds to the R in ADKAR; AI transformations fail at reinforcement more often than at any earlier ADKAR stage.
Synonyms
reinforcement lever , change reinforcement
See also
- ADKAR — Prosci's five-stage individual change model — Awareness, Desire, Knowledge, Ability, Reinforcement — that describes the sequence through which a single person adopts a change.
- Adoption metric — A leading or lagging indicator of transformation uptake — including training-completion rate, active-usage frequency, productivity delta, and worker-sentiment score.
- Training and enablement plan — A designed learning program combining formal training (10%), social learning from peers and mentors (20%), and experiential on-the-job development (70%) — the McCall 70-20-10 ratio applied to AI literacy and capability-building.