A supply chain manager may know how to use a forecasting platform after an onboarding workshop, yet still need help when new features arrive or better ways to interpret forecasts emerge. Everboarding is ongoing product education for those changing needs. For AI products, a new feature or a substantial change in design or performance is an opportunity to explain what has changed and how to use it. section 12.3.4 section 10.2.2
Match the help to the moment and the user:
- Offer regular webinars for updates, feature demonstrations, and advanced use cases. section 12.3.4
- Maintain a knowledge hub for on-demand articles, videos, and documentation; provide a community forum for questions and peer learning. section 12.3.4
- Put brief explanations where users need them through tooltips or contextual help, while keeping fuller documentation available for people who need more detail. section 12.3.4 section 10.2.2
After the first workshop
Supply chain managers first learn to navigate a predictive platform, enter data, and interpret forecasts in a live workshop. Monthly webinars then highlight emerging optimization practices, while a tooltip explains confidence intervals at the point of use. The workshop starts the learning; the webinars and in-product help keep it going. section 12.3.4
Everboarding complements initial onboarding rather than replacing it. It also provides a reason to revisit guidance when an AI feature changes: users should not have to infer new behavior solely from the interface, especially when much of the AI interaction happens under the hood. section 12.3.4 section 10.2.2
