RCM Insights: Discover
Objective. Use Discover to find what is genuinely askable of the data, without assuming that a suggested question means the data is complete or fresh enough to commit on.
Discover helps a user find what they can meaningfully ask - the questions the data can support and the directions worth exploring. It answers 'what can I actually ask here', orienting a user who does not yet know the shape of the data.
See it in the demo
What this screen answers
Discover answers the orientation question for a business user: given this data, what is worth asking and what will produce a supportable answer? New users do not know the shape of the data and waste Ask on questions it cannot support. A Sales person uses Discover to show the breadth of askable business questions; a CSM uses it to steer users toward decision-linked questions and away from ones the data cannot yet answer.
The task
Browse the suggested or discoverable questions and pick ones that map to a real RCM decision. Use Discover to shortlist, then move the chosen question into Ask and inspect its evidence there. Treat Discover as a menu of directions, not a set of answers. The task is explore, shortlist, hand to Ask - described at that level, without inventing control names or claiming a suggested question is pre-validated.
How to read it
The classic misread is assuming that because a question appears in Discover, the data behind it is complete, fresh and ready to commit on. Discover shows what is explorable, not what is validated - a suggested question can still sit on thin or stale data. So a discoverable question is an invitation to ask and inspect, never a pre-approved answer. Carry the same discipline through: once you pick a direction, verify its evidence in Ask and Data before it informs a decision.
Honest limits
This screen proves the discovery model on seeded data. It does not prove that every suggested direction has live, fresh, well-defined data behind it for a given customer. Confirm the connected sources, freshness and definitions with product before treating any discoverable question as answerable for the customer. Discover widens the aperture; evidence inspection still gates trust.
Interpretation check
A question appearing in Discover means it is explorable, not that the data behind it is complete, fresh or validated - a suggested question is an invitation to ask and inspect, not a pre-approved answer.
Practical task
In the demo Discover screen, pick two suggested questions that map to real RCM decisions, carry one into Ask, and write a one-line verdict on whether the evidence behind it is strong enough to act on - noting that Discover surfaced it but did not validate it.
Self-check
A user says 'it is in Discover, so the answer must be reliable.' What do you correct?
Discover shows what is explorable, not what is validated. The data behind a suggested question can be thin or stale - the question still has to be asked and its evidence inspected before it is trusted.
How should a CSM use Discover with a new user?
To steer them toward decision-linked questions the data can support and away from ones it cannot, then teach them to verify evidence in Ask and Data before acting.
What is the right relationship between Discover and Ask?
Discover shortlists directions worth exploring; Ask produces the answer with inspectable evidence. Discover is the menu, not the meal.
What must be confirmed with product before a discoverable question is answerable for a customer?
The connected sources, their freshness and the metric definitions behind that direction - otherwise the suggestion may not be supportable on the customer's live data.
Verified vs demo. Screen is live in the demo at /#/discover; the discovery of askable questions is demo-shown on seeded data, and exact controls, suggestion logic and figures are SME-validation-pending. Live sources, freshness and definitions behind each suggestion are production-dependent - confirm with product.