How recommendations are generated

Pytheus does not hand you a generic best-practice checklist. Every recommendation starts from your own CAMP assessment and the priority math behind it, and you work with them on the Decisions surface.

The inputs are simple. For each in-scope capability, Pytheus Intelligence takes your current maturity, your target maturity, and the capability's criticality. Priority is how far a capability is from its target, weighted by how critical it is. Capabilities with the widest gaps on the most important functions rise to the top.

From there, the engine applies deterministic rules to turn priority into specific suggestions. The same assessment always produces the same recommendations, and each one can be traced back to the capability, the maturity delta, and the criticality that triggered it. There is no black box and no model guessing what you need.

Recommendations are derived, not authored. Change a maturity score or a criticality rating and the list updates accordingly.

This matters because you can defend every line item to your board or auditors. When someone asks why a recommendation exists, the answer is a number you can point to, not an opinion.

The rest of this section covers what recommendations look like and how to work with them:

• Recommendation types

• Expected impact

• Effort

• Why recommendations are capability-driven