Traditional performance governance is post-hoc:

• quarterly reports
• attribution after the fact
• committee reviews
• manual oversight
• inconsistent interpretation

This creates structural failure modes:

• Performance drift goes undetected
• Mandate violations appear only after damage is done
• PM decisions deviate from the intended process
• Risk exposures accumulate silently
• Attribution becomes a forensic exercise
• Committees react instead of govern

Performance governance fails because it is open-loop.

There is no system that continuously enforces alignment.

Performance governance is not a reporting problem.
It is a control problem.

To govern performance, an institution must:

• sense performance continuously
• detect drift in real time
• enforce constraints automatically
• align decisions with the mandate
• ensure the process is followed
• close the loop between research → decision → execution → outcome

This requires a closed-loop decision-control system, not dashboards or reports.

1. Continuous Sensing

Real-time monitoring of exposures, decisions, and outcomes.

2. Signal Detection

Identifying deviations from:

• mandate
• benchmark
• risk limits
• intended process

3. Decision-Control Logic

Rules, constraints, and governance logic that determine:

• what is allowed
• what is disallowed
• what requires escalation

4. Enforcement Layer

Ensures decisions remain aligned with:

• strategy
• risk
• performance objectives

5. Learning Loop

Performance outcomes feed back into:

• research
• models
• decision logic
• governance rules

This is the closed-loop that institutions lack today.