Strategic Alignment — Did This Produce Value?
The fifth discipline: converting governed AI capability into organizational value you can prove. Five chapters.
3. Reviewing against intent
Four questions after deployment. The order matters, and one of them is almost always skipped.
| Question | Common failure | |
|---|---|---|
| 1 | Accuracy — is the output right? | Sampled once at launch, never again |
| 2 | Efficiency — did it cost less? | Counts AI time, ignores review time |
| 3 | Alignment with intent — is it doing what we meant? | Never asked, because the task succeeded |
| 4 | Downstream impact — what changed elsewhere? | Invisible unless someone looks |
Question 3 is the one that gets skipped — and it is the one Direction exists to catch. A workflow can pass accuracy, efficiency and impact while doing something nobody intended, because the task was completed correctly and the problem it was meant to solve was never restated.
The efficiency trap
Most efficiency calculations count what AI saved and omit what review cost. If verification time is not in the denominator, the number is fiction — and the verification ceiling from Module 3 is precisely the cost being left out.
Evaluating tools, not just capability
Capability is the easy half, and the half vendors demonstrate.
| Criterion | The question |
|---|---|
| Capability | Can it do the work? |
| Boundability | Can its scope be constrained — and is the constraint enforceable? |
| Auditability | Does it record what it did and why? |
| Attributability | Can you tell which actor did what? |
| Exit cost | What does leaving cost — data, workflow, skills? |
Attributability is the one discovered too late. A platform where every action is logged under one shared service identity cannot support after-the-fact accountability, however complete the logs look. That is the Module 4 attribution failure arriving as a procurement decision rather than a bug.