> ## Documentation Index
> Fetch the complete documentation index at: https://docs.alignr.io/llms.txt
> Use this file to discover all available pages before exploring further.

# 2. Run and explain the assessment

> Learn what passing, failing and incomplete evidence look like in one worked example.

**Journey:** [Overview](/journeys/first-assessment) → [Establish evidence](/journeys/connect-and-map) → **Assess** → [Follow up](/journeys/close-the-loop)

We will assess whether Acme's observed Global Administrators have MFA registered. The examples below assume suitable source coverage and current, eligible evidence; the app also applies its coverage and freshness rules.

## Choose and run the standard

<Steps>
  <Step title="Copy the identity template">
    In **Standards → More → Browse library**, choose **BIOS Identity Assurance** and copy it. The copy starts as a disabled draft.
  </Step>

  <Step title="Review the question">
    Review the **Global Administrators use MFA** control, its population, expectation and settings. Review the other controls and manual checks in the template before enabling the standard.

    **Checkpoint:** you understand that this control selects the Global Administrator role and checks MFA registration. Its name does not establish sign-in policy enforcement.
  </Step>

  <Step title="Enable the reviewed standard">
    Open the copied standard and select **Review & enable**. Turn on **Enabled**, then select **Save changes**.

    **Checkpoint:** the standard shows **Enabled**, and the controls you intend to assess are enabled too. The final **Run checks** action stays unavailable while the parent standard is disabled.
  </Step>

  <Step title="Run checks">
    Select **Run checks** from Standards. Review the selected standard, clients and settings, then confirm **Run checks for N clients**. Inspect the results after evaluation finishes.

    **Checkpoint:** the result belongs to the intended client and control, with an evaluation time you can identify.
  </Step>
</Steps>

## Work through the result

The accounts below are fictional examples. Switch between scenarios to see how the conclusion changes.

<Tabs sync={false}>
  <Tab title="Pass">
    | Account | Observed role        | MFA registered |
    | ------- | -------------------- | -------------- |
    | Alex    | Global Administrator | `true`         |

    The selected population contains Alex. The registration observation satisfies the expectation, so this simplified example **passes**.

    **Your next question:** does the selected population and source coverage represent the accounts you intended to assess? This result establishes registration for the assessed population.
  </Tab>

  <Tab title="Fail">
    | Account | Observed role        | MFA registered |
    | ------- | -------------------- | -------------- |
    | Alex    | Global Administrator | `true`         |
    | Morgan  | Global Administrator | `false`        |

    Morgan's observed false value contradicts the expectation, so the control **fails**. Alex's satisfying observation does not cancel that failure.

    **Your next action:** inspect Morgan's evidence, confirm the account's purpose and ownership, then review an appropriate change.
  </Tab>

  <Tab title="Missing evidence">
    | Account | Observed role        | MFA registered |
    | ------- | -------------------- | -------------- |
    | Alex    | Global Administrator | `true`         |
    | Sam     | Global Administrator | No observation |

    Sam is in the selected population, but the required observation is absent. This simplified example is **No data** (`no_data`), because the evidence cannot establish a complete pass.

    **Your next action:** investigate collection, permissions and account identity matching. Missing evidence is not a registration value of false.
  </Tab>
</Tabs>

## Two cases that are easy to misread

<AccordionGroup>
  <Accordion title="What if Morgan fails and Sam has no evidence?">
    The known contrary observation still proves a **fail**. The result does not mean the assessment has complete coverage. Investigate Morgan's failure and Sam's missing evidence as separate follow-ups.
  </Accordion>

  <Accordion title="What if no administrators are observed?">
    An empty observed population produces **No data** in this example. It does not establish that the client has no administrators or that every administrator satisfies the control.
  </Accordion>
</AccordionGroup>

## Explain the result to someone else

A useful explanation follows this pattern:

> We assessed Acme's observed Global Administrators for MFA registration. Morgan's registration observation was false, so the control failed. Sam's registration observation was missing, so coverage also needs investigation. We still need a separate review of effective MFA enforcement.

In a real handover, include the actual source, observation time and evidence references. Do not copy the example names into a client report.

**Checkpoint:** you can distinguish contrary evidence from missing evidence and explain the limit of the conclusion. For other statuses, use [Understanding control results](/guides/control-status).

<Card title="Next: decide what happens next" icon="arrow-right" href="/journeys/close-the-loop">Turn the assessment into an owned, verifiable follow-up.</Card>