Adoption is 50%. Is the program working?
The headline hides the denominator and the behavior the customer needs.
“it’s hard to measure the impact that this champion is having internally” (opens the source)
The question
LanternFlow is a fictional approval-workflow vendor. Aster Manufacturing bought 200 seats. The counts below use the same final week of a four-week observation. The sustained users are among the final-week workflow completers.
| Users | |
|---|---|
| Licensed | 200 |
| Enabled | 160 |
| Active in final week | 80 |
| Completed target workflow in final week | 48 |
| Completed it in at least 3 of 4 weeks and in final week | 36 |
A separate non-random pilot has two groups of 40. Training group completion rises from 12 to 24; comparison group rises from 16 to 20.
“Explain the 50% headline. What is sustained use, and what does the pilot prove?”
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A strong answer, step by step
Open each step in turn. This is one strong answer, not the only one.
Step 1: Name the denominator
What would you do here? Open the move you’d make.
Call the whole account 50% adopted.
Tempting, but it misses something. That hides whether the denominator is enabled or purchased seats.
Show both denominator labels.
The strong move. Both rates are valid if their labels are clear.
See how a strong candidate says it
“Weekly active use is 80 / 160 = 50% of enabled seats, or 80 / 200 = 40% of licensed seats.”
Why it works: Both rates are valid if their labels are clear.
Step 2: Follow the target workflow
What would you do here? Open the move you’d make.
Measure sustained workflow completion.
The strong move. The customer needs repeat workflow completion, not only a login.
Use logins as the completed business outcome.
Tempting, but it misses something. Activity does not show whether the approval workflow ran.
See how a strong candidate says it
“48 / 80 = 60% of active users complete the workflow. Sustained completers are 36 / 200 = 18% of licensed seats.”
Why it works: The customer needs repeat workflow completion, not only a login.
Step 3: Compare changes
What would you do here? Open the move you’d make.
Attribute all 12 added users to training.
Tempting, but it misses something. Four more users appeared in the comparison group too.
Subtract the comparison-group change.
The strong move. The comparison accounts for a change that happened without training.
See how a strong candidate says it
“The training group improves 30 percentage points; the comparison improves 10. The difference is 20 points, or eight users in a group of 40.”
Why it works: The comparison accounts for a change that happened without training.
Step 4: Keep the causal limit
What would you do here? Open the move you’d make.
Investigate the repeat-use gap and strengthen the next test.
The strong move. A descriptive comparison is not proof that training caused adoption or renewal.
Promise retention from the pilot result.
Tempting, but it misses something. The pilot did not measure renewal and was not randomized.
See how a strong candidate says it
“The pilot is not random. Selection, timing or another change could explain part of the difference.”
Why it works: A descriptive comparison is not proof that training caused adoption or renewal.
The answer, in short
- Decision
- Keep the denominator visible and investigate sustained workflow use.
- Because
- The 50% headline answers a narrower question than the customer’s outcome.
- What would change it
- If the comparison group rises from 16 to 28, the difference in changes becomes zero.
The comparison group now reaches 28 users. What can you still claim?
Common traps
- Confusing enabled seats with licensed seats.
- Calling a non-random before/after difference causal.
Check your answer
- I named the denominator.
- I separated login and workflow completion.
- I calculated the comparison change.
- I stated the causal limit.
Last reviewed Nov 10, 2026