Pattern identified
Approval Bottlenecks
163 people are waiting on sequential human approvals.
163
Related signals
12
Departments
1,180
Est. hours / month
4
Systems involved
HIGH
Cross-department relevance
What people are experiencing
“Getting approval requires emailing four different people.”
“Everything stops if one approver is out of the office.”
“Nobody can tell me where in the approval chain my request currently is.”
20 submissions in this prototype dataset describe this pattern.
What connects these?
AI has identified recurring characteristics across these submissions. People decide which of them matter.
- Sequential review
- Approvals happen one after another rather than in parallel.
- Single points of delay
- One absent approver halts the whole request.
- Uniform thresholds
- Low-risk requests receive high-risk scrutiny.
- No visible status
- Requesters cannot see where a request currently sits.
Accept the constraint. Find the possibility.
Can't change — right now
- Existing statewide platforms
- Current vendor contracts
- Reporting obligations
- Security requirements
- Current staffing levels
Can change
- How information moves between systems
- How repetitive work is performed
- How reports are generated
- How exceptions are surfaced
- How teams share information
Illustrative demonstration data