Examples

Best for: recurring incidents, queue growth, change-driven rework
Constraint: decision rights + intake rules not enforced (work starts, doesn’t finish)

Best for: go-live slip, stabilization drag, shared experts across delivery + support
Constraint: no hard boundary between delivery and support (flow collapses into interrupts)

Best for: budget reset “buy lists,” repeated DR debates, spend re-litigation
Constraint: no trusted baseline + requirements + cost/capacity model (decisions become opinion-driven)

Constraint: Unenforced ownership + intake drives waiting, handoffs, rework.
Wave 1 (0–60 days):
- Service ownership + decision rights
- WIP limits per queue/vendor lane
- Change gate: owner, window, backout, minimum evidence
Evidence signals:
- Long waiting states + reassignment loops
- Aging concentrated in a few queues/services
Measures:
- Major incidents/month, MTTR
- Backlog aging distribution, reopen rate

Constraint: Shared experts without an intake boundary caps throughput.
Wave 1 (0–60 days):
- Hard boundary: delivery vs production support
- WIP caps: no new starts until exit criteria met
- Go-live readiness gate + stabilization rules
Evidence signals:
- “Ready” to “started” gaps from contention
- Emergency change concentration in stabilization
Measures:
- Active WIP vs staffing, implementation cycle time
- Stabilization duration, interruption rate

Constraint): No decision-quality baseline/model, so investments reset each cycle.
Wave 1 (0–60 days):
- Baseline of top services/assets + owners
- Minimum requirements: RTO/RPO, availability, security
- Investment gate: capacity, run cost, risk explicit
Evidence signals:
- Conflicting inventories + unclear ownership
- DR artifacts incomplete/misaligned to tiering
Measures:
- Inventory integrity, forecast vs actual variance
- DR evidence completion, findings aging

Pick the example that matches your situation