At this stage · Read the snapshot and the recommended action, then dig into the evidence below.
Last-Mile Revenue Risk
Volatile driver schedules are driving attrition and capacity loss, putting last-mile delivery revenue at risk.
Executive summary
Last-Mile Revenue Risk is currently rated high, and the trend is worsening. The primary driver is schedule instability, with driver attrition at 21.4% against a target of 10% — 11.4% above where it should be.
Left unmanaged, approximately $42M of business value is at risk, alongside capacity of −8% and growing pressure on driver pool. The forecast shows the situation worsening over the next four quarters without action.
ARBI recommends Approve Schedule Stabilization Program. The moderate action path protects $24M protected with ~57% risk reduction within 3 months. This decision sits with COO + CHRO, targeted for Q3 2026.
Approve Schedule Stabilization Program
- 1Roll out fixed shift patterns + 2-week visibility (0–3 mo)
- 2Targeted retention for high-attrition metro routes (0–4 mo)
- 3Scale AI dispatch pilot to top 10 depots (3–9 mo)
- 4Board checkpoint on future workforce model (Q4)
- • Schedule-stability elasticity of −1.3 holds
- • No structural shift in gig-economy supply
A material change to these assumptions would change the outcome.
The supporting evidence, benchmarks, impact and scenarios behind this recommendation follow below.
Dashboard · severity, forecast & benchmarks
| Metro | Regional | Hub | Night | |
|---|---|---|---|---|
| Van drivers | 26 | 22 | 18 | 14 |
| HGV drivers | 23 | 20 | 16 | 12 |
| Sorters | 15 | 13 | 11 | 9 |
| Supervisors | 12 | 10 | 9 | 7 |
Business impact
- Revenue at risk: $42M
- Cost increase: +$5.9M/yr
- ROI of acting: ~5.5×
- Capacity: −8%
- On-time: Slipping
- Peak resilience: At risk
- Automation delay: Roadmap slipping
- Network expansion: Constrained
- Customer SLA: Exposed
- Driver pool: Unstable
- Stability: Declining
- Supervisor strain: High
Decision options · trade-offs
| Option | Benefit | Cost | Effort | Time | Risk ↓ | Conf. |
|---|---|---|---|---|---|---|
| Workforce Optimization | High | $1.2M | Low | 3 months | Significant (~57%) | High |
| Human + AI LogisticsRECOMMENDED | High | $4.0M | Medium | 9 months | High (~78%) | Medium |
| Retention & Pay Review | Medium | $2.6M | Low | 4 months | Moderate (~45%) | High |
| Future Workforce Model | Very High | $7.5M | High | 18 months | Transformational (~85%) | Medium |
| Combined Stabilize + AI | Very High | $9.0M | High | 12 months | Highest (~88%) | Medium |
Top-left = high impact, low effort (quick wins).
Scenario analysis · five futures (Do Nothing anchored)
Capacity keeps eroding; SLA breaches rise
Attrition continues to ~26%
−$42M
Stabilize schedules; capacity recovers
Attrition drops to ~13%
+$24M protected
Stabilize + pay + hiring surge
Pool stabilizes quickly
+$30M protected
Future workforce model
Roles redesigned around AI
+$36M protected
AI dispatch & route planning
Drivers augmented by AI
+$33M protected
Diagnosis · why this is happening
Schedule Instability
- • Driver Attrition (21.4%)
- • Schedule Stability (48/100)
- • Time-to-Fill (38days)
- • Delivery Capacity vs Plan (92%)
- • On-Time Delivery (91.2%)
- • Route Productivity (87%)
- • Regional Driver Supply (Tightidx)
- • Driver Wage Inflation (+6.1%)
- • Gig-Economy Competition (Highidx)
Evidence · 22 indicators (with benchmarks)
Trust · why you can rely on this
22 indicators across 6 categories, each with PY / target / industry benchmarks.
Data → analysis → insight → business risk. Open full trail →
Deterministic: evidence quality, source coverage, framework support and freshness.
- • Schedule-stability elasticity of −1.3 holds
- • No structural shift in gig-economy supply
- • AI dispatch reaches 70% depot adoption
- • Demand grows ~3%/qtr
Decision record
Captured in-session · backend persistence to follow.
Connected topics · how this issue ripples outward
Last-Mile Revenue Risk doesn't sit alone. These connected topics are influenced by the same drivers — exploring them shows how one issue propagates across the enterprise. (Workspaces built out in the next phase.)
- 1Route Productivity · expanding soonConnected because driver attrition directly erodes route output.
- 2Distribution Capacity · expanding soonConnected because capacity loss flows from the same workforce instability.
- 3Automation Readiness · expanding soonConnected because AI dispatch is the structural fix for the schedule problem.
- 4Future Workforce Readiness · expanding soonConnected because the long-term model reshapes these roles.
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At this stage · Read the snapshot and the recommended action, then dig into the evidence below.