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Global last-mile transformation at Amazon scale.
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01 NA · EU · JP · Operating regions
02 DSP 2.0 · Co-developed partner-model redesign
Prior executive retrospectives
Three operating problems. Three durable corrections.
Each retrospective follows the same structure Luna Sol uses today: the operating reality, what was actually done, and the measurable result.
Global delivery economics
A quality failure reframed as a network-value problem.
$25M
validated annual cost avoidance
A legacy labor model under-allocated pre-route and post-route work. Dispatch slipped, rescue activity increased, and driver retention suffered—yet the issue continued to be treated as field execution rather than a planning defect.
1 · Time-motion studies across 15+ station archetypes 2 · A financial bridge linking planning error to dispatch, defects, rescue cost, and retention 3 · The business case rebuilt through three ownership transitions 4 · VP-level approval and embedding into the standing planning cycle
$25M annual cost avoidance · 1,000+ stations affected · 5% YoY defect reduction
Measurement integrity
A 44% reporting gap exposed and corrected.
1,200 bps
hidden degradation quantified
A removed accountability metric and blanket exemptions had created a 44% gap between reported and actual execution. Leadership was making network allocation decisions on distorted signals without knowing it.
1 · Audited completion, quality, compliance, exemption, and classification logic 2 · Quantified a 1,200 bps hidden degradation between reported and actual performance 3 · Designed tiered weather governance and corrected measurement logic 4 · Rebuilt trust directly with delivery partners after the correction
817 bps performance recovered · $1M+ annual cost protected · 18M+ packages reclassified
Peak surge readiness
Record volume absorbed without incremental headcount.
92%+
service compliance
A historic fleet transition, weather volatility, record volume, and a headcount freeze created a peak-season problem that could not be solved by adding analysts or managers.
1 · Built AI-assisted defect attribution and executive reporting 2 · Separated structural root causes from behavioral execution gaps 3 · Targeted coaching across 290 delivery partners 4 · Hardened routing, fleet, and weather governance for the following peak
92%+ service compliance · 1,923 bps routing improvement · 33→ 95%+ field engagement
Measured outcomes
Reported results from prior Amazon operating work.
These figures belong to Ryan’s prior operating context and are kept separate from Luna Sol client outcomes.
$25M
annual cost avoidance
Global delivery economics
1,000+
stations affected
Global delivery economics
5%
YoY defect reduction
Global delivery economics
817 bps
performance recovered
Measurement integrity
$1M+
annual cost protected
Measurement integrity
18M+
packages reclassified
Measurement integrity
92%+
service compliance
Peak surge readiness
1,923 bps
routing improvement
Peak surge readiness
33→ 95%+
field engagement
Peak surge readiness
These retrospectives describe Ryan Miller’s prior employment at Amazon, not a Luna Sol Group engagement. Figures are anonymized where appropriate and reflect the collaborative work of Amazon operating teams and leadership, not solely Ryan’s individual contribution. Amazon is referenced for prior-experience context only; all marks belong to their respective owners.
Why this page exists
Operator credibility, kept separate from client claims.
The three flagship engagements on the homepage are Luna Sol client work. This page is background—the operating pedigree behind the method, not a fourth case study.
Luna Sol keeps these deliberately distinct: a prospective client should never have to guess whether a number on this site came from a paid engagement or from Ryan’s own career history.
01 Role · Global last-mile executive operator
02 Benchmark · 103.8 TPH manual-sortation benchmark
03 Program · DSP 2.0 partner-model redesign, co-developed
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