San Francisco, CA
Open to remote-first roles
01Regional logistics network / confidential

Fulfillment systems for a regional logistics team

This work started with a noisy fulfillment process, too many manual decisions, and a team spending time firefighting instead of operating. I rebuilt the system around cleaner states, fewer handoffs, and more visible exceptions.

Quick facts
Role
Lead systems partner
Scope
Fulfillment operations, inventory state, and carrier routing
Context
2023 · Operations leadership with cross-functional implementation support
Human control
Operators still reviewed true exceptions before they cascaded into shipping failures.
Proof flow
Fulfillment operating flow
Input
Order intake
Orders entered from multiple sources with inconsistent state naming and missing context.
Checks
State normalization
Mapped inventory, order, and dispatch states into one source-of-truth operating model.
Routing
Exception review
Reserved operator judgment for real mismatches while standard paths routed automatically.
Outcome
Reliable fulfillment
Fewer handoffs, visible exceptions, and cleaner carrier routing under higher volume.
Human controlOperators still reviewed true exceptions before they cascaded into shipping failures.
Measured result
Error rate
12% to <1%
Capacity
+340%
Time saved
40 hrs/week
The problem

What had to change.

A fast-growing logistics team had outgrown its spreadsheet-heavy workflow. Core operating decisions depended on tribal knowledge, which increased errors and slowed the team down as volume grew.

Constraint

Existing workflow had to stay live while the operating model was being rewritten.

Constraint

Data lived across fragmented sources with inconsistent naming and handoffs.

Constraint

The team needed a system that operators could trust, not just a prettier dashboard.

Intervention

What changed in the operating model.

Intervention 01
Defined a clearer source-of-truth model for order state, inventory state, and dispatch logic.
Intervention 02
Reduced human judgment on repeatable paths and reserved manual intervention for true exceptions.
Intervention 03
Made anomalies visible early so the team could fix issues before they cascaded downstream.
System

What now exists.

System 01
A more durable fulfillment workflow with explicit states and cleaner decision paths.
System 02
Exception monitoring that surfaced stuck orders, mismatches, and routing failures faster.
System 03
A simpler operating cadence for reviewing edge cases and improving logic over time.
Outcome

What improved.

Error rate
12% to <1%
Capacity
+340%
Time saved
40 hrs/week
  • Cut fulfillment error rates from 12% to under 1%.
  • Increased weekly volume capacity by 340% without adding headcount.
  • Returned roughly 40 manual hours per week to the core ops team.
Next step

If this looks useful, here are the fastest ways to evaluate fit.