Watch the real work
Start with the people doing the planning. Review the calendar, driver logs, trailer inventory, spreadsheets, and recordings of the decisions being made in real time.
Case study 01 · Reeder Pallet
From one person’s memory to a planning system.
Daily dispatch depended on judgment built over years. The goal was not to replace it. The goal was to make it visible, repeatable, and easier for the team to run.
The assignmentScale without losing the operation
The business wanted to grow without doubling headcount.
Routing, trailer movement, production, and inventory decisions were carried by one experienced operator and a manually maintained planning process. A generic route optimizer would miss the reasons the operation worked.
We started by learning the work, then built the smallest useful system around the decisions that actually mattered.
How the work movedEvidence before automation
Build the system with the operation, not around it.
Make the rules visible
Normalize destinations, identify recurring route patterns, and turn constraints around drivers, trailers, timing, inventory, and customer commitments into explicit logic.
Build around judgment
Create a short-horizon planning board that suggests drivers and trailers, groups compatible loads, flags conflicts, and explains why. The planner stays in control.
Learn from real use
Put the system in front of the operation, record what breaks trust, and carry that feedback back into the data model, planning logic, and interface.
The working systemSource to decision
A visible path from incoming work to the next decision.
See the operation
- Upcoming orders
- Driver history
- Trailer locations
- Recurring routes
- Recorded planning decisions
Make a useful plan
- Normalize destinations
- Pair compatible loads
- Suggest drivers and trailers
- Detect conflicts
- Explain each recommendation
Keep a human in control
- Dispatch plan
- Load queue
- Unload queue
- Review states
- Overrides and corrections
What changedEarly operating proof
The work moved from an idea to something the team could react to, correct, and improve.
“We’re leaps and bounds ahead of where we were two or three weeks ago. This is amazing.”
The part that matters
Real operations expose what the first version cannot know.
New orders changed route pairings. Accepted plans needed durable identities. A trailer could not quietly belong to two drivers. Every feedback recording made the next version more trustworthy.
That is what working with Techology looks like: inspect the live system, make hidden rules explicit, build the smallest useful version, and stay with it until it holds up under real use.
Start here
Have a system only one person knows how to run?
Tell me how the work happens today and where it starts to break. I’ll reply directly.
Tell me what’s stuck