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Jackson Macdonald
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Enterprise Automation · Implementation · Adoption

Turning a manual POS migration into a scalable implementation system

A large franchise POS migration was being coordinated almost entirely by hand. I redesigned the operating workflow around self-service scheduling, calendar-triggered automation, centralized tracking, templated communications, and exception management.

migration throughput increase
coordination (was 20–30 hrs/wk)
~20 min/wk
centers in rollout
~200
ahead of Dec. 31 target
~2 mo early

The problem

When I took over the migration, the technical rollout was only part of the problem. The coordination around the migration was highly manual.

For each store, someone had to call the location, compare schedules, agree on a migration date, send a one-off calendar invitation, manually record the migration, manually track which communications were due, write and send reminder emails, monitor replies, and determine whether intervention was needed.

At that point, the program was migrating roughly 2 centers per week. Managing scheduling, communications, and follow-up consumed approximately 20–30 hours per week. Every location that remained on the legacy system also carried an additional cost of $125 per month. The project had a target completion date of December 31.

Before: a person as the orchestration layer

The process required a person to act as the orchestration layer. That did not scale across hundreds of locations.

The redesign

The goal wasn't to automate the migration. It was to automate the coordination around the migration so the team could focus on the locations that actually needed attention.

The redesigned workflow moved the predictable path into the system and preserved human involvement for exceptions.

The new workflow

Inside the system

1. Self-service scheduling

The store scheduled its own migration. This removed the need for repeated phone calls and calendar coordination.

2. Calendar as the event source

The calendar became the trigger for the workflow. Once a migration was scheduled, the event could drive everything that followed.

3. Zapier as the orchestration layer

Zapier detected the scheduled migration and moved the relevant information into the tracking system — not a complex backend architecture, just the connective layer.

4. Spreadsheet as the first database

The original tracking layer was a spreadsheet. It was not a sophisticated database, but it was sufficient for the need and allowed the process to be implemented quickly.

Use the simplest system that reliably solves the problem.

5. Date-based communication logic

The migration date controlled which communication should be sent and when — 6 weeks, 1 month, 2 weeks, 1 week, and 1 day out, each communicating what mattered at that point in the migration.

6. Reply alerts

A reply did not disappear into the automation. A response created an alert for Jackson to review — a human-in-the-loop exception path.

7. Monday.com evolution

The workflow later moved from the spreadsheet into Monday.com, adding clearer statuses, ownership, dashboards, more automation, and better operational visibility.

Architecture view

Human-in-the-loop design

The system handled the normal path. Human attention was reserved for replies, unusual questions, blockers, exceptions, and location-specific issues.

Business impact

Throughput

Before

~2 centers/week

After

~14 centers/week

Approximately 7× higher migration throughput.

Administrative effort

Before

20–30 hrs/week

After

~20 min/week

The recurring scheduling and communication workload became a short Monday-morning exception review — roughly a 98% reduction in recurring administrative effort.

Project timeline

Target

Dec. 31

Actual

First week of Nov.

The rollout finished nearly two months ahead of the target date.

Financial consequence

$125/mo

cost per unmigrated center

Accelerating the migration reduced the amount of time locations remained on the legacy platform and therefore reduced recurring platform costs across the network.

My role

I redesigned the coordination workflow, implemented the automation layer, standardized the communications, created the tracking model, and managed the migration program.

  • Process redesign
  • Workflow automation
  • Implementation management
  • Stakeholder communication
  • Migration tracking
  • Exception handling
  • Adoption
  • Reporting
  • Operational improvement

What this demonstrates

  • Enterprise implementation
  • Workflow automation
  • Zapier
  • Monday.com
  • Process redesign
  • Human-in-the-loop systems
  • Change management
  • Adoption
  • Operational reporting
  • Scale
  • Business impact

The automation didn't just save my time. It increased the capacity of the migration program itself.

The best automation often removes the coordination bottleneck around the work rather than trying to automate the work itself.

Building AI systems that have to work in the real world?

I’m interested in AI implementation, deployment, transformation, forward-deployed, and product-adjacent roles where I can own the path from business problem to deployed outcome.