Tech Solutions / 2026
Replaced a multi-day spreadsheet and macro commission process with a portable Python operations hub around ServiceTrade, payout review, dashboards, and accounting handoff.
Client
Fire & Life Safety Company
Technologies
Python 3.11
Flask
MariaDB 10.6
Docker Compose
ServiceTrade
Asana
CSV Export
GoDaddy Passenger / Gunicorn
Manual cycle
Rules model
Core gain
Project Type
01 – Challenge
Monthly commissions started in spreadsheets, took the owner two to three days to calculate, and still carried accuracy risk. A macro-driven stopgap cut the cycle down, but it still depended on manual ServiceTrade exports, fixed rules, and a workflow that would not scale with a growing sales team.
02 – Approach
Started by mapping the actual payout logic, exceptions, split scenarios, and owner review points instead of trying to automate the spreadsheet as-is. That made it possible to separate source-of-truth job data from payout rules, introduce review checkpoints, and design the system around owner control rather than consultant-only logic.
03 – Solution
Built a Python and Flask operations hub with MariaDB-backed payout data, dynamic commission rules, spiffs, bonuses, penalties, job-level review, payout accounting views, dashboards, onboarding flow, backups, and export paths. The app stays portable to a simple Linux host, supports direct ownership by the client, and leaves room for direct ServiceTrade and Asana automation without Zapier lock-in.
04 – Outcomes
Replaced a multi-day spreadsheet commission cycle with an owner-controlled web workflow
Removed dependence on brittle macro runs and repeated manual ServiceTrade exports
Opened the door to dynamic commission structures, spiffs, and payout adjustments without rewriting the whole process
Created a documented, portable system the business can own, move, and extend over time
05 – The Story
The real problem was not just slow commission math. The business had outgrown a process that depended on one owner, one spreadsheet, and one set of rules that could only evolve through manual effort.
A temporary macro tool bought time, but it also proved the limit of the approach. As the sales team grew and payout logic became more nuanced, the process needed to become a real system rather than a smarter spreadsheet.
So the build focused on control. The owner needed to track jobs, review exceptions, add spiffs, adjust rules, and move payouts into accounting without being trapped in a developer-only workflow.
That led to a portable Python app with dashboards, payout accounting, backup routines, and future direct integrations. It solved the immediate monthly pain while creating a platform the company could actually grow with.
What mattered
The point was not to install software and walk away. The point was to create an operating layer the business could trust, improve, and own after handoff.
That meant documenting the system, making the workflow legible, and removing the extra work that shows up when teams are forced to manage operations across disconnected tools.
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Continue through the work to see another example of strategy, systems, and execution translated into a better operating result.
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© 2026 OCDATA – Michael Bennett
Currently accepting new engagements