How a Numbers Mindset Helped Me Clear 50+ Tickets a Week

If you think math is just formulas on a whiteboard, you’re missing its best gift: a way of thinking. Math trains you to frame messy reality as solvable problems define variables, model constraints, test hypotheses, and choose the most optimal path. That mindset isn’t only for classrooms. It’s the compass I used to navigate one of the toughest weeks of my internship at Neybor, where I worked as a property & operations manager.

Math Is More Than Numbers It’s a Toolkit for Life

What does learning math actually give you?

• Critical thinking: break big problems into components, question assumptions, and compare scenarios.

• Problem solving: design step-by-step strategies, not one-off reactions.

• Calm under pressure: complex systems feel less scary when you can model them.

• Decision quality: evaluate trade-offs with clarity, not guesswork.

Personally, math has changed how I plan, organize my day, and stay resilient when things go sideways. It’s also how I tackled a real operations crisis, also it's so cool to have as a skill.

The Problem:

At Neybor, maintenance tickets had piled up 50+ per week. The manager was unavailable, so I had to take point. The issues weren’t just technical; they were organizational:

• Teams were doing tasks outside their scope because of absent employee (e.g., bulk deliveries, laundry runs, ad-hoc tenant requests).

• In the app, room numbers weren’t visible, which created extra on-site friction.

• Crews would visit a house, fix half the issues, then switch to another house far away.

• That meant time lost in traffic and incomplete visits frustrating residents who had already waited too long.

Everyone was busy. But the system wasn’t working.

The Math Solution: 

Instead of telling the team to “work harder,” I treated the chaos like an optimization problem.

1) Group by House (Clustering the Demand)
Tickets were reorganized by house and priority. The goal: finish all tickets in a house before moving to the next, rather than scattering effort across the city.

2) Prioritize Rationally (Weighted Queue)
Not all tickets are equal. I created a simple priority score (high > medium > low, with a bump for houses holding many tickets). This ensured urgent and dense clusters came first.

3) Plan by Geography (Shortest Route Wins)
Maintenance time isn’t just wrench-in-hand time; it’s travel time, parking, and unlocks. So we planned daily zones: each day focused on a geographic cluster of houses to minimize travel and maximize time on site.

4) Keep Slack for Emergencies
We built a margin into every day to absorb urgent, last-minute issues without detonating the entire schedule.

Execution: A Clear Plan 

First, I prototyped the plan in Excel to group tickets and to build a day-by-day route. Then, we informed tenants of the exact day we would pass, which did two things:

• Set clear expectations (less anxiety, fewer “any update?” messages).

• Reduced rework (fewer missed visits, because residents were prepared).

Result: the maintenance team felt relief, tenants felt heard, and we cleared the backlog. The difference wasn’t magic; it was structure.

The Math Behind:

This kind of scheduling looks fancy, but the core ideas are simple:

• Clustering: handle everything in one location before jumping across town.

• Routing: find the shortest path that visits all required stops (a classic math problem called the Traveling Salesman Problem, or TSP).

• Capacity & Time Windows: extend TSP to multiple crews, daily work limits, and service times known as the Vehicle Routing Problem (VRP).

You need a habit: define the inputs, choose a strategy, and iterate.

From Spreadsheet to Script: Leveling Up With Python

After the Excel version worked, I started moving toward a Python solution. Why?

• Repeatability: run it weekly without rebuilding everything by hand.

• Speed: let the computer test routes and pick the best.

• Fairness: objective rules reduce the “who shouts loudest” bias.

The basic recipe:

1. Data in: list of houses with coordinates, number of tickets, and priority.

2. Scoring: compute a priority score so urgent clusters float to the top.

3. Routing: build daily routes that minimize total travel time while respecting a work-day limit and service durations.

4. Output: a clear per-day, per-crew plan with Estimated Times of Arrival (ETAs), plus a ready-to-send notice to tenants.

This is math as a service to people: fewer delays, less guesswork, more trust.

Lessons You Can Steal for Your Team

• Name the bottleneck. Is it travel, scheduling, scope creep, or missing information? Fix that first.

• Batch work smartly. Group by location and priority; finish what you start.

• Protect focus. Limit context switching across distant addresses.

• Communicate proactively. Share specific visit days; it buys goodwill and saves you messages.

• Leave buffer. Plans without slack break the moment reality shows up.

• Automate the routine. If your plan works in Excel, consider a script to run it weekly.

Why Math Is the Best Thing You Can Learn

Math won’t turn you into a robot. It does the opposite: it frees your attention for the human parts of the job listening to residents, supporting the team, and staying calm when things get messy. It helps you:

• analyze obstacles without panic,

• form and test hypotheses,

• choose the most optimal path given real limits.

That’s what I did at Neybor. It’s what you can do on any team with too much work and too little time. Start small. Organize by house and priority. Plan by zones. Share ETAs. Iterate. You’ll feel the difference in a week.

Math isn’t just a subject. It’s a superpower for getting real-world work done faster, calmer, and better for everyone.