Learn how to turn daily technician time data into a clear utilization scorecard you can actually manage. In this lesson, you’ll build a month-by-month view by technician, calculate annual averages, and create visuals (including a heat map and summary chart) that quickly reveal where scheduling and dispatch performance is strong or breaking down.
Download the Excel file used in this tutorial:
Result: Months run down the rows, technician names run across the columns.
Goal: For each technician and month, calculate:
Important detail from the video:
When you copy the formula across technicians and down months, you must lock references correctly.
Result: The entire monthly utilization matrix fills in correctly.
This row calculates annual utilization per technician using totals (not averaging the monthly percentages).
Key point shown in the video:
The video recreates the same structure, but groups technicians by Tech Level instead of technician name.
Q1. What is a tech utilization rate in service operations?
Tech utilization rate measures how much of a technician’s available time is spent on billable work. It’s a core service operations KPI used to understand productivity, staffing efficiency, and whether your scheduling process is working as intended.
Q2. Why is utilization such an important KPI to track?
Utilization helps you spot issues that directly impact profitability, like under-booked techs, overbooked schedules, and patterns that lead to costly overtime. It also turns operational complexity into a simple scorecard you can review weekly or monthly.
Q3. What data do I need to follow along with this tutorial?
You need a daily log that includes: date, technician name, billable hours, and available hours. Many service platforms can export this, and if you don’t have software, you can still track it in a spreadsheet as long as time is recorded consistently.
Q4. What will I be able to build after watching the video?
You’ll build a utilization table by month and technician, create an annual average utilization summary, and add visuals like a heat map and a chart that makes performance differences easy to see across techs or tech levels.
Q5. How should I interpret “high” vs “low” utilization?
High utilization isn’t always “good” and low isn’t always “bad.” Extremely high utilization can hurt quality, customer experience, and team burnout. Many teams aim for a practical sweet spot (often around the mid-range) based on service type, travel time, and workload.
Q6. Can I analyze utilization by technician level or service type too?
Yes. In the tutorial, you’ll see how to summarize utilization not only by individual technician, but also by tech level, and you can extend the same approach to service types like maintenance, installs, or repairs if your data includes that field.
Q7. Where do I get the sample dataset used in the video?
There’s a download link in the video description (and/or the book resources). If you can’t find it, you can email and request the service ops tech utilization rate file.