Estimating and Tracking Effort on the Campus Careers Website
08 May 2025
Effort estimation: the process of forecasting the amount of time required to complete a task or project.
As part of our work on the Campus Careers Website, our team made a conscious effort to estimate and track the time spent on each issue using a shared spreadsheet. This practice was required, but also incredibly enlightening. What follows is my personal reflection on what I learned from this process.
How I Made My Effort Estimates
I began by reading through each issue listed in our shared Google Sheet and breaking them into smaller subtasks. I considered complexity, technical challenges, and previous experience. Discussions during sprint planning also helped align expectations. For example, implementing the form validation logic for company submissions looked simple but needed time for testing and integration, so I estimated more hours up front. I added buffer time for debugging, especially for pages with heavy client-server interaction.
The Benefits of Estimating Ahead
Even though estimates weren’t always accurate, they added structure to the sprint. Having a timeline gave me accountability, especially since our estimates were shared with the group. It made prioritization easier and encouraged better time allocation. Even when I overestimated, the extra time was useful for refining UI/UX elements, testing more thoroughly, or documenting my work.
The Value (and Cost) of Tracking Effort
Tracking actual time helped identify trends. For instance, I noticed I was spending more time on backend tasks than expected, particularly on handling edge cases with Prisma and form data validation. This data helped in our retrospectives and personal reflection. The downside? Occasionally forgetting to log time right after a task—but once it became part of my routine, the benefits far outweighed the effort.
Tracking Actual Effort and Estimating Accuracy
We used a centralized spreadsheet with columns for task name, estimated hours, actual hours, and notes. I usually logged time right after completing a task. If I forgot, I’d review my Git commits or messages in Discord to reconstruct my work session. I’d estimate my tracking accuracy at around 85–90%, with minor gaps during long, focused debugging sessions.
Time Spent on Timekeeping
Logging time took 5–10 minutes a day. At first, it felt like overhead, but I eventually viewed it as a small habit with high payoff. By the end of the project, we had a clear view of which areas were time sinks and how we had progressed over time. This made finalizing features, preparing documentation, and wrapping up easier. It also gave us confidence that we were building the project mindfully and efficiently.
Final Thoughts
Effort estimation and tracking weren’t just busywork—they were tools that helped us reflect, plan, and improve. For the Campus Careers Website, this practice shaped how we approached our work and gave us a foundation for better collaboration.
Ultimately, the biggest insight was this: you can’t improve what you don’t measure.