# Revenue Per Day

I learned this principle nearly 40 years ago, though I couldn't have articulated it the way I can now. I was working mega mansions that took 8 to 10 months, sometimes a full year. Nearly every day, I drove to the same job site, and eventually, I began to wonder what other opportunities I could have pursued that year and how much I could have earned by doing something different.

Then I encountered a case that made my thoughts concrete. I completed a 5,800 square foot house in the same amount of time it took me to do 11 other jobs. Those 11 jobs generated more revenue and more profit than the single large house that consumed the same calendar time. That comparison changed how I evaluated every job after that.

The metric that makes this pattern visible is revenue per day. Take the total job revenue and divide it by the number of days (or trips) the job consumed. That's it. The number tells you immediately whether a job is worth taking under a cherry-picking model.

Here's an example from another contractor. He gave a client a fixed price of $6,600 for a repaint. The job took 16 trips. Whether those were full days or partial days doesn't matter for this calculation. $6,600 divided by 16 trips equals $412.50 per trip. That number is the diagnosis. It shows whether the job performed well or poorly compared to other work he could have taken during those same 16 days.

The mega mansions look profitable because the total contract value is high. An $80,000 project sounds substantial until you divide it by 200 days on site. That's $400 per day. If you can do smaller jobs that average $1,500 per day, you'd make more money doing 200 days of that work than you would on the mansion. The mansion ties you up for months while better opportunities pass by.

The result is opportunity cost made visible through simple math. Every day you spend on a low-performing job is a day you can't spend on higher-performing work. Painters chase big total contract values without tracking how many days those contracts consume. They brag about landing the $80,000 mansion without calculating what they're actually making per day. Then they wonder why their year-end numbers don't match their expectations.

I had a [$3 million account](https://jackpauhl.gitbook.io/archive/field-notes/business-strategy/how-i-landed-usd3-million) in the past painting new construction homes for a builder. What I valued about that account was the predictable time structure. The builder gave a two or three day schedule to get each house painted, depending on the size. Two-story larger builds got three days. Smaller single-floor homes got two days. That's it. You knew exactly how many days each job would consume before you started.

That predictability let me calculate revenue per house divided by two or three days and know immediately whether each house type was profitable. More importantly, I could plan how many houses I'd complete in a month. The fixed schedule also forced efficiency. You had to complete in two to three days, which eliminated the drift that happens on jobs without firm boundaries. The 16-trip repaint probably could have been 8 to 10 trips with better structure, but without constraints, [work expands to fill available time](https://jackpauhl.gitbook.io/archive/field-notes/operations-systems/milking-the-clock).

The builder account had four advantages. First, predictable time commitment. Second, known volume potential. Third, predictable payment schedule—a check every two weeks. Fourth, consistent work with low variability. Multiple houses instead of one mansion eating up months, steady cash flow instead of waiting 60-90 days for one large payment after months of work, and repeating the same process instead of constantly adapting to unique conditions.

Here's what this process looks like in practice. Track revenue per day for every job you complete. Create a simple record with job name, total revenue, days on site, and daily rate. After six months or a year, sort that data by daily rate. The pattern becomes obvious. You'll see which job types, client types, or project characteristics consistently deliver higher daily rates. That tells you what to pursue and what to avoid.

This isn't about hitting some arbitrary target rate. It's about comparing job performance against each other to identify which types of work are more profitable per day. A $6,500 job that takes two days generates $3,250 per day. Another $6,500 job that takes five days generates $1,300 per day. Same total revenue, vastly different performance. One job left $3,700 on the table compared to what five days could have generated at the higher rate.

The insight here is that total contract value is a misleading metric if you're trying to maximize profit. What matters is how much you make per day and how many of those days you have available in a year. You can't work more than approximately 200 days per year accounting for weekends, weather, materials delays, and scheduling gaps. If you fill those 200 days with work averaging $400 per day, you'll make $80,000. If you fill those same 200 days with work averaging $1,500 per day, you'll make $300,000.

The difference isn't working harder or longer hours. It's selecting different work. That's what cherry-picking means. You're choosing which jobs to take based on profitability per day, not based on total contract size or keeping the schedule full. This is why volume-based thinking fails. More jobs doesn't equal more profit if those jobs perform poorly per day.

Painters operating without this metric are flying blind. They can't distinguish between work that's actually profitable and work that just feels busy. They take whatever comes in to keep the schedule full, then wonder why they worked all year and have little to show for it. The schedule was full, but full of low-performing work.

Track the metric. Sort the data. The pattern will show you what to pursue and what to avoid.

Be sure to check out [The “Flaw of Averages” in Cost Estimating](https://jackpauhl.gitbook.io/archive/field-notes/industry-analysis/the-flaw-of-averages-in-cost-estimating)