In a bid to improve profitability I recently downloaded the aTimeLogger app in order to see where I spend my time throughout the day.
The idea behind this experiment came from a recent ChooseFI podcast that I’ve previously written about here. Using the data, we can attempt to reduce the travel time and work time for each job, thus increasing the actual hourly rate. We can then pinpoint which jobs pay the least and increase the amount charged per clean. Lastly we can investigate the discrepancies and wide variations in the actual hourly rates.
Actual hourly rates were calculated using this equation. Now lets take a look at the results from week one:
|Day||Type||Travel Time||Work Time||Amount Charged ($)||Actual Hourly Rate ($)|
|Totals||8h 14m||31 h 20m||1541|
So lets look at some of the highlight (and lowlights) from week one’s data:
- Average hourly rate (Commercial) – $37.70
- Average hourly rate (Domestic) – $30.43
- Best hourly rate – $82.64
- Worst hourly rate – $15.53
- Total weekly travel time – 8h 14m
- Weekly income – $1541
The fact that I spend the equivalent of a full work day travelling from job to job blows me away.
I put the discrepancy in hourly rate down to poor estimating. A lot of the lower paying commercial jobs are clients that I took on when I first opened the business. I was keen to build my portfolio and was willing to work at a reduced rate to build clientele. I’ll either increase the price per clean for these clients or swap them out for new clients at a higher rate.
I’ll analyse and attempt to reduce travel time in a future post. Reducing work time for each job while maintaining a high level of quality may be difficult, but I’ll investigate strategies in the coming months.
It’ll be interesting to analyse week two’s data to see if the results are similar to week one.