Workforce Management: Using Data to Determine Labor Efficiency
As a professional working in a labor-intensive industry, you understand the importance of efficiency and making the most of the money that is available. Before Cartegraph, I worked for a Utilities department that had limited resources. Like you, I wanted to figure out the best way to save existing dollars, while maximizing productivity. The result of my effort was an eye-opening discovery that was available to me in Cartegraph’s software the whole time. It is available to you, as well.
Using my existing Cartegraph data, I was able to determine staffing strategy, develop future personnel levels, and effectively manage the morale of our field staff. I tested, refined, and verified the accuracy of this labor efficiency model over the course of four years, so I believe it will assist you, too.
First, determine your fundamental presuppositions. This is how the model I am proposing can be custom-fit to your organization and is critical to determining accuracy.
To realistically adjust your labor efficiency baseline, you must first account for the time employees spend engaging in the everyday, routine activities unrelated to the work being completed. To do this, you’ll deduct the average time spent engaging in these activities from the total labor hours available for your sample size.
For example, my department’s fundamental presuppositions were the following:
- Vacation, sick time, and personal days: 7%
The average field staff member takes 2 weeks’ vacation, 5 sick days and 2 personal days per year.
- Daily prep time: 13%
At a minimum, one hour per day, per employee is spent gathering tools, hooking up equipment, completing paperwork, and otherwise preparing to do work.
- Daily break time: 5%
I factored in 30 minutes of break time per employee, per day.
When taken together, these presuppositions reduced my staff’s total available work hours by 25%. So, for the sake of accuracy and fairness, my labor efficiency calculations were performed with the baseline assumption that a work crew is realistically capable of dedicating 75% of its total allotted work hours to completing the tasks at hand.
How-to calculate labor efficiency.
This is the Cartegraph data you’ll need:
- Labor hours recorded for each field staff member.
- Number of available work days or hours per month.
- Fixed number of field staff.
This is the equation you’ll use:
L / (S x W x D) = F (x 100)
D = Number of work days for the month
S = Number of Field Staff
W = Work Hours per day
L = Labor Hours recorded
F = Available work hours (%)
And this is an example of how you’ll use it:
In May, the City of Carteville’s eight-member Public Works field crew worked 20 eight-hour days, for a total 782 hours worked. What was its labor efficiency rating?
Number of work days for the month (D) = 20
Number of Field Staff (S) = 8
Work Hours per day (W) = 8
Labor Hours recorded (L) = 782
Available work hours (F) = X
L / (S x W x D) = X (x 100) = F
782/ (8 x 8 x 20) = X
782/1280 = .61 (x 100) = F
F = 61%
For the month of May, the Carteville Public Works field crew operated at a 61% labor efficiency rating (out of the aforementioned 75%).
I found our staff to have the best morale when working at
55% - 62% capacity. In other words, my crew was happiest when it was busy, but not over-worked. I also found that working above 60% capacity for too long resulted in stress, feeling overwhelmed, and delaying routine maintenance tasks. Knowing this helped determine staffing strategy and I used these numbers to justify hiring new staff, manage morale, and project staff needs into the future.
All of the data you need is already there. All you need to do is mine that data to better understand how your staff works, their stress points, and how to determine staff levels into the future.
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