Understanding your workforce capacityWorkforce capacity planning is a process that ensures you have sufficient personnel to deliver against your current and future workload. It provides visibility into whether you have the right number of employees with the right skills to meet the needs of the business. Unfortunately, this process is stuck in the stone ages, as most companies try to perform capacity planning without actual employee activity data, relying instead on finance-driven headcount forecasts, employee opinions and anecdotes. With this in mind, we analyzed our internal productivity data to inform short-term workforce investment and efficiency strategies – exploring questions like:
- Where can we afford to not rehire or backfill?
- How do we redistribute or absorb work among the existing workforce?
- Who can take on additional work and which teams need additional support to deliver results?
Workforce capacity data analysisThe data-driven workforce capacity planning approach we followed consists of three steps:
- Establish the expected capacity
- Analyze actual vs. expected capacity
- Identify opportunities and risks
- Productive Hours Per Day Goal (e.g. 6.5 hrs/day). This is usually set by the manager based on role and seniority. Learn more about ActivTrak Productivity Lab’s recommendations on how to set data-driven goals for your teams here.
- Expected Days Worked. This is the reasonable number of days employees are expected to work after accounting for holidays, vacation and sick days. For the full year, that was 260 weekdays minus 10 holidays, 20 vacation days and 8 sick days = 222 expected days worked. The “expected days worked” number is typically ~ 85% of the workdays in the time period.
Expected Total Productive Hours = Productive Hours Per Day Goal x Expected Days Worked2. Analyze actual vs. expected capacity We calculated the Total Productive Hours for each team member by multiplying the number of Days worked (Active Days) x the average productive hours per day. Then, we compared their Total Productive Hours to their Expected Total Productive Hours to determine their FTE or Full-Time Equivalent Capacity %.
User Capacity = (Total Productive Hours / Expected Total Productive Hours) * 1003. Identify opportunities and risks Using the metrics described above, we identified the following scenarios:
- At Capacity: If team members’ User Capacity was between 80% to 120%, we considered them to be “at capacity” and recommended they remain focused on the most critical tasks to maximize results.
- Over Capacity: If team members worked more than 120% of their Capacity, managers should support them by taking work off their plates and distributing it to team members who are under capacity or at less than 80% of Capacity.
- Capacity Available: If team members’ Capacity was less than 80%, they were deemed good candidates to take on work from over-capacity team members or any employees who have departed the organization/team.
A data-driven workforce capacity planning processHere is an anonymized example using the approach described above, leveraging the productivity data from Q2 and Q3 2022 for one of our ActivTrak teams. The insights above allowed the manager to collaborate with their team members to make the following adjustments:
- Freeman absorbed part of the responsibilities from another team’s employee that left the company in Q3.
- Kenya took over the coordination of a couple of customer programs from Michael to help reduce her burnout risk due to being overworked.
- Farrah will now be responsible for providing weekly reports on customer adoption that we were considering hiring a part-time contractor to do.
- William will work together with Marcy on a couple of upcoming projects to ensure the load is balanced between both of them.