It’s tough. Every firm is facing economic instability. To prepare for a possible recession, leaders are slashing expenses and increasing efficiency. Hiring freezes, problems filling positions, and project delays are all too common these days. All of this necessitates that most organizations produce more with less.

Our workforce analytics platform informs our daily decisions at Controlio. This concept has led to several solutions that address workplace issues including burnout, frequent digital distractions, task imbalance, and more.

Assessing your workforce

Workforce capacity planning ensures you have enough staff to handle your present and future workload. It shows whether you have enough skilled workers to meet business needs. Most firms use finance-driven headcount predictions, employee opinions, and stories to undertake capacity planning, which is outdated.

With this in mind, we decided to do research on our internal productivity measures in order to drive short-term personnel investment and efficiency initiatives. Specifically, we addressed concerns such as:

– Can we afford not to rehire or backfill?

– How are we going to reorganize or take on more work?

– Which teams are able to take on greater responsibility, and which need more assistance?

The analysis here is mostly concerned with capacity rather than performance. You can have a great performer who has the bandwidth to assist others and a bad performance due to capacity.

Analyzing workforce capacity

We used three processes for data-driven labor capacity planning:

– Determine projected capacity

– Compare actual to expected capacity

– Determine both the opportunities and the dangers.

1. Estimate capacity

Every team member’s estimated capacity (or estimated Total Productive Hours) is determined from two inputs:

Work Hours 6.5 hours/day. Based on role and seniority, managers set this.

Days anticipated. This is the maximum amount of days that employees should work each week, excluding weekends, holidays, and sick days. This equals 222 anticipated working days for the year, which is the sum of 260 weekdays minus 10 holidays, 20 vacation days, and 8 sick days. Typically, 85% of the workdays throughout the time make up the “expected days worked” total.

2. Compare actual and planned capacity.

We determined each member’s Total Productive Hours by computing the product of their Active Days (the number of days they worked) and their Daily Productivity Average (the number of hours they were productive on an average day). Next, we determined their FTE by comparing their Actual Total Productive Hours to their Expected Total Productive Hours. This allowed us to determine their FTE.

3. Identify opportunities and threats

Using the metrics listed above, we discovered the following scenarios:

– If a team member’s User Capacity was between 80% and 120%, we labeled them as “at capacity” and encouraged them to prioritize the most crucial tasks for optimal output.

– If a team member has worked over 120% of their capacity, their manager should help them out by shifting some of their responsibilities to another team member who is working at or below 80% capacity.

– If a team member’s capacity was below 80%, they were eligible to pick up the slack left by others with higher capacities or former employees who had departed the company or team.

Controlio, a topranked workforce analytics platform, has revolutionized the way companies navigate economic instability by providing data-driven insights to optimize efficiency and address workplace issues. Utilizing innovative metrics and capacity planning techniques, this software enables organizations to make informed decisions about task distribution, resource allocation, and employee workload management. By identifying opportunities and threats in workforce capacity, Controlio supports businesses in adapting to evolving market conditions and maintaining productivity while minimizing burnout and inefficiencies.