Part 2: Benchmarking Performance Metrics - The Complete Guide To Workforce Optimization

In our last post, The Complete Guide To Workforce Optimization Part 1: Skills Catalog, we discussed the importance of creating an employee skills and work catalog (parts of the taxonomy). This enables software systems to help identify capacity-demand mismatches, or understaffing and overstaffing, in planning and scheduling applications. What wasn’t discussed is how to match the right quantity of capacity, in terms of person-hours or person-days, to fulfill a given amount of demand.

In services industries, accurate and granular benchmarking metrics enable bidders to set the right price so that the project is priced competitively but can still be profitable.

What is Meant by Performance Benchmarking?

Performance benchmarking is about quantifying the normal expected amount of manpower to satisfy a given type and unit of demand. For the purpose of planning and scheduling, we are not factoring in a work quality metric but assume that all workers have similar productivity for a given task. In other words, we are setting the expectation for how many desks, hospital beds or square feet of space can be cleaned per hour.

Who Needs to do Performance Benchmarking?

Performance benchmarking is usually needed in industries with workforces that perform regular and repeatable activities, such as cleaning and sanitation, security, catering and facility management.

Benchmarking is not usually required for organizations whose employees are performing complex or unpredictable reactive support and repair services, such as automotive or appliance repair or emergency medical technicians. In the case of technicians performing routine planned or preventive maintenance, service times for these activities are usually known. Contact center performance metrics are also fairly well-known by service providers.

Any organization that doesn’t feel they have task-level performance data may need to perform benchmarking before implementing an optimization system. This performance benchmark data will later be joined to the taxonomy discussed in the last article Part 6: Strategic Planning.

Download our Benchmarking Excel Template

What is the Right Level of Granularity & Measurement Unit?

Benchmarking can be done at different levels of granularity, from the single activity level (ex. cleaning windows) to the service type level (ex. interior cleaning). The level of granularity may require some thought. If the granularity level is too fine, then the data collection and integration effort will be higher. For instance, you may not need to detail out the time it takes for a senior housekeeper vs a junior housekeeper to clean a room.

Too coarse a granularity, on the other hand, will result in plans and schedules that are less optimal, meaning frequently overstaffed or understaffed. This could happen, for instance, if you don’t account for the extra time it takes to clean a multi-room suite.

The units of measurement can also vary by work type. Some examples are the time it takes hospital staff to perform various medical procedures may reside in a lookup chart of minutes per procedure. Cleaning staff may be benchmarked based on the number of square feet, hospital beds, rooms, or windows serviced in the case of window cleaning. It’s a good idea to involve front-line managers to determine which are the best metrics to use.

How to Derive Performance Metrics

There are different approaches to measuring performance. The traditional way is to observe the worker. The problem with this approach is that a worker may feel pressured to work at higher-than-usual efficiency, so the numbers may not scale well.

A good practice is to perform benchmarking passively through analytical approaches. This could involve looking at historical staffing levels alongside, say, patients served, hotel occupancy rates, commercial office square footage, or the number of desks cleaned. From there, performance averages can be derived based on the number of hours worked per person, per unit (ex by room, desk, or square feet).

Communication is key

Benchmarking employees can be a sensitive topic, especially for unionized workers. That’s why it’s critical that leadership effectively communicate why and how the information will be used.

Some industries, like warehousing, often use benchmarking to drive greater productivity through competitive peer pressure. This is probably not ideal, for a services outsourcing company that needs to balance costs with service levels.

Whatever the reason for doing benchmarking, you should make it clear to your employees why you’re doing it and how it benefits them and the company.

Download our Benchmarking Excel Template

Read all the articles of The Complete Guide to Workforce Optimization:
Introduction to our Series
Part 1 Cataloging Employee Skills and Work Activities
Part 3 Demand Planning
Part 4 Operational Scheduling
Part 5 Tactical Planning
Part 6 Strategic Planning

Frequently Asked Questions

Q: What role do benchmarked activity performance rates play when configuring a frontline workforce optimization model?

A: Benchmarked activity performance rates help organizations accurately translate service demand into workforce capacity requirements.

Performance benchmarks define the typical time required to complete specific activities based on real operational data. These benchmarks allow workforce optimization platforms to estimate staffing needs, shift structures, and workload distribution more accurately. By using historical execution data instead of generic assumptions, organizations can better align workforce capacity with actual operational demand, helping reduce both overstaffing and resource shortages.

Q: Why do static, un-benchmarked employee performance estimates fail in dynamic frontline scheduling environments?

A: Static performance estimates often fail because they ignore critical operational variables like technician skill differences, travel dependencies, and changing site constraints, which triggers scheduling volatility.

Traditional scheduling methods frequently rely on fixed assumptions for task duration, regardless of technician expertise, travel conditions, equipment differences, or site complexity. In dynamic frontline scheduling environments, variables such as technician expertise, travel conditions, equipment differences, and site complexity can significantly impact execution times and workforce productivity. Modern workforce optimization platforms use historical operational data to build more accurate performance baselines, enabling schedules to better reflect actual field conditions and reducing the need for constant manual schedule adjustments.

Q: How does a frontline workforce platform utilize performance intelligence to optimize multi-objective operational schedules?

A: Frontline workforce platforms use performance intelligence to balance operational efficiency, service quality, and workforce constraints within a single scheduling framework.

By leveraging historical execution data, performance intelligence, and operational performance metrics, optimization platforms can evaluate multi-objective operational schedules and scheduling trade-offs simultaneously. For example, the system may determine whether assigning a highly skilled technician to a complex task delivers better service outcomes despite increased travel time. This data-driven approach helps organizations improve resource allocation, maintain customer service targets, reduce unnecessary labor costs, and support more balanced workforce utilization.

Q: How do data-driven performance benchmarks translate directly into measurable business outcomes for mobile workforces?

A: Accurate performance benchmarks help organizations improve workforce utilization, reduce travel inefficiencies, and strengthen operational reliability.

When schedules are built using verified performance data, organizations can align technician assignments more closely with employee skills, expected execution times, and regional demand patterns. This leads to more efficient territory coverage, reduced idle time, and fewer scheduling disruptions. As a result, businesses can improve service consistency, lower operational costs, support employee work-life balance, and scale operations more effectively without proportionally increasing workforce size.

Q: What foundational data integrations are required to continuously update and maintain workforce performance benchmarks?

A: Maintaining accurate workforce performance benchmarks requires integrating workforce optimization platforms with operational and workforce management systems.

Continuous workforce optimization depends on access to real-time operational data. Integrating systems such as Human Resource Management Systems (HRMS), Field Service Management (FSM) platforms, and Customer Relationship Management (CRM) tools allows organizations to continuously capture task completion data, workforce availability, skill profiles, and operational constraints. This integrated data flow helps ensure that workforce planning models remain aligned with current operational realities and can adapt more effectively to changing business conditions.