The ABC’s of a VEU analysis

Technician staffing questions are on the rise as delayed vehicle replacement drives vehicle maintenance requirements upward.

Many fleet and maintenance managers feel they cannot keep up with the additional demand but struggle to quantify and justify how many technicians they need. The number of technicians required for a maintenance operation to operate effectively is primarily driven by the size, composition, and age of the fleet it serves.

Katherine Vigneau, CAFM, is director of fleet, Matrix Consulting Group, and Canadian director of MCG Consulting Solutions.

A process, originally used by the US federal government, known as vehicle equivalent unit (VEU) analysis, can be used not only to calculate an organization’s requirements, but also to benchmark against other fleets with varying fleet compositions. VEU analysis involves assigning a value to an asset class to equate the effort required to maintain dissimilar types of vehicles to a passenger car or sedan. The sedan is assigned a baseline VEU of 1.0 and all other vehicle classes are assigned values relative to that ranking.

What does a VEU of 1.0 mean? Industry averages show that it takes approximately 10 hours of preventative and unscheduled maintenance per year to keep a sedan on the road. The age of the fleet and several factors unique to each organization can influence the 10-hour benchmark and will
be discussed.

Assuming 1.0 VEUs equals 10 maintenance hours, all other types of vehicles can be allocated a VEU value based on their relationship
to a passenger car. For example, a half-ton pickup truck is assigned a VEU of 1.5. This means that a truck of this type, on average, requires about 1.5 times the annual maintenance hours of a passenger car, or approximately 15 hours per year.

From this understanding of VEUs, the methodology involves 11 steps.

Create a consolidated vehicle and equipment inventory.
For organizations with a fleet information management system (FIMS), this step is fairly straight forward. The data elements needed include the vehicle make and model, year, odometer reading and maintenance costs (lifetime and last 12 months). The inventory should contain any asset that a technician may be asked to repair, which could include hand tools and generators.

Assign like assets to specific equipment classifications.
Assets should be grouped into classifications that have similar age, utilization and maintenance requirements as each group will be assigned a VEU value for the group. The value is an average so it is understood that some units will require less maintenance and others more. Where like assets are used in vastly different ways (and engender very different maintenance demands) sub-classifications may be needed.

Calculate or assign a VEU value to each classification.
A VEU value is assigned to each vehicle classification. There are two ways to do this. Organizations with very good data may use actual maintenance data to calculate the relationship of a given vehicle class to a sedan. More commonly, industry benchmarks of VEUs per common classes of equipment are used.

Total the VEUs represented by the fleet.
Once all classes of equipment have a VEU value, they can be multiplied by the number of assets in that class. Following this, all classes can be added to get the total number of VEUs in the fleet.

Determine the number of maintenance hours per VEU.
I mentioned previously that the standard is that one VEU equates to 10 maintenance hours. However, experience shows that this number can vary. Factors such as vehicle age, parts support and operating environment can influence the number of maintenance hours required.

Multiply the maintenance hours by the VEU count for the total maintenance required.
Once the total VEU count and the maintenance hours per VEU are known, they can be multiplied to find the annual maintenance hours required to support the entire fleet.

Assess the productivity of the technicians in annual productive hours.
Now it is important to turn to technician productivity. The industry benchmark is that technicians should be 70 per cent productive. This allows for vacation, sick leave, breaks and training. The typical work year is 2,080 hours and 70 per cent of that is 1,456 productive hours per technician.

Divide the total maintenance required by the annual productive hours.
Dividing the total annual maintenance needed (from step six) by the annual productive hours (from step seven) will reveal how many technicians are needed.

Review current staffing for annual productive hours.
Similarly, the number of current staff can be assessed to determine how many full-time equivalent (FTE) technicians an organization has. Does the supervisor turn a wrench? What percentage of time? The actual FTE count on the ground can be multiplied by the 1,456 annual benchmark to understand what current staff are capable of.

Determine acceptable outsourcing percentage.
Before calculating whether the organization is short-handed or has surplus staff, the amount of outsourcing needs to be considered. Another industry benchmark is that fully functioning shops still outsource 10-15 per cent of work. This should be work that can’t be done efficiently in-house. The outsourced work should be removed from the annual maintenance hours required.

Calculate the shortage or surplus of technicians.
Finally, the adequacy of technician hours can be assessed by comparing the number required (from step 8) to the number available (from step 9).

Here’s an example. The example to the right (in the chart) represents a fleet of 602 assets. Using industry standard values, these 602 assets total 1,362 VEUs. Since the fleet does not have parts support and technicians must find and pick up their own parts, the maintenance hours per VEU is 11 hours/VEU. The fleet therefore requires a total of 14,982 maintenance hours each year. When that is divided by the industry standard of 1,456 hours per technician, the number of technicians required is 10.29 (without considering outsourcing).

This is by no means an objective analysis as the assigned VEU values, and assumptions on maintenance hours per VEU and technician productivity will all influence the outcome. The methodology is simple, but accurate data and individual experience will add value to the results and help to justify your staffing requirements.