How to Benchmark Repair Costs

Use historical data to create trends that help estimate operating costs

Construction Equipment - April 1, 2004

Mike Vorster
Contributing Editor

As we saw last month, the estimate for lifetime repair cost greatly affects that machine's operating cost. In fact, repair parts and labor comprise between 15 and 25 percent of the total equipment budget. Equipment managers must be able to estimate, benchmark, track and manage this cost.

Four factors add greatly to the challenge of making sound estimates. First, repair costs are strongly influenced by conditions outside the direct control of the equipment manager. The work performed, the conditions under which the machine is working, and the skill of the operator can easily cause estimates to vary by 100 percent. Second, the internal management philosophy has a strong influence on costs. For example, focusing on repair before failure will certainly reduce the repair bill. Third, repair costs tend to occur in big amounts at relatively random points in time. They happen on irregular timelines and cost varying amounts. And fourth, repair costs vary with the age of the machine. They tend to be low in the beginning, but increase as machine life grows and warranties expire.

Manufacturer's literature provides some guidance on owning and operating costs. The information represents the best estimates, but the definitions and working environment can differ substantially from your unique situation. Two other disadvantages also exist: The data tends to be valid over the early years but lacking in the later years, and the values are frequently expressed as an estimate over total machine life so do not clearly show the rate at which repair costs grow with machine age.

Another approach is to use your knowledge of component life and replacement cost to build an estimated cost for each defined period in a machine's life. You would use a factor on the cost of individual components to allow for ongoing running repairs and arrive at a good estimate for the way in which repair costs are likely to vary with machine age. Partnering with the manufacturer will give results that can be used to estimate costs, fix replacement cycles, and benchmark current operations.

The best approach is to use data that you have collected and develop your own benchmarks, standards and norms. It is not a simple process and will require some time and effort. But your estimates will be consistent with your definition of cost and reflect the conditions under which you operate and manage your fleet. Here's a five-step process on how to use your data to estimate the lifetime repair costs for a group of machines.

Step 1. Define the group of machines. Identify a group of essentially similar machines by type, size or make. This group will define the benchmark for similar machines. Six or eight machines will suffice, but the more in the group, the more accurate the benchmarks. Our example is based on five dozers in a given horsepower range all purchased at about the same time and all used in similar applications.

Step 2. Collect data. Record hours worked and total lifetime repair costs at one or more points in the life of each machine in the group. Costs should include repairs done in-house as well as by third parties. Include only the repair-cost component of the total operating cost and omit items such as wear parts, tires or tracks, and preventive maintenance. Twenty to 30 pairs of data points will suffice; our example uses four pairs of data points for each machine spread fairly evenly throughout its life.

Step 3. Plot the data points. Use a large sheet of graph paper or a spreadsheet program. The horizontal axis should be total hours worked, and the vertical axis should be the lifetime repair costs. This will provide a relationship between hours worked and total lifetime repair costs.

Step 4. Draw a trend line. The data points will not lie along a smooth line because costs vary by machine. But it should be possible to draw a smooth line that is a "best fit" for the plotted data points. We know it goes through the zero, zero point and will curve gently upward to reflect the fact that repair costs increase with age. Draw it by hand on graph paper or use the spreadsheet program to do the work. Some points will be above the line and some below, because individual machines will cost more or less than the average values represented by the line. If the fit of the line appears good and the data are good, then the line will establish a good baseline for estimating lifetime repair costs.

Step 5. Use the line. The adjacent graph represents our example and can be used to estimate lifetime repair costs at 1,000-hour intervals. Select the period along the bottom of the chart, go up to meet the line, and go over to the vertical axis to read estimated cost. The lifetime repair cost at 8,000 hours is estimated to be $78,000 or $9.75 per hour. This is different from the lifetime repair cost at 5,000 hours, which totals $32,300 or $6.46 per hour.

Repair cost estimating and establishing benchmarks for repair costs is an important and critical part of equipment management. This five-step process will enable managers to use data to establish personal benchmarks and will provide good information to use in developing owning and operating cost estimates.

Collect the Data
Machine #	Hours worked	Repair costs
Our trendline plots four data points for each machine, spread evenly throughout each machine's life. This table shows one set of data.
101	1,586	$3,093
102	2,317	$5,305
103	2,416	$5,462
104	2,463	$9,562
105	3,100	$9,509