Methods For Measuring Construction Inefficiency (Including the One You Should Use)
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Methods For Measuring Construction Inefficiency (Including the One You Should Use)

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In this Ideas & Insights, we’re going to discuss methods for measuring lost productivity or inefficiency. And we’re going to discuss five of those methods, in the following descending order of preference:

  1. Measured Mile
  2. Comparing Actual Productivity from the Subject Project to Different Project
  3. Comparing Actual Productivity to the Contractor’s Bid or Estimate
  4. Expert Opinion
  5. Published Inefficiency Factors

Measured Mile

The preferred method, as determined by courts and triers of fact, for measuring lost productivity or inefficiency is the measured mile. The measured mile method compares the achieved productivity of two periods of performance for the same operation on the same project. The two periods of performance are called the unimpacted (efficient) and impacted (inefficient) periods.

A comparison of the productivity in the unimpacted and impacted periods will result in the calculation of the inefficiency factor, which is the productivity of the unimpacted period minus the productivity in the impacted period divided by the productivity in the unimpacted period (U-I/U). This inefficiency factor represents the percent of lost productivity in the impacted period as compared to the unimpacted period.

The reason that this method is the preferred is because of its reliance on the actual or achieved productivity.

Why is the “actual or achieved productivity” feature of a measured mile method so important?

Well, it’s because the contractor’s achieved productivity removes variables or problems in the source data that could affect the accuracy of the analysis. For example, use of the actual or achieved production information of the same or similar work on the same project eliminates from consideration problems for which the contractor would be responsible such as errors in the bid, deficiencies in labor and management, equipment problems, etc.

Other less obvious variables are also eliminated by comparing achieved productivity of the same or similar operation on the same project like having the same crew composition and nearly the same project conditions.

By eliminating as many potential variables or problems from the calculation, the measured mile method is able to show that if the productivity achieved during the impacted work period is less and, if everything else is the same, we should be able to measure the difference in productivities and attribute that reduced productivity specifically to the change or alleged change.

I know this can sound complicated, but think of it this way. If you and I go down to the local high school and we each run a mile (four laps around the track), we’re likely to finish at different times. If we go back next week, but I have since broken my toe, how should I measure the difference in my performance? Doesn’t it make sense that I would compare my “broken toe” time with my time last week when I was healthy? Of course it does, but we also have to ensure that there aren’t other variables or factors that may also affect performance, like the weather conditions and track conditions.

The result of the measured mile analysis should be a percent difference in productivity achieved, or discrete productivity difference, that can be related back to the quantifiable amount of additional labor, hours, or equipment. What I’m saying is when you compare the achieved productivity from the unimpacted period to the achieved productivity from the impacted period, you calculate an inefficiency factor, as discussed above. You would apply that inefficiency factor to the labor and equipment hours expended during the impacted period to identify the additional labor and equipment hours attributable to the change or alleged change.

Again, we should only determine costs after the measured mile analysis is complete. And it’s only after we have determined the inefficiency factor and applied that rate to the labor and equipment hours in the impacted period, do we calculate the cost of the additional labor and equipment hours expended in the impacted period.

Comparing Actual Productivity From The Subject Project To A Different Project

Why would a contractor or analyst choose to use the achieved productivity on a different project as the basis upon which to measure the lost productivity on the subject project instead of using an unimpacted period on the subject project?

In most cases, the answer to this question is: “Well, there wasn’t an unimpacted period of operation on this project and, thus, the only example of an unimpacted period of productivity of a similar operation that we could find was from a different project.” That, in fact, may be true.

However, when analyzing a contractor’s allegation that its operation has experienced some loss of productivity that relies on the productivity achieved on a different project as the basis of comparison to demonstrate inefficiency on the subject project, the analyst should evaluate the entire operation that was allegedly inefficient on the subject project to satisfy himself or herself that there was, in fact, no “unimpacted period” available. In some cases, the analyst may elect to use an alleged unimpacted period from a different project in place of an unimpacted period on the subject project to produce a more favorable result.

If there was, in fact, no unimpacted period of the operation on the subject project, the contractor may have to rely on an unimpacted period from a different project to demonstrate a reduction in efficiency. When doing so, the analyst should perform the same calculation that is used for the measured mile method, but in this instance compare the productivity from the impacted period on the subject project to the unimpacted period on a different project.

Why is this approach less desirable than the measured mile method? Well, when comparing productivity, the further we distance ourselves from the subject project, which includes that project’s specific conditions, equipment, crews, etc., the chances that additional factors or variables could begin to affect the accuracy of the results of the inefficiency analysis also increase.

For example, the different project might have been in a different state, been completed under different conditions, using different crews, and maybe the work, though similar, is even slightly different. These variables, and others, can affect the productivity of the unimpacted operation to such an extent that it is not a reliable basis upon which to establish a comparison.

Let’s go back to the running example. Presume you and I go to the high school track and run the same mile. But this time, my identical twin brother joins us and runs it as well (yes, I have a twin brother). Unlike you and my brother, I come to the track with a broken toe. It’s reasonable to say that it makes more sense to measure the impact of that broken toe on my time against my brother’s time than against yours. Remember, we’re identical.

But even though we’re identical in just about every way, we are ultimately two different people. He may have had pasta for dinner the night before. I may have had a salad. I might wear running shoes. He might wear regular sneakers. These variables, although they seem minor, can have a real effect on the results.

Examples of Variables That Might Affect This Approach

Below is a list, not an all-inclusive list, of factors that themselves could affect the productivity of the operations on the different projects and, thus, skew the results of the inefficiency analysis by overstating or underestimating the lost productivity.

  • Did the actual conditions on both projects differ significant enough to affect productivity?
  • Were the differences in the skilled labor used on the projects significant enough to affect productivity?
  • Were the differences in the operations being compared significant enough to affect productivity?
  • Were the differences in the materials used, the market conditions, and demand for the materials used on both operations significant enough to affect productivity?
  • Were the differences in composition of the crews performing the work being compared significant enough to affect productivity?
  • Were the differences between the equipment used on the operations being compared significant enough to affect productivity?
  • Were there different general contractors, subcontractors, owners, inspectors, etc. on both projects that would affect productivity?

So, when the subject project doesn’t have an unimpacted period and the contractor or analyst is forced to look to another project, they have to be aware of these and other factors that must also demonstrate that the operations being compared were similar enough to not affect productivity. If the contractor or analyst are unable to do so, then some sort of allowance or accounting of the differences would have to be made.

Some people try to claim that comparing the productivity of similar operations on different projects is a measured mile approach. However, let me give you a real-world litigation example. In this example, an expert completed a “measured mile” analysis to determine the inefficiencies caused to the underground piping in a 10-story hospital with an additional basement floor. The underground piping installation was allegedly inefficient due to an owner change to the operation of the dewatering pumps.

The expert, who performed the analysis, contended that there was no unimpacted period for the project in question, so he used the productivity achieved on a nearby single-story nursing home as the basis for the unimpacted productivity rate. Using the nursing home productivity rate for the unimpacted period, and the hospital productivity rate for the impacted period, the expert measured a productivity loss of 25% to the hospital’s underground piping installation.

The expert said he performed the measured mile analysis. So we have to ask ourselves this question: Did he? No, he didn’t. A measured mile analysis is a comparison of an unimpacted operation to an impacted operation of same or similar work on the same project. His analysis was a comparison of similar projects, or alleged similar projects.

Was it a reasonable choice to use the unimpacted productivity from a single-story nursing home as the basis of measurement? I think regardless of what an analyst or an expert calls their analysis, you always have to dig deeper into the details and that’s what we’re going to do here.

So let’s look at some of the facts we discussed earlier. Let’s start with location. The nursing home was less than a quarter of a mile from the hospital, so the soil conditions were the same. The unions and other location-based factors had no effect. Let’s look at labor and materials; the market conditions and demand were the same. So there’s no effect there. We have the same general contractor, so there’s no effect there. In this instance, the crews were the same on both projects. We have to look at the schedules of work. The general sequence of installation was the same, which would make sense because it’s one of the first items of work coming out of the ground. We’re pretty quickly eliminating these potential factors or variables that could affect the results.

But these projects did have some distinctions. One example was the method of work. In this instance, the size of the piping in the nursing home was a smaller diameter. Then we look at the type of the project. Well, the projects here were completely different in size, shape, and scope. The subject project was an 11-story hospital with a basement, and the nursing home was a one-story facility. The underground systems for the hospital were significantly more complex than the nursing home.

But remember, the expert here wanted to use the nursing home, a one-story facility, as the basis of productivity.

What were the results? In this case, the panel of judges decided not to use the “measured mile” prepared by the contractor’s expert as the basis of measuring the inefficiency of the underground piping installation. The main reason that the judges rejected the contractor’s approach was the differences in the piping sizes and systems’ complexity between the hospital and the nursing home.

However, it’s important to note that the judges awarded the contractor a portion of the additional cost that resulted from the inefficient underground piping work. Why is that? Why would the judges do that? Here’s an excerpt from the ruling:

The subcontractor made little if any effort as we would ordinarily expect to cite us to contemporaneous project records in support of the testimony. Given the labor overrun that the subcontractor knew had begun very early in the project, we find it difficult to believe that the contemporaneous documentation contained in the record would not provide relevant evidence supporting both the fact that an impact on productivity occurred and the extent of that impact. Therefore, in this circumstance, we make the inference that the contemporaneous project records do not support the subcontractor’s position.

It takes no special expertise to conclude that a wet, muddy site will make the contractor inefficient. Again, we’re talking about underground piping. The contractor is entitled to additional cost resulting from the muddy site conditions. We find no other basis in the record in which we could better calculate the amount of the subcontractor’s productivity losses, the MCAA productivity factors are a reasonable starting point to estimate inefficiency losses. And, we apply a 5% inefficiency factor to the underground piping.

So what we have here is that the judges have said, “The expert’s presentation wasn’t based on facts. However, we can still step back here and look at what really happened. We believe that the wet and muddy site conditions clearly had an effect on the contractor’s efficiency. And because we can’t rely on the expert’s analysis, we want to start with the MCAA factors, or use the MCAA factors, as a starting point.”

What Does The judge’s Decision Tell Us?

  1. Contemporaneous documents are incredibly important to any inefficiency claim. At a minimum, record the daily quantities of work accomplished, labor and equipment hours expended, and be proactive with schedule management and communication. We need the contemporaneous documents to help tell the story. Good contemporaneous documents will record the amount of work completed, will record the resources expended, and will also tell us what really happened on the project.

  2. Establishing a direct cause and effect relationship between the alleged change and the effect on the contractor’s operation is essential. For example, even though the judges did not want to, or didn’t feel compelled to rely on the expert’s testimony and analysis, they still were able to determine that a change existed based on changed condition. They were able to somehow award some compensation to the contractor for that changed condition.

So if you prove entitlement, but do not correctly quantify inefficiency, a judge or jury may select another method to measure inefficiency, something we need to be mindful of.

Even though I can write about this topic for hours, I’ll stop there for now. We’ll talk about other methods for calculating inefficiency in the second part of this. And I’ll tell you why you should stay away from them.

Comparing Actual Productivity To The Contractor’s Bid Or Estimate

In some instances, when attempting to demonstrate its lost productivity, a contractor will compare the actual productivity that it achieved on the impacted operation to the anticipated productivity of that operation in its bid or estimate.

The biggest obstacle to using this approach is that the “unimpacted” productivity from the contractor’s bid is, at best, an estimate. It was not a rate of productivity that was actually achieved. Said another way, whereas the previous two methods (the “measured mile” method and the comparison to another project) use an unimpacted period that represents the contractor’s actual performance, this approach does not.

This is not to suggest that an acceptable inefficiency analysis cannot rely on the contractor’s anticipated rates of productivity from its bid. Rather, if a contractor or analyst elects to use an anticipated or estimated rate of productivity, then they must overcome the obstacle of demonstrating or establishing that the contractor’s anticipated productivity was, in fact, achievable.

Expert Opinion

This method consists of a construction expert reviewing the project documentation to provide an opinion that quantifies the lost productivity experienced by the contractor on the operation in question. The support for the expert’s opinion is based solely on his or her past construction experience and, typically, does not include an analysis.

The reason this method is not preferred is that it isn’t supported by a repeatable, statistically-based calculation or analysis and is based solely on the expert’s opinion. This is not to suggest that an opinion based solely on the expert’s experience is fundamentally flawed; however, it should be obvious that the expert’s experience and qualifications should match the subject project’s work scope and conditions as closely as possible to provide a convincing and acceptable opinion.

Published Inefficiency Factors

Contractors have sometimes relied on inefficiency factors published by contractor groups and other organizations within the construction community to quantify their lost productivity.

These publications usually identify factors, like trade stacking, worker morale, etc., that contractors would encounter on the projects that are believed to adversely affect an operation’s inefficiency. Typically, these factors are assigned a percentage that represents the reduction in productivity experienced by the operation if the factor exists.

As an example, a contractor may claim that it was forced to complete a particular work item when other trades were working in the same location at the same time, which it had not originally anticipated. As a result, the contractor’s operation progressed slower than expected and, thus, was less productive, meaning that the contractor expended more labor hours than anticipated to complete the work item. In order to quantify its lost productivity using published standards, the contractor would simply multiply the trade stacking percentage to the actual hours it expended to complete the work item.

The weaknesses of this approach should be apparent.

First, the inefficiency factor that’s used to quantify the alleged lost labor hours was not based on a calculation using production data from either the project or the contractor’s records. The evidence used to calculate the lost productivity is general in nature and may not apply to a particular project because of different project facts. It should be obvious that the farther the evidence that’s used to calculate the reduced productivity is from the project temporally, spatially, and factually, the less reliable it becomes to properly measure the operation’s inefficiency.

Second, the lost productivity factors listed in these publications are usually based on limited facts and analysis, which may call into question their reliability.

Third, these lost productivity factors should only apply to the specific trade or industry that prepared the publication. For example, it wouldn’t be advisable for a heavy highway contractor to use the Mechanical Contractors Association of America (MCAA) factors to quantify the lost productivity on an excavation operation.

Lastly, because the lost productivity factors are often prepared by a specific trade or industry expressly for use in forward-pricing change order work, their ability to objectively quantify lost productivity in a claim (after-the-fact) situation may be questionable.

This isn’t to suggest that published factors have no value. Rather, they should be used in the appropriate situations, which is when the above-mentioned methods aren’t available and the affected work is the same or closely matches the work described in the publication.

In summary, the calculation of lost productivity is an imperfect science because the availability and quality of the data used to calculate productivity and to prove inefficiency varies from project to project. However, using the production data from the subject project provides the best and most reliable result to both demonstrate and evaluate allegations of lost productivity.

Mark Nagata is a Director/Shareholder of TRAUNER and is an expert in the areas of critical path method scheduling, delay and inefficiency analysis, and construction claim preparation and evaluation. He loves to get questions at

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