Quantifying Inefficiency: Comparing Comparisons Part II
In Part I of our blog series on “Quantifying Inefficiency: Comparing Comparisons,” we introduced the fundamentals of inefficiency and detailed the most reliable way of analyzing and quantifying the impact that work performed inefficiently can have on a construction project: the measured mile analysis. As discussed in Part I, the measured mile analysis compares the productivity in an unimpacted period of performance and an impacted period of performance of the same operation to quantify the contractor’s inefficiency using the simple formula below:
However, when an impacted project has no period of performance that can be classified as unimpacted or nearly unimpacted, then there is no reliable and easily identifiable “unimpacted” period of performance on that project to use as the baseline period of productivity. Thus, the version of the measured mile analysis described above that uses the “impacted” and “unimpacted” periods of performance from the same project cannot be used to accurately quantify the contractor’s inefficiency. This is because the formula in this scenario, by relying on the achieved productivity of the same operation on the same project, in most cases will underestimate the contractor’s lost productivity.
Consider the following example. Project A, originally planned to begin in late summer with site excavation work, has its notice-to-proceed (NTP) delayed by circumstances outside the Contractor’s control. The Contractor on Project A doesn’t actually receive its NTP until late December and must perform its site excavation work in frozen soil and poor weather conditions. To make up for the initial impacts experienced on Project A, the Contractor is forced to work extended periods of overtime and shift-work for the remainder of Project A. As discussed in our previous blogs, weather, changed soil conditions, and extended overtime/shift- work can all be sources of inefficient work.
During its best performance period on Project A, the Contractor excavated 20 cubic yards of soil per day, and during its most significantly impacted portion of work, the Contractor excavated 18 cubic yards of soil per day. Using the inefficiency formula above would identify that the Contractor only experienced a 10% reduction in efficiency on Project A, despite being impacted immediately upon beginning its work. This is obviously not a true indication of the Contractor’s inefficiency experienced on the project. So how can we more accurately quantify how inefficient the Contractor’s excavation operation really was?
In situations in which no true unimpacted or nearly unimpacted productivity existed, or can be identified, as in our above example, the most effective way is to identify an unimpacted production rate that was actually achieved on a similar project to use as the “unimpacted” basis of comparison. This actual achieved productivity of a similar operation on a similar project can then be compared to the impacted productivity achieved on the current project. It is important to note that there are at least two reasons that this alternate measured mile analysis approach is acceptable. First, this approach is applicable when an unimpacted period of productivity does not exist on the current project, and second, the alternate project’s production rate was actually achieved and is not a “theoretical” or anticipated productivity.
Although the analysis is performed similarly, comparing achieved productivities on two separate projects is not strictly a measured mile analysis in its purest sense. However, before the inefficiency calculation can be made, the analysis does require some initial groundwork to be laid due to the inherent introduction of variables from using the alternate project that could contribute to or be responsible for the difference in productivity between the different projects.
This initial groundwork requires the analyst to identify the reasons why the operation from the alternate project being used as the “unimpacted” period of performance is similar enough to the operation from the inefficient project so that it can be objectively viewed as a suitable baseline for comparison. Obviously, the more characteristics that the two projects have in common the more reliable the comparison will be. Characteristics to be compared between the projects include but are not limited to: location, weather, and soil conditions for where the work is being performed; who the general contractor, subcontractors, or project managers/superintendents were; the crew size and composition of those performing the work; what means and methods are being employed; equipment used; and the general scope, complexity, and cost of the work.
Perhaps what is less obvious in this comparison is that it is important to identify the areas in which the two projects are different. Where there are differences, the analyst should be able to detail why those differences are not responsible for the calculated inefficiency, and therefore, do not render the alternate project unreliable to use in this analysis.
Consider our example above. On Project A, the Contractor was unable to identify a period of performance in which its work was unimpacted. However, the Contractor recently performed a similar excavation, Project B, only one year prior. Project B was performed only 25 miles from Project A, performed by the same crew as Project A, and was run by the same superintendent. In fact, Project B was performed with the same equipment as Project A and this project was actually used by the Contractor in the development of its bid price for Project A. The only marked differences between Project A and Project B were that Project B was slightly larger and was performed in summer months. While the time of year was certainly a significant difference between the two projects, it is actually the key changed circumstance that the Contractor alleges was responsible for its reduction in productivity in Project A.
So, for example, when the Contractor reviewed the production rates that it actually achieved on Project B, it determined that it averaged 38 cubic yards of soil excavated per day. Thus, for the inefficiency calculation above, 38 cubic yards of soil per day is used as the unimpacted productivity. Using this amount, along with the average of what the Contractor actually achieved on Project A, 19 cubic yards of soil per day, the Contractor calculated that it experienced a 50% reduction in its productivity on Project A. This inefficiency percentage is a drastic change from the 10% reduction identified using the measured mile analysis that failed to identify a true unimpacted productivity in Project A.
While this analysis inherently introduces variables that may affect the inefficiency analysis, in situations where the analyst is unable to establish an unimpacted or nearly unimpacted productivity on the project in question, the calculation can provide reliable results when those variables are shown to have a minimal effect on the difference in productivity. However, if there are variables, other than the alleged cause of inefficiency in the subject project that were responsible for a reduced productivity, then the results of the calculation can be adjusted to account for the additional variables.
That does beg the question, however: what if there was wasn’t an unimpacted or nearly unimpacted productivity on a project and the contractor never performed a project with similar characteristics such that an actually achieved productivity can be can used for the comparison?
In our third and final blog in this series, we’ll tackle the last production rate comparison that can be used to address inefficiency.
If you have any interest or questions about this topic, please feel free to contact me at firstname.lastname@example.org.