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Measured mile analysis

Measured mile analysis

An 'artificial' opinion

The measured mile analysis is a technique used to identify and quantify productivity loss on construction projects. It involves measuring the productivity of a particular task or activity over a set distance, referred to as the "measured mile." This technique allows construction professionals to identify factors that are causing productivity loss and implement strategies to improve efficiency.

Author: David Brown, Diales Quantum Expert

One of the key benefits of the measured mile analysis is that it provides a clear and objective way to assess productivity. By measuring the same task or activity over a set distance, it is possible to eliminate variables that could affect the results. This allows construction professionals to focus on specific factors that are impacting productivity, such as equipment malfunctions, delays due to weather, or inefficient work processes.

To conduct a measured mile analysis, construction professionals typically select a task or activity that is representative of the work being performed on the project. This could be something as simple as excavating a certain amount of soil or installing a specific type of piping. The task is then performed over a set distance, with the productivity being measured at various points along the way. 

Once the data has been collected, it is analysed to identify areas where productivity is lagging. This may involve looking at factors such as the amount of time spent on the task, the amount of material used, or the number of workers involved. By identifying the root cause of the productivity loss, construction professionals can implement strategies to improve efficiency. There are a number of strategies that can be used to improve productivity on construction projects, including investing in new or more efficient equipment, improving work processes, and providing additional training to workers. By using the measured mile analysis, construction professionals can identify specific areas where these strategies are needed and implement them in a targeted and effective manner. Overall, the measured mile analysis is an effective tool for identifying and addressing productivity loss on construction projects. By providing a clear and objective way to assess productivity, it allows construction professionals to identify the root causes of inefficiency and implement strategies to improve efficiency and reduce costs.

The italicised narrative you have just read, was not written by me, but was produced by an AI chatbot created by San Francisco based OpenAI, in response to a request posed by me for it to “write me an article on the measured mile analysis of productivity loss in construction”.

It took about 3 seconds get a response.

The ‘artificial’ opinion is not bad, and offers a sensible sounding synopsis of the measured mile analysis, and certainly passes for media content, oven-ready for distribution on social media.

Impressed, I asked the bot “is a measured mile approach preferred over earned value in productivity loss analysis?”, certain that a thorny opinion query on a preferential analysis approach, that often may allude even the seasoned professional, would surely trip the bot up.

The response, verbatim was:

A measured mile approach is a method used to determine the productivity of a construction project by comparing the actual output to the estimated output over a specific time period, usually a week or a month. This approach is used to identify the factors that are contributing to any productivity losses on a project and to develop a plan to improve productivity.

Earned value management (EVM) is a project management technique used to measure progress and performance on a project. It involves measuring the value of the work that has been completed and comparing it to the planned value of the work that was expected to be completed at that point in the project.

Both the measured mile approach and EVM can be useful tools for analysing productivity losses on a construction project. The choice of which method to use may depend on the specific needs and goals of the project and the preferences of the project team.

Again, this bot took about 3 seconds to respond, and again, it was a pretty solid effort.

So, what does AI mean for construction professionals and, in particular, those of us who grind out a living in the construction dispute space? Are we about to be usurped by computers?!

My answer (unsurprisingly you might say!) is no. And it starts with looking behind the initial response. Whilst both bots provided pretty impressive summaries about productivity loss, they were just that – summaries. They didn’t look at the practicalities and difficulties inherent in demonstrating and measuring productivity loss, describing a process rather than understanding it.

Indeed, the second ‘article’ produced by the AI did not actually answer the question posed, namely, to indicate a preference for a given approach. In my experience, those of us who frequently provide such analysis will ordinarily have a preference, and that preference is often governed by things like the nature and quality of records available to conduct an analysis, as well as other external factors.

Further, in my experience, a claims consultant or expert witness will not require prompting to advocate the merits of a favoured approach in a given set of circumstances. It may be that to readily express a preference is a uniquely human trait that would evade AI software, and by extension, bring into question the usefulness of AI in expert opinion.

The responses generated by the bots indicate that the AI software cannot (yet) produce an article that indicates a practical comprehension of the subject; rather it provides an illusion of comprehension. The result is a narrative which might well be acceptable in less scientific publications, but which is insufficient to ‘pass muster’ under any greater scrutiny.

Conclusion, the bots may provide a reasonable introduction to any subject, but it is far from being able to actually produce an analysis. I think it’s safe to say that the bot is unlikely to put an expert witness out of work, now or ever.

This article was written for issue 25 of the Driver Trett Digest. To view the publication, please visit: www.driver-group.com/digest-issue-25



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