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What Ever Happened To “Life-Cycle Cost Estimating?”

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What Ever Happened To “Life-Cycle Cost Estimating?”

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GTIM Nation is well aware that, in my self-appointed role of defense-against-management-fads guard dog, I have snarled at, barked at, and thrown up on several popular initiatives, mostly contra risk management (no initial caps), misapplication of Generally Accepted Accounting Principles, and those who would eschew Earned Value’s capability to produce an Estimate at Completion (EAC) in favor of using burn rates, or re-estimating remaining budget and adding that figure to the cumulative actual costs. Despite my reasonable opposition, unfortunately, these practices have yet to be roundly denounced or, better still, jettisoned from and ignored by the community of management scientists writ large. So, when a management fad does actually receive the left-behind treatment, I think it’s illustrative to go back and see what all the original fuss was all about, how the fad gained traction, and what ultimately led to its demise, particularly and especially if the fad was largely germane to the Project Management world. Such an example is the “Life-Cycle Cost Estimating” craze.

Just so everyone’s clear on what’s being evaluated here, according to,

A Life-Cycle Cost (LCC) is the total cost of a program from cradle to grave. (also referred to as Total Ownership Cost (TOC)) LCC consists of Research and Development (R&D) Costs, Investment Costs, Operating and Support Costs, and Disposal Costs over the entire life cycle. These costs include not only the direct costs of the acquisition program but also include indirect costs that would be logically attributed to the program. In this way, all costs that are logically attributed to the program are included, regardless of funding source or management control.[i]

My recollection is that Life-Cycle Estimating or Life-Cycle Cost first became a thing in the mid-1990s, and internet searches for papers on the topic show a sudden increase in titles published late in that decade. While perhaps noble in purpose, its stated goal of returning the “total cost of a program from cradle to grave”[ii] is impossible, as a couple of thought experiments will demonstrate.

Consider two (American) football stadiums: Soldier Field in Chicago, home of the Chicago Bears, and the Seattle Kingdome, home (for a time) to the Seattle Seahawks. I’ll contrast them so[iii]:



Soldier Field (Chicago)

Seattle Kingdome


October 9, 1924

March 27, 1976

Original Costs (2021 $s)



Seating Capacity:





January 9, 2000



March 26, 2000

Years in Service:

2021 will be its 97th



To further quantify the differences between these two projects facilities, consider the variance between them if each had had just one game, which sold out, per year, and that the ticket price was an inflation-adjusted $10 (USD), and that this was the sole source of revenue. What would have been the result?

Soldier Field:    $64,935,680

Seattle Kingdome: $15,180,000

…or, a delta of $49,755,680, which represents a whopping 62% advantage to Soldier Field, and even that figure gets larger each year Soldier Field stays open. I wonder what the respective Life-Cycle Estimators would have had to say at the project’s kickoff meeting had they been asked about each facility’s Return on Investment.

The second thought experiment that I would like to propose is based on the parameters needed to generate the “Life Cycle Costs.” From the definition in the first paragraph, these include:

  • Research and Development
  • Investment
  • Operating and Support
  • Disposal

Prior to project initiation, none of these improbably reduced number of parameters can possibly be known, or even estimated to any reasonable degree of precision (“…regardless of management control”? Puh-leeze). And yet, here’s the Life-Cycle Estimating crowd not only laying claim to an ability to perform such a capture, but actually asserting that such an “analysis” ought to be part of PM strategies going forward.

So, how did Life-Cycle Estimating become popular? I think it’s because of its implied (?) claims to be able to reasonably quantify far into the future, an ability that would automatically enrich any of its practitioners. With such a potentially beneficial capability, sprinkled with officious-sounding jargon, how could it not gain immediate and widespread recognition, if not complete acceptance, within the management science realm?

Did Life-Cycle Estimating end up going away, like other management fads? Sort of. There are still recent papers being published (not to be confused with a recent offering from my esteemed colleague Elizabeth Harrin, who blogged about the life-cycle of the estimate itself), but it seems to me that it doesn’t receive nearly the attention it did a decade or two ago. It may well be that it’s finally dawning on people outside of GTIM Nation that the future cannot be quantified. Not by risk managers, and not by estimators.

It’s why the term “precise estimate” is an oxymoron.




[i] Retrieved from on May 9, 2021, 18:38 MDT. This source cites the source of the quote as the Defense Acquisition Guidebook (DAG).

[ii] Ibid.

[iii] Wikipedia contributors. (2021, May 7). Kingdome. In Wikipedia, The Free Encyclopedia. Retrieved 01:57, May 10, 2021, from and Wikipedia contributors. (2021, May 9). Soldier Field. In Wikipedia, The Free Encyclopedia. Retrieved 01:58, May 10, 2021, from


Posted on: May 10, 2021 10:48 PM | Permalink

Comments (3)

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Question for the author: So, the only reason Soldier Field is more valuable than Seattle Kingdome is because Soldier Field is still operating? What if Soldier Field also shut down in 2000?

I believe that there are many, many reasons why, as a facility, Soldier Field is more valuable than the now-extinct Kingdome, with its effective service life being Exhibit A. The fact that the vast majority of these reasons were unknown, or even unknowable at the start of these facilities' relative start dates is the reason Life-Cycle estimating ought to be considered unreliable.

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