Estimating the Trees but Not Seeing the Forest

The following is from a recent assignment and many experiences in my estimating career.  The dollar amounts have been changed but the ratios have been maintained. While I am presenting a design-build scenario these events occur regardless of contract type.

The owner retained the services of a design-build team to prepare and develop the project budget, prepare preliminary design documents, and perform the pre-construction estimating.  If everything works out right, they will finalize the design parameters and build the facility on a fast track design build basis.  I became involved just prior to the third estimate milestone on the project.

The first budget estimate prepared by the design-build team was based on very minimal design information.  The design-build team provided an estimate that amounted to $30 million in project costs.  The owner approved the estimated cost so some additional design work could proceed and another project milestone could be met.  The owner did add some capacity (scope) to the project.

 At the next milestone for the design–build team, the estimate came in at $40 million for the project.  The owner had some slight “financial heartburn” but since they were carrying the Contingency Fund dollars, authorized them to proceed with further preliminary design services and another cost estimate milestone for the project.  Some added scope was included.

 The third estimate was submitted to the owner.  It was prepared on a detailed basis for each major section of the project.  Quantities were developed for every discipline using estimators and computer models of the design.  At this time, the design was still less than 20% complete according to the design group on the design-build team.   The estimated budget for this cost milestone came in at $120 million, three times what was estimated on the previous estimate and four times what was estimated initially on the project!

 How did the costs quadruple from the initial budget?  How did they triple from the second estimate?  Yes, there were some scope changes, but nowhere near this large.  I would suspect the earlier estimates may have used “incorrect” cost information for the components or perhaps the cost information was applied incorrectly.  I would suspect that the root cause is the estimating on the project focused on the trees (detail) and forgot about the forest (entire project budget).  Unfortunately, both of these errors occur all too often.

 Mistakes like these can occur due to a lack of estimating knowledge for conceptual estimates.  If parametric cost data is determined, it needs to be from similar projects or adjusted with common factors and, if all else fails some common sense.  Capacities, volumes, weights and other parametric data are used successfully by estimators on all types and sizes of projects.  – Throughout the world, every day!

 Perhaps the design-build team was focused and concerned about the number of yards of excavation and backfill, tons of steel in the structures, equipment counts, linear feet of pipe and conduit, the entire myriad of details required in determining the costs.  If this is the case, perhaps they omitted what I would term a “sanity check” on the total project cost to see how they compared to other similar projects.

 By doing a double check parametric estimate based upon the project parameters, they could have noticed a problem at the very first estimate on the project.  Whether it is a budget or a hard money bid, this sanity check has been used at virtually every level of estimating I have been associated with in my career.  For example, mechanical and electrical contractors check by comparing costs per fixture, devices and/or square foot of building area at bid time.

 Oh By the Way…  The initial cost estimates can go the other way by being far too high and kill an otherwise promising project.  Also parametric estimates can have the same problems.  This highlights the need to not only check your numbers with an alternate method but the importance of maintaining reliable cost data.

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