As an example of facility benchmarking, a hypothetical company called ABC Architects is engaged by a town in the Massachusetts Route 495 area to renovate an elementary school. This design firm has past experience with educational facilities but has not maintained any record of construction unit costs or space allocation. The town’s school committee has asked ABC for an initial construction cost and space program, based on a student population of 550 students. Fortunately, the firm received a national summary of school construction activity from the American School Board Journal and was able to view construction unit costs, cost per student and space allocation per student for renovations and new construction.
Based on the limited regional information available, ABC decided to view elementary school construction at a national level to identify any regional tendencies. From the information[1] provided, ABC noted the relatively high variation between the average cost per square foot, as well as the minimum and maximum cost/sf. The high and low ranges for the three categories indicate the unit costs or space allocation that fit within 67% of all the project samples. Based on the information available, ABC could cautiously provide the school committee with unit cost ranges from $110 to $150 per square foot. The high variation in unit costs are a clear indicator that design firm should bracket their expected project costs and not provide a single unit cost to their client. A graph of the data was created by ABC and highlights the variation in unit cost based on a given student population:
As the projects approach 600 students, the construction unit costs become closer in range. ABC could further analyze the raw data by narrowing the samples to include only Northeast or Mid-Atlantic schools, and again determining the average, standard deviation and high/low ranges.
To complement the external data they received, ABC Architects could also furnish its own internally derived data to provide more samples that are within the region. The combined external and internal data would provide an excellent benchmark resource for ABC, which subsequently recommended that construction costs for the elementary school renovation could fall between $118 to $140/sf, based on the number of students proposed, with an allowance of 112 to 135 square feet per student.
The elementary school case study reflects the unique challenges that facility designers face when asked to furnish preliminary budget information. By contrast, real estate professionals are able to research a multitude of spaces, with current market data via CoStar or with brokers. For the construction industry, the number of projects in a specific region at any one time for a building type is more limited and may require a broader regional study to determine “the reference market”. Architects in particular have a tendency to want to view every aspect of every project prior to providing an informed opinion. Without the benefit of reviewing every project first-hand, architectural design firms often will not pursue benchmarking against the market. This often results in the perception that architectural design and engineering firms are unwilling, or worse yet, unreliable sources of market information.
Design and engineering firms can proactively determine the most useful metrics that serve their needs as well as their clients' for purposes of strategic planning, capital cost estimation, space allocation, HVAC equipment performance, circulation planning, etc. Once the data is obtained from external or internal sources, it can be sorted, analyzed, summarized and distributed to members within the firm and key client contacts for mutual benefit. If design and engineering firms provide clients with a range of probable construction costs along with other relevant metrics, they will become even more valuable assets to clients, particularly in times where project volume may drop.