According to NASA, “the theory of learning is simple.”  This ‘simple’ theory of learning that is commonly referred to as “The Learning Curve” is as relevant to the construction industry as it was to the assembly of the Mars Lunar Rover. For builders this “simple” theory impacts costing, budgeting, forecasting, and scheduling. Hinze and Olbina (2009) add that the learning curve can help refine estimates, predict profits, and aid negotiations. Fortunately, adherence to a few ‘simple’ Rules of Productivity can help leaders and managers utilize this theory to reduce direct labor costs as workers learn to work in a more efficient and profitable manner.

T.P. Wright first introduced the concept of the learning curve to the aircraft industry when he published an article in the February, 1936 Journal of Aeronautical Science. Wright was among the first to recognize that repetition of the same operation or task resulted in less time or effort expended on that operation. For his learning curve, Wright asserts that “the man-hours necessary to complete a unit of production will decrease by a constant percentage each time the production quantity is doubled.”  Though originally offered to the aircraft industry, NASA observes that learning curves have subsequently been applied to all types of work from simple tasks to more complex jobs like building their space shuttles. To that end Abilla (2007) asserts that “it is easy to apply the concept of the learning curve to construction because output is a physical product that is easily measured.”  Indeed, any industry where repetitive tasks can be tracked by physical progress can gain easily quantifiable benefits from understanding how the learning curve functions – its benefits and limitations.

NASA’s cost estimating tool ( shows learning curve as a constant percentage every time a unit of effort or “production quantity” is doubled. For instance, when the rate of improvement is 20 percent between doubled quantities, the learning percent is 80 percent. NASA continues to present learning percentages for a variety of industries. Though construction is notably absent from the list, their estimates range from 85 percent for labor intensive tasks like aerospace and shipbuilding to a stingier 95 percent for repetitive machining operations. With this, NASA suggests that gains associated with repetitive tasks are greater when they are performed by hands-on labor as opposed to simpler shop or machining operations. This supports Abilla’s (2007) assertion that “the most obvious way learning is realized is with experience acquired by direct labor.”  Recent observation of labor-intensive construction/ building activities conducted in a field environment revealed a 77-80 percent learning curve. This represents a 20-23 percent increase in efficiency every time a unit of effort is doubled, and somewhat exceeds NASA’s estimate for learning while completing repetitive tasks. If these findings are applied to a sample task that initially takes 100 hours to complete, after 6 repetitions this ultimately results in a 36 percent increase in efficiency . However, Hinze and Olbina (2009) caution that “the [learning curve] predictions are approximation(s).”  In this data set it is noteworthy that the fourth repetition showed gradual improvement en route to the final predicted efficiency gain. Learning curve predictions must allow this type of flexibility.

While an understanding of learning theory is advantageous for anyone in the construction industry, it is similarly important to understand that the learning curve does not provide positive gains infinitely. To the contrary, if observed over a long enough timeline the learning curve demonstrates diminished, if not negative returns. Abilla (2007) points out that “typically, the increase is sharpest after the initial attempt and then gradually evens out.”  Dozzi and Abou (1993) continue that “the learning curve eventually reaches a plateau that reflects the minimum amount of time required for a task.”  As repetition increases, learning decreases and the time required to complete a task stabilizes. After this point of maximum efficiency is attained, the time required to complete a repetitious task can only increase.

Fortunately, adherence to some “simple” Rules of Productivity can help leaders and managers in a variety of industries utilize the learning curve to their advantage. Direct labor often accounts for the greatest cost on a job. Since learning curve theory states that labor intensive tasks gain the greatest reward from learning through repetition, this is where leaders and managers must focus their attention in order to attain maximum profitability. First and foremost, leaders and managers must get involved with Job Task Planning prior to construction. Design must precede construction. Contractors stand to gain huge increases in efficiency when they get involved earlier in the design process. Abou and Dozzi (1993) confidently state that “design improvements have the greatest impact” when measuring the effectiveness of direct-labor. To that end, Tony Guzzi (2012), President and CEO of the Emcor Group recently attributed strong revenue growth to EMCOR’s involvement “at an earlier stage in the contracting cycle.”  By getting involved with the design process builders can insert repetitive tasks into the design in order to increase their efficiency.

Workforce Management follows Job Task Planning once a job begins and progresses. Wideman (1994) points out that managers and leaders must ensure sufficient and continuous availability of work prior to commencement. After investing the effort to include repetitive tasks in the design phase, leaders and managers must ensure an uninterrupted workflow in order to reap the rewards of their efforts. Personnel assigned to repetitive tasks must also remain uninterrupted. Abou (1993) points out that it is “desirable to have the same person perform a task several times as opposed to making personnel changes along the way.”  It is therefore desirable to allow the same workers to complete repetitive tasks so that they can gain efficiency and profitability through repetition.

Another important Rule of Productivity that managers must pay special attention to both during the pre-construction planning process and during construction is Logistics. In seeing to proper Workforce Management, managers must not disrupt productivity through failed logistics. Instead, they must ensure sufficient and continuous availability of physical resources prior to beginning work and throughout the building process. Learning curve calculations aside, Abou and Dozzi (1993) estimate that this task alone represents a 6 percent gain in productivity when compared to the inherent inefficiency that results from the “starting and stopping” (i.e. mobilization) that occurs when ”an essential component of an activity is not available when it is required.”

Builders must also understand the Human Factors that contribute to productivity. Motivation and boredom are of the utmost importance when workers are performing repetitive tasks. Abilla (2007) states that people need to be motivated and interested in what they are doing. If workers lack motivation, they will perceive repetitive tasks as boring. Abilla (2007) continues that when boredom invades the workplace, “learning and performance will be compromised.”  It follows that when performance is compromised by monotony, quality and craftsmanship suffer as well. In speaking to motivation, best-selling business author Jim Collins (2001) suggests that if you can successfully implement these Rules of Productivity, then “you will not need to spend time and energy ‘motivating’ people.”  To the contrary, if workers have meaningful work and sufficient supplies then they will self-motivate! 

Failure to follow these Rules of Productivity could have costly consequences. Wideman (1994) reports that if delays occur between reps, the “unlearning curve” effect can be noted as the workers fall out of practice. In addition to setbacks on the learning curve, initial productivity when beginning (or resuming) a task is not 100 percent. There are extended losses that include (re) mobilization, material handling and distribution, and start-up.

Management has much, if not more control over efficiency than labor has. Hinze (2009) estimates that “85 percent of cost reduction is expected from management.”  Regardless of the trade or industry, leaders and managers must pay special attention to Job Task Planning, Workforce Management, Logistics, and Human Factors in order to fully benefit from learning associated with repetitive tasks. If these ‘simple’ Rules of Productivity are properly executed, Abilla (2007) reports that “the rate of improvement [will be] consistent and predictable.” In an industry where predictable and consistent improvement is the goal, leaders and managers must account for learning as a best practice.


Lee Feigenbaum is a LEED AP BD+C and a project director at P.J. Mechanical Corp. in New York. He can be reached at For reprints of this article, contact Renee Schuett at (248) 786-1661 or email