Role of Workforce Management in Bridge Superstructure Labor Productivity

There have been many studies on different aspects of the construction process in regard to how they each impact construction productivity. In reviewing the documentation of this research, very few articles were located that dealt with heavy/highway construction in general, and even fewer were found that dealt with bridges in particular. In addition, very little was found in the literature dealing with the effect that the quality of workforce management has on construction productivity. This paper describes the results of four case studies of highway bridge construction performed by established contractors with little bridge building experience, in which workforce management had a significant negative effect on labor productivity. The contractors’ lack of experience in bridge construction seemed to be the cause of several problems that plagued each of the four projects. The baseline productivity of each project was calculated, and the loss of labor efficiency was estimated to be 80, 75, 32, and 70%, respectively. The schedule slippage on the four case study projects was estimated to be between 127 and 329%.     

Schedule Acceleration, Work Flow, and Labor Productivity

This paper details how construction labor efficiency is affected by deviations from the normal flow of work. A methodology is presented to estimate the loss of labor efficiency, based on variations in the percentage of labor hours used each week. The procedure can be used without the need for contractor production records. The theoretical basis for the method rests on the assumption that the rate of manpower utilization is consistent with the amount of work available for the contractor to perform. Using productivity data from three electrical projects that were accelerated, the labor efficiency is shown to be correlated to changes in the percentages of weekly work hours. Loss of efficiency curves are developed for various project phases. A case study is presented of an actual electrical construction project. Losses of efficiency are calculated for each phase, and it is shown that the contractor incurred an estimated loss of productivity of 25%. The analysis is validated by comparing a weekly inefficient work-hour profile to the chronology of events that occurred on the project.     

Measuring and Modeling Labor Productivity Using Historical Data

Labor productivity is a fundamental piece of information for estimating and scheduling a construction project. The current practice of labor productivity estimation relies primarily on either published productivity data or an individual’s experience. There is a lack of a systematic approach to measuring and estimating labor productivity. Although historical project data hold important predictive productivity information, the lack of a consistent productivity measurement system and the low quality of historical data may prevent a meaningful analysis of labor productivity. In response to these problems, this paper presents an approach to measuring productivity, collecting historical data, and developing productivity models using historical data. This methodology is applied to model steel drafting and fabrication productivities. First, a consistent labor productivity measurement system was defined for steel drafting and shop fabrication activities. Second, a data acquisition system was developed to collect labor productivity data from past and current projects. Finally, the collected productivity data were used to develop labor productivity models using such techniques as artificial neural network and discrete-event simulation. These productivity models were developed and validated using actual data collected from a steel fabrication company.     

Reducing Variability to Improve Performance as a Lean Construction Principle

Variability is common on construction projects and must be managed effectively. New management thinking, like that of lean production, has suggested that better labor and cost performance can be achieved by reducing output variability. Efforts to utilize lean thinking in construction, so far, have generated limited evidence to support this claim. This paper investigates the relationship between variability and project performance to test the notion that reducing output variability will result in improved labor performance. Using productivity data from concrete formwork activities on multiple projects, various measures of output variability are tested against construction performance. It is shown that variability in output is inevitable and that there is little correlation between output variability and project performance, but that variability in labor productivity is closely correlated to project performance. It is concluded that lean improvement initiatives should be redirected to adaptable workforce management capabilities to reduce variability in labor productivity instead of output in order to improve project performance.     

Statistical-Fuzzy Approach to Quantify Cumulative Impact of Change Orders

This paper presents a hybrid approach to quantify the impact of change orders on construction projects using statistical regression and fuzzy logic. There are many qualitative variables affecting the impact of change orders on labor productivity; statistical analysis falls short of addressing the fuzziness of those variables. Because of their complementary nature, fuzzy logic and regression analysis can be integrated; regression analysis is used to determine the membership functions of the input linguistic values. In this paper, each input variable is statistically treated before entering a general rule relating its space to the space of loss in labor productivity. The relative weight of each input variable is determined by its coefficient of determination (R2) value. The expected loss of labor productivity and its standard deviation are then determined from the output fuzzy membership function. The proposed methodology is general and can be applied in areas of system analysis and decision making when a complex input-output function is to be predicted in the presence of some fuzzy knowledge and a large number of real input-output data.     

U.S. Construction Labor Productivity Trends, 1970–1998

Construction productivity trends carry immense consequences for the economy as a whole. However, there is little scholarly consensus concerning even the direction of such trends. The main objectives of this paper are to (1) present an approach to studying long-term productivity trends in the U.S. construction industry; and (2) provide a preliminary indication of such trends over the past 25–30 years. Subsequent, extended statistical studies are suggested that may be based on the approach of the selected work presented here. Labor cost and output productivity trends are tracked for tasks that represent different trades and differing levels of technological intensity within the building construction sector. Specific tasks dealt with a range from a zero technology impact task, such as hand trenching, to compaction with a sheepsfoot roller. Means's cost manuals were used to trace the benchmark values for these tasks. These values reflect productivity trends. Unit labor costs in constant dollars and daily output factors were compared over decades for each task. Direct work rate data from 72 projects in Austin, Tex., over the last 25 years were also examined. Increasing the direct work rate usually increases construction productivity. The combined data indicate that productivity has increased in the 1980s and 1990s. Depressed real wages and technological advances appear to be the two biggest reasons for this increase. The data also indicate that management practices were not a leading contributor to construction productivity changes over time. Subsequent studies are required to add weight to these observations and can be based on the approach presented here.     

Impact of Change’s Timing on Labor Productivity

There are many types of construction changes and each type can have an effect on labor productivity. To a certain extent though the specific type of change is not as important as the mere presence of the change and, as analyzed in this paper, the timing of that change. The research reported in this paper reaffirms that project change is disruptive and detrimental to labor productivity. Data from 162 construction projects were statistically analyzed and a series of three curves are presented in this paper, representing the impact that change has on the labor productivity for early, normal, and late timing situations. The projects are a representative sample of the industry, involving a wide range of sizes, different delivery systems, and industry sectors. Late change is more disruptive of project productivity than early change, all other things being equal. The implications and benefits of this research are clear: if changes are necessary, they should be recognized and incorporated as early as possible. Practitioners can use these data and curves for either forward pricing or retrospective pricing of changes. Other researchers can use these findings to test their own findings and to explore timing issues in further detail.     

Impact of Overmanning on Mechanical and Sheet Metal Labor Productivity

This paper details the impacts of overmanning on labor productivity for labor-intensive trades, namely mechanical and sheet metal contractors. Overmanning, as used in the following research, is defined as an increase of the peak number of workers of the same trade over the actual average manpower used throughout the project. The paper begins by reviewing literature on the effects of overmanning on labor productivity. Via a survey to various contractors, data were collected from 54 mechanical and sheet metal projects located across the United States. Various statistical analysis techniques are then performed to determine quantitative relationship between overmanning and labor productivity. These techniques include the stepwise method, T-test, P-value tests, analysis of variance, and multiple regression analysis. The results indicate a 0–41% loss of productivity depending on the level of overmanning and the peak project manpower. Cross-validation is performed to validate the final model. Finally, a case study is provided to demonstrate the application of the model.     

Construction Baseline Productivity: Theory and Practice

In this paper, the theoretical basis for construction labor productivity measurement is presented. In particular, the theoretical basis for baseline productivity measurements is developed by examining a productivity database consisting of 23 projects involving masonry construction. An important hypothesis is presented showing that as the design becomes more complex, the baseline productivity worsens. It is also hypothesized that higher values of the coefficient of variation indicates a higher variability in management and craft skills and in the use of technology. Two measures are proposed to measure the performance of individual projects: The disruption index and the project management index. These two measures identify the best and worst performing projects. Cumulative probability distributions of the disruption index and the project management index were also developed to evaluate the 23-project database and compare it with other databases. The hypotheses developed from the 23-masonry project database were tested against an 8-project database of concrete formwork and a 12-project database of structural steel erection. Strong support for each hypothesis was found using the two additional databases.     

Relationship between Automation and Integration of Construction Information Systems and Labor Productivity

Information technology (IT) has been used to increase automation and integration of information systems on construction projects for over two decades. However, evidence that overall costs have been reduced or project performance has been improved with IT in construction is limited and mostly focused on application specific studies. A comprehensive understanding of the relationship between IT and project performance helps industry practitioners better understand the likely outcomes of implementation of IT application and likewise benefits researchers in improving the effectiveness in their IT development efforts. An opportunity to examine new evidence exists with the emergence of the Construction Industry Institute’s Benchmarking and Metrics database on construction productivity and practices. This article presents an analysis of that data to determine if there is a relationship between labor productivity and level of IT implementation and integration. Data from industrial construction projects are used to measure the relationships between the automation and integration of construction information systems with productivity. Using the independent sample t-test, the relationship was examined between jobsite productivity across four trades (concrete, structural steel, electrical, and piping) and the automation and integration of various work functions on the sampled projects. The results showed that construction labor productivity was positively related to the use of automation and integration on the sampled projects.     

Improved Measured Mile Analysis Technique

Quantifying lost labor productivity on construction projects is difficult and sometimes subjective. A widely accepted way to quantify losses is the “measured mile” approach. It compares periods of a project that have been impacted by change to those that have not been impacted. As currently practiced the measured mile relies on subjectively identifying that reference period. In this paper the measured mile and a variant, the baseline method, are analyzed and compared to a new, proposed statistical clustering method. This new approach is advocated because it determines its reference period using objective criteria. A case study is included to show how the three methods work, and advantages and disadvantages of each method are presented in this paper.     

Union and Open Shop Labor Cost Differences

One area within the construction industry that has dramatically changed is the growth of open shop construction. This growth suggests that open shop general contractors may have a competitive advantage over union general contractors. This paper investigates productivity and wage rate variances between Colorado open shop and union general contractors on projects completed since January 1981. Though there is little productivity variance, a significant variance of wage rates indicate the Colorado open shop general contractor presently has a clear overall labor advantage. The productivity and wage rate variance of 29 individual project job tasks were investigated. Data was collected from 35 union and 20 open shop contractors' project labor costs reports. Additional information was collected during interviews with representatives of eleven general contractors. The productivity and wage rate variances are described by individual job tasks; by the union craft jurisdictions of laborers, carpenters, ironworkers, and cement finishers; and by an overall comparison between open shop and union general contractors.     

Comparative Study of Activity-Based Construction Labor Productivity in the United States and China

This research compares construction labor productivity (CLP) of the United States with its Chinese counterpart at the activity level to evaluate productivity differences between the two countries from an operational perspective. Supplementing other comparative construction studies measuring productivity by output value per person, this research examined CLP—measured by physical quantity installed per labor hour—based upon published national average productivity data. Sampled activities included earthwork, concrete, masonry, structural steel, waterproofing, and interior finishes. Paired comparisons (United States–China) of these selected activities were then analyzed and evaluated. The source of the U.S. labor productivity data was RSMeans Building Construction Cost Data, which was cross validated by data from the Walker’s Building Estimator’s Reference Book. The source of Chinese labor productivity data was mainly the Beijing construction quota, which was cross validated by Chinese quotas from several other cities and provinces in China. In terms of hourly output, significant differences were observed in many operational categories. To test the hypothesis that the labor-equipment compositions of the Chinese construction crews contributed to the labor-productivity gaps, a labor intensive factor (LIF) was introduced to measure the intensity of labor usage in a construction activity. Statistical analysis indicated that modest to strong correlations exist between the productivity differences and LIFs of the sampled activities. Chinese CLP significantly lags behind its U.S. counterpart in equipment-intensive construction activities. Smaller CLP gaps or comparable CLPs between the two countries were observed for labor-intensive activities. According to these findings, construction equipment efficiency appears to be a major factor contributing to the productivity difference between the two countries.     

Role of Inventory Buffers in Construction Labor Performance

Buffers of material stockpile (inventory) are formed at the work level in construction to help manage production. The size of material stockpiles often has an important bearing on construction project performance. In construction projects, where conditions are often uncertain and variable, some have suggested that buffers be sized and located according to the conditions. New management thinking like lean construction and theory of constraints suggests that the size of buffers needs to be managed carefully, because when oversized, buffers are wasteful, impede workflow, and hinder performance. Research has shown that project variability can be affected with the careful deployment of buffers but has not really evaluated the impact on construction labor performance. This paper reports an exploratory analysis of the relationship between inventory (buffers) and construction labor performance with data collected from three commercial projects in Brazil. In this study, the size of the buffer between rebar fabrication and installation in the construction of a structural system is compared to the labor performance of the fabrication and installation crews. The results show that some buffer helps achieve the best labor performance in the construction operations studied.     

Increasing productivity in public works maintenance: The effects of job estimates based on engineered performance standards.

Data regarding the size of conventional labor hour estimates based on Engineered Performance Standards (EPS), and labor hours expended in completing jobs were collected from a carefully selected sample of Navy Public Works offices. An analysis of 266 work orders sampled from 12 Navy activities revealed that EPS estimates were significantly lower than conventional estimates but that the difference diminished with time from between 35% to 40% early in the EPS program (1958) to between 5% to 7% in 1963. This reduction was attributed to a learning effect which caused a lowering of conventional estimates as they were shown to be excessively high. Other analyses showed that estimated hours were consumed on the job regardless of how grossly they appeared to overestimate actual requirements, indicating that EPS utilization increased productivity by an amount roughly corresponding to the initial difference between EPS and conventional estimates. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Active management of prolonged pregnancy

OBJECTIVES: We assessed perinatal morbidity and mortality of prolonged pregnancies (> or = 294 days) compared with those of term gestations. We also evaluated the impact of induction of labor compared with spontaneous onset of labor. STUDY DESIGN: This observational study included consecutive cases treated at Chicago Lying-In Hospital from July 1980 to December 1984. Complications, presence of meconium, indications for cesarean section, mode of delivery, perinatal morbidity (and mortality), meconium aspiration, and duration of labor were compared with those in the total hospital population, in infants weighing > or = 2500 gm, and within prolonged gestation groups; spontaneous onset and induced ("active management") labors were also compared. The chi 2 analysis was used. RESULTS: Of 12,930 deliveries there were 707 prolonged gestations (5.5%) and 10,698 with infants > or = 2500 gm. Among the prolonged gestations 67% were in multiparous women and 33% in primiparous women. Labor started spontaneously in 62%, and 38% underwent induction; the overall cesarean section rate was 17% with similar indications in both spontaneous onset and induction groups. Meconium was present in 34%; it was present in 23% of inductions, which is fewer (p < 0.01) than among those with spontaneous onset of labor (40%). Also there were fewer depressed neonates at 5 minutes (p = 0.03) among inductions. Meconium aspiration was seen in 24, with nine deaths. The perinatal mortality was 14 per 1000 (corrected 12.7/1000), significantly more than in the general population. Among those with spontaneous onset of labor it was 20.5 per 1000; there were no deaths among inductions. Postpartum maternal morbidity was 16% among cesarean sections and 4% among vaginal deliveries. CONCLUSIONS: Prolonged gestation has a high perinatal morbidity and mortality rate. All perinatal deaths were observed among patients whose labor started spontaneously. "Active management" (induction at 42 weeks) did increase the primary cesarean section rate compared with that of the general obstetric population; it did not do so among prolonged gestations and prevented perinatal deaths in this group. From this experience an active approach seems justified.     

Impact of Change Orders on Labor Efficiency for Mechanical Construction

Change orders have become an everyday occurrence in construction. It is widely accepted by both owners and contractors that change orders have an effect on the labor efficiency, but these effects are difficult to quantify and frequently lead to disputes. Data from 61 mechanical construction projects were collected to develop a statistical model that estimates the actual amount of labor efficiency lost due to the change orders. The input variables needed in the model are as follows: (1) The original estimated labor hours; (2) impact classification; (3) total estimated change hours; (4) number of change orders; and (5) the timing of changes. The results of this study show that impacted projects have a larger decrease in labor efficiency than unimpacted projects. Additionally, the later a change order occurs in the life of a project the more impact it will have on the labor efficiency. The results appear to be consistent with the intuition of experienced professionals. Although each project has unique characteristics, the resultant model provides owners and contractors with a baseline measure of lost labor efficiency.     

Improving Labor Flow Reliability for Better Productivity as Lean Construction Principle

New management thinking, like that of lean production, has suggested that better labor and cost performance can be achieved by improving the reliability of flows. In this context, lean thinking portrays reliable flows as the timely availability of resources, i.e., materials, information, and equipment. Little attention has been given to labor as a flow. Further, little discussion can be found related to flexible capacity management strategies. Efforts to utilize lean thinking in construction, so far, have generated limited evidence to support the need for more reliable labor flows. This paper investigates the lean principle that more reliable flows lead to better labor performance. Actual data from three bridge construction projects are examined to document the instances of poor flow (resource) reliability and its effect on labor performance. Inefficient labor hours are calculated. The results show that there is strong support that more reliable material, information, and equipment availability contributes to better performance. However, the projects showed considerable deficiencies in the utilization of the labor resource. It is concluded that lean improvement initiatives should focus more on workforce management strategies to improve labor utilization that will lead to better labor performance.     

Work Sampling Can Predict Unit Rate Productivity

Various methods are employed to measure labor utilization during power plant construction, one of which is work sampling. Work sampling attempts to evaluate how the work force spends its time at work. This provides timely information to management in order to determine whether corrective action or detailed study is needed to achieve a higher degree of efficiency. However, the effectiveness of work sampling in demonstrating true labor performance has not been statistically verified using data collected at construction sites. This study collects 45 work sampling data points from 11 nuclear power projects and 4 fossil fuel power projects. the relationship between work sampling and productivity has been strongly supported by this statistical analysis. This study also verifies that work sampling is a good labor productivity indicator as well as a useful predictor in a productivity projection model.