# Calculating Loss of Productivity Due to Overtime Using Published Charts – Fact or Fiction

By Regula Brunies, FPMI, CCC, CQS and Zey Emir, P.Eng, MBA Revay and Associates Limited



### INTRODUCTION **In simple terms, productivity is defined as the measure of output (the work produced in units) per unit of input (hours required or**  **cost incurred). Other frequently used productivity measurements include:** 
**$ revenues $ revenues hours earned**

**——————— ——————— ——————— hours worked $ actual cost hours worked**  **The most convincing method of measuring loss of productivity is undoubtedly the “measured mile” approach. It compares pro** **ductivity achieved during unimpacted periods or “normal peri ods” with the productivity achieved during periods affected by**  **the causes alleged. It is based on actual data and inherently accounts for contractor inefficiencies and/or estimating errors.** **The damages are calculated based on the difference in produc tivity rates.**  **Unfortunately this method is of no help if: 1. the required data for a detailed productivity analysis are not**  **available or are unreliable; 2. several causes contributed to the productivity loss, but only**  **one cause is compensable; 3. the productivity loss has to be included in a change order**  **quantification prior to the execution of the change (forward costing).**  **Short of “guesstimating” , the only alternate method for quantify** **ing a distinct productivity loss may be the use of published stud ies for the cause in question, but not without the greatest caution.**  **Contractors and their claims consultants often rely on studies which have very little to do with the specific situation under**  **scrutiny. In fact, they may have never examined the actual study and simply relied on a single chart reproduced in a book or by a**  **trade association.**

**This article examines the numerous studies available for loss of productivity due to overtime. The objective is to inform the user**  **of their often limited application and the pitfalls of erroneous application.** 



### LOSS OF PRODUCTIVITY DUE TO OVERTIME **Overtime in construction is usually defined as work performed over 40 hours per week, or in some instances, more than eight**  **hours in one day. The most cited factor affecting productivity during scheduled**  **overtime is physical and mental fatigue. Other factors which may contribute to a productivity loss include:** 
**• absenteeism, accidents; • reduced supervision effectiveness;** **• shortage of materials, consumables or tools due to accelerat ed pace; and**  **• tardy processing of engineering questions and requests for clarifications due to greater demand within a given period.**  **Whenever loss of productivity due to overtime is quantified, the surrounding circumstances must be clearly understood.** 



### Bureau of Labor Statistics **The oldest study on overtime, widely cited as a reliable source, dates back to the 1940s. This study by the Bureau of Labour Sta**  **tistics of the U.S. Army Department of Labor (BLS) is based on 78 individual cases covering 2,455 men and 1,060 women working in**  **a wide variety of manufacturing industries with the work being mostly highly repetitive, machine paced, performed indoors and** **requiring little decision making. Moreover, this work was per formed by incentive wage employees during wartime, on pro**  **longed overtime schedules. According to the BLS study, average productivity for 50-hour, 60-hour and 70-hour weeks were 92%,**  **82% and 78% respectively. Notwithstanding the fact that this study was limited to the manu** **facturing sector, the Mechanical Contractors Association of Amer ica (MCAA) relied on these BLS data when it issued its Bulletins**  **no. 18A and 20 in 1968, to assist contractors in the preparation of claims and change orders relative to loss of productivity due to**  **overtime. In 1994 the MCAA, in its M3 publication entitled “Change Orders, Overtime and Productivity”**  **, still included the same BLS information as a reliable source to prove overtime inef** **ficiency. Since the BLS data were gathered in a very specific envi ronment in the manufacturing sector, the BLS results and the**  **MCAA charts are of little use for quantifying loss of productivity in construction.** 



### Foster Wheeler
**L.V. O’Connor, Director of Construction of the Foster Wheeler Cor poration published a paper in 1969 entitled “Overcoming the**  **problems of Construction Scheduling on Large Central Station** 

# The Revay Report

Volume 20 Published by Construction Consultants Number 3 Revay and Associates and November 2001 Limited Claims Specialists**Boilers” . The paper describes Foster Wheeler’s research conduct**  **ed from 1963 to 1968. Figure 1 shows Foster Wheeler’s overtime inefficiency curves derived from its own data. The paper does not**  **disclose how and under what circumstances the data were obtained. Although not explicitly stated, it is presumed that the** **findings are based on the boilermaker trade. Average productivi ty for 5-10 hour days and 6-10 hour days were 87% and 73%**  **respectively. Figures 3a and 3b reflect the**  ratios of productive return to overtime hours **for long-term job schedules of overtime operations: the curves reflect the average and the range of expected perfor**  **mance. It is important to note that after several weeks of overtime, the reduced labour productivity reaches the point of no return. The**  **study also suggests that a 45-hour job schedule very quickly becomes nothing more than wage inflation. It is important to note**  **that the effect of reduced labour productivity reaches the point of no productive returns on overtime hours, earlier for a 50 hour**  **schedule than for a 60 hour schedule. However, the inflated cost per hour of productivity effect is greater for the 60 hour schedule.**  **The study contains the following warning: “The industrial firm’s data on productivity is based on Fixed Stan** **dards, and a performance of 1.0 may not be the same as a per formance of 1.0 referenced to some other standard of**  **comparison. As a result, a 30% reduction of productivity in one set of data could compare with a 15% reduction reflected in**  **another set of data due to these differences.” In 1973, the American Association of Cost Engineers (AACE) pub** **lished a report on the “Effects of Scheduled Overtime on Con struction Projects” where it relied on the BRT data. Similarly,** **“The Owner’s Guide to Overtime, Construction Costs and Pro ductivity”** **, published in 1979 by the Associated General Contrac tors, the American Subcontractors Association and the** 

Figure 2

**2** Figure 1



### Proctor & Gamble **The Business Roundtable (BRT) issued a task force report in 1980 entitled “Scheduled Overtime Effect on Construction Projects”** **which was an update of their 1974 report entitled “Effect of Sched uled Overtime on Construction Projects”**  **. The original data relied upon were actual project records derived from a series of short** **jobs over a 10-year period in the 1960s and originated from a sin gle project, namely the Proctor & Gamble Green Bay, Wisconsin**  **process plant. The output was recorded from physical count or measurement, the input was based on actual payroll hours. It is**  **reported that the work was carried out in a tranquil labour climate with excellent field management. The nature of the construction**  **activities and the trades involved are unknown. Figure 2 depicts the**  cumulative effect of overtime on productivity for 50- and 60-hour work weeks as per the BRT Study. **The measure of productivity is a comparison of actual work hours**  **expended for preplanned operations with a fixed standard base of calculated work hour requirements called a “bogey”**  **. The “bogey” standard is for a straight-time schedule. The data are not** **a comparison of actual straight time with actual overtime pro ductivity.** 

Figure 3b Figure 3a**Associated Specialty Contractors relied on the same BRT data. Finally, the 1994 MCAA publication includes the same BRT data**  **as proof of the relationship between overtime and the increasing ratio of inefficiency during consecutive overtime periods. Thus, all**  **three publications contain no original data and the limitations of the BRT Study are equally applicable.** 



### Construction Industry Institute **In 1988, the Construction Industry Institute (CII) published Source Document 43 on “The Effects of Scheduled Overtime and Shift**  **Schedule on Construction Craft Productivity.” This study contains original data collected between 1984 and 1988**  **from seven different U.S. heavy industrial projects at various stages of completion, including oil refineries, natural gas recovery**  **plants, a fossil power plant and a chemical processing unit. The focus of the data is on crew performance. Trades involved are pri**  **marily electricians, pipefitters and insulators. Two projects include data for concrete crews (labourers) and one project includes form** **work and rebar crews (carpenters and ironworkers). Only two pro jects include data on straight-time as well as on overtime**  **schedules. On the chemical processing unit all tradesmen worked on a rolling 4-10 hour day schedule (two days off); three crews**  **were shifted such that at least two crews were on site every day. Figures 4a to 4d depict the results for selected crews.** **Figures 5a and 5b show the curves produced for average nor malized productivity against time for various combinations of**  **overtime schedules. They were generated to illustrate overall results of the study.**  **Based on the inconsistent patterns, no defensible conclusions could be developed with respect to overtime inefficiency. Thus it**  **is not surprising that the study concludes with the following statements:**  **“1.Previous studies by BLS, the Business Roundtable and others are not consistent predictors of productivity loss during over**  **time schedules for construction projects in this study. 2. Even on the same project working an overtime schedule, pro**  **ductivity trends of individual crews are not consistent. 3. Productivity does not necessarily decrease with an overtime**  **schedule. 4. Absenteeism and accidents do not necessarily increase under**  **overtime conditions.” In 1994, the Construction Industry Institute (CII) issued Source** **Document 98 on “Effects of Scheduled Overtime on Labour Pro ductivity: A Quantitative Analysis”**  **, the most comprehensive report since the BRT report (1974; 1980). It is based on 151 weeks**  **of data collected from 1989 to 1992 from four active industrial construction projects (papermill, manufacturing, process plant,**  **refinery) without major contract disputes. Each was constructed in a tranquil environment and was well managed. The overtime**  **schedule was used to maintain the schedule, not to attract labour. The manufacturing and papermill projects were existing facilities**  **where old systems and equipment were removed and replaced with new ones. Congestion was a major concern. The refinery**  **involved the rebuilding of an existing facility. The process plant was a spacious, outdoor, grass-roots facility.**  **The focus of the study was on detailed observation of piping and electrical crews, rather than on various trades. The rationale that**  **only piping and electrical trades were studied is that these trades represented the majority of the work and were most likely to be** 

**3** Figure 4a Figure 4b

Figure 4c Figure 4d**affected by scheduled overtime. For electricians, the work involved the installation of conduit, cable and wire, terminations**  **and splices, and junction boxes. For piping, work included pipe erection and the installation of supports and valves. The perfor**  **mance of a crew on an overtime schedule was compared to the same crew on a straight-time schedule. There were not data for**  **5-8 hour days. Therefore a 4-10 hour day schedule was used as the baseline. Work weeks shorter than four days usually were**  **shortened because of weather. There was one 7-day work week which was discarded. Over 90% of the work days were 10-hour**  **days. The study specifically excluded the early phase of the work and the start-up phase.**  **Figure 6 shows the** overtime efficiency (3-4 week duration) as a function of the number of days worked per week. **It is obvious that 2- and 3-day work weeks were significantly less efficient than**  **the normal 4-day work week, probably because of the effects of adverse weather. The loss of efficiency for the 5- and 6-day work** **week was in the range of 10 to 15 percent with very little differ ence between the 5- and 6-day work week.**  **The remaining analyses contained in this study were an effort to support the initial determination that there are productivity loss**  **es when working overtime. Figures 7a and 7b show the** efficiency trends for 50-hour and 60-hour weeks as a function of time compared to the curves from the 1980 Business Roundtable Study. **All curves except the BRT curves were normalized about the first week of overtime for better visualization of trends. It is**  **evident that some crews follow the general downward trend established in the BRT Study, while others do not.** 

Figure 6

**4** Figure 5a

Figure 5b

**Figure 8 shows the** average overtime efficiency of all crews working a 50-hour work week, the BRT curve and other references.**The study concluded that the data are consistent with the BRT curve**  **and that the BRT curve is probably a good representation of the industry average but individual work may vary appreciably.** **Moreover, the study showed that it was possible to work over time for three to four weeks without losses of productivity which**  **would be consistent with the 1988 CII study. In the final conclusion, the study states:** 

**• “The use of short-term overtime** can **cause a loss of labour efficiency. The**  average **loss was in the** range of 15%. **When losses were analyzed as a function of time, the averages were**  **consistent with the Business Roundtable curve. However, overtime losses are** not automatic**but can range from**none to 25% **for crews (projects) where there are no other factors affecting productivity. Examples of factors that** can **cause loss es greater than 15% are incomplete design, numerous**  **changes, work in an operating environment or labour unrest. • As overtime efficiency decreases, the research found that**  **there was an increase in disruptions. The most consistent increase occurred in the category of resource availability. It is**  Figure 7b Figure 7a**concluded that this increased difficulty in providing resources is the root cause of losses of efficiency.**  **• The data collection and analysis methodologies are a sound, reliable way to measure the effects of scheduled overtime. The**  **basis for this conclusion is that the results of the analysis are consistent and in line with what would be reasonable.”**  **[emphasis added] Needless to say, the rather vague quantitative conclusions render** **their application to a loss of productivity calculation highly ques tionable. However, this study could be construed as a validation**  **of the BRT curves (in spite of the warning expressed in the BRT study) and the apparent contradiction of the CII 1988 conclusions.** 



### National Electrical Contractors Association **The National Electrical Contractors Association (NECA) published several studies on overtime.** **In a 1962 survey, 289 members replied to four questions con cerning overtime on a sporadic, short-duration basis and two** **questions concerning continuous overtime over several succes sive weeks. This is an extremely small sample considering that** **NECA has thousands of members. The responses yielded the fol lowing average values of productivity.**  **NECA concluded that the observations were close enough to give substantial confidence in the applicability of BLS values to elec**  **trical contracting which provided a more complete coverage. Notwithstanding NECA’s conclusion, it must be reiterated that on** **one hand the BLS data were collected under very specific condi tions in the manufacturing sector and on the other hand NECA**  **data were nothing more than a limited survey, i.e. subjective data which cannot be verified. At best, the coincidental similarity of**  **questionable data can be considered a general indicator. In 1969, NECA published “Overtime and Productivity in Electrical**  **Construction” , a study conducted by the NECA Southeastern** **Michigan Chapter. Data are from jobs worked during 1964, pre sumably for electricians. The origin of the data and the work envi**  **ronment are unknown. Figure 9 shows the** decline of productivity over periods of one to four successive weeks. **What happens beyond is, as indicated, a question mark. What is striking about**  **the four weeks of data is that weeks 2, 3 and 4 are multipliers of 1.5, 2.0 and 2.5 respectively of the first week data. This raises**  **some serious concerns with respect to the originality of the data.**

**The findings for the** number of work hours per day **and the** number of work days per week **are depicted in Figures 10a and 10b. They are consistent with expectations.** **In 1989, NECA published a second edition of “Overtime and Pro ductivity in Electrical Construction”** 

**. The study provides information on low, average and high pro**  **ductivity loss for 5-, 6- and 7-day work weeks and 9, 10 and 12 hours per day for sixteen successive work weeks, based on data**  **gathered by NECA since 1969 for journeymen electricians. The origin of the data and the work environment are unknown. Figure**  **11 summarizes** the data for average productivity for successive weeks of overtime.



### Miscellaneous Studies **In 1969 James Howerton published statistics on an overtime study conducted in 1964. The project, its location and the trades**  **involved are unknown. Figure 12 shows** productivity as a function of successive weeks of overtime. **SCHEDULED SCHEDULED PRODUCTIVITY DAYS HOURS EXTENDED WEEK** 

**6 8 98%**

**7 8 95%**

**SCHEDULED SCHEDULED PRODUCTIVITY DAYS HOURS EXTENDED WEEK** 

**6 10 84%**

**7 10 78%** FOR SPORADIC EXTENDED DAYS IN AN OTHERWISE NORMAL WEEK

FOR ISOLATED OR SPORADIC EXTENDED WEEKS

FOR CONTINUOUS OR PROTRACTED EXTENDED WEEKS **SCHEDULED SCHEDULED ACTUAL HRS PRODUCTIVITY DAYS HOURS EXTENDED DAY EXTENDED DAY** 

**5 8 9 100%**

**5 8 10 98%**

**5 8 11 95%**

**5 8 12 92%**

**5** Figure 8

Figure 9**In 1987 J.J. Adrian reported loss of productivity as part of an analysis of a contractor’s claim. The data originate from concrete**  **activities in Chicago in 1982. The work was performed under ideal weather conditions (60°-80°F). Figure 13 shows the**  productivity losses reported for successive weeks of overtime. **In 1991 Haneiko and Henry published statistics on the impact of overtime on concrete placement. The data were collected in 1986**  **on a backfit project in Texas. Overtime for concrete placement averaged 20 hours/week (60 hours/week) for an eight-week peri**  **od. Productivity during this period was 35% less compared with the eight-week straight time period (40 hours/week), namely 6.78** **hrs/cy vs. 5.01 hrs/cy. The only concrete work account that con tinued throughout the overtime period was the footings and**  **grade beams. Straight time productivity was 4.68 hrs/cy. Figure 14 shows**  productivity over eight weeks of overtime for the concrete placement of footings and grade beams.


### U.S. Army **In 1979, the Corps of Engineers published the “Modification Impact Evaluation Guide” for the purpose of evaluating impacts**  **due to changes. With respect to overtime, the guide recognizes: “Working more hours per day or more days per week introduces**  **premium pay rates and efficiency losses. Workers tend to pace themselves for longer shifts and more days per week...**  **When modifications make it necessary for the contractor to resort to overtime work, some of the labour costs produce no return**  **because of inefficiency... if overtime is necessary to accomplish modification work, the**  **government must recognize its liability for introducing efficiency losses...**  **... data are included merely as information on trends rather than firm rules which might apply to any project...** 

Figure 11 Figure 14

**6** Figure 10a Figure 12

Figure 10b Figure 13**... data do not extend beyond the fourth week, it is assumed that the curves would flatten to a constant efficiency level.”**  **Figure 15 depicts the curves published by the Corps on the** effect of the overtime work schedule on efficiency.**The origin of the data relied upon is unknown. However, it appears that the Corps**  **accepted the NECA (1969) average data for 6-9s, 6-10s, 6-12s, 7- 8s, 7-9s and 7-10s since they are identical, and added some of**  **their own lines.** 

### CONCLUSIONS **At the outset of this article it was clearly stated that published charts should only be used with the greatest caution and, more**  **importantly, only when no other practical method is available to calculate productivity losses from the actual project records.** **The inherent limitations of published charts have best been sum marized by the U.S. Army Corps of Engineers:**  **“... data are included merely as information on trends rather than firm rules which might apply to any project.”**  **Notwithstanding these limitations, appropriate application of published data for the purpose of forward costing of a change or** **accelerated schedule, i.e. before execution of the work, is consid ered advantageous to all parties involved. The owner will know**  **the cost prior to embarking on a change or accelerated schedule and the contractor will get paid for the cost of the agreed upon**  **productivity loss during the execution of the work. With this approach both parties share some risk but can avoid the costly**  **after-the-fact dispute resolution process. The use of published charts in an after-the-fact claim situation is**  **more problematic. Each of the studies containing original data applies to a very specific project environment for specific trades**  **only. It is, therefore, of the utmost importance to understand and document the surrounding circumstances of a claim situation. It** **is then up to the experienced analyst to compare the claim sce nario to the published study which resembles it most and intro**  **duce adjustments if deemed necessary. Published data can therefore be helpful in quantifying loss of productivity in over** **time situations but the result will always remain an approxima tion, although it may be the best one under certain**  **circumstances. For many types of projects no published data are available. Such** **projects include roadwork, pipelines, transmission lines or exten sive cut and fill operations, just to name a few. However, the**  **absence of such data is not surprising. On these types of projects contractors typically record actual quantities and hours of work,**  **allowing for a loss of productivity calculation based on actual data. Thus, an attempt to rely on undated published data on these** **types of projects will invariably be treated with suspicion. More over, these projects are often planned from the outset with**  **10-hour shifts and/or 6-day week schedules to take advantage of daylight or to attract labour to remote work sites. The latter aspect**  **is particularly relevant in cases where the labour force is housed in camps, thus eliminating daily commuting time to the work site.** **The fatigue resulting from a daily two-hour commute is consid ered similar to a daily increase of two working hours. Reliance on** **published charts on such type of project is therefore highly ques tionable.**  **In claim situations where the loss of productivity is a result of extended overtime and other parallel causes, none of the pub** **lished charts offer any help in calculating cumulative losses. Con versely, relying on published charts for the isolation of one**  **specific cause such as overtime may yield unreliable results. However, if there is no other practical way to calculate such loss,**  **the analyst may have no choice but to rely on a study which best fits the project situation under scrutiny, to calculate an approxi**  **mate loss.**



### REFERENCES **Adrian, J.J., (1987). “Construction Productivity Improvement.”**  **Elsevier Science Publishing, New York, NY, pp 96-98. American Association of Cost Engineers, Morgantown, WVA** **(1973). “Effect of Scheduled Overtime on Construction Pro jects.”**  **AACE Bulletin (October). Prepared by Construction**  **Users Anti-Inflation Roundtable, Roger M. Blough, Chairman.**

**7** 

### Synopsis **Based on the foregoing overview of available studies it is evident that only a few are based on original data. Moreover, less than**  **reliable data have been published and republished over and over giving a false appearance of originality. Finally, data are available**  **for a limited number of trades only. Figure 16 compares the reported efficiency from various studies for the 50-hour, 60-hour**  **and 70-hour work weeks with the majority based on 10-hour workdays and an overtime schedule of four consecutive weeks.**  **Subject to the qualifications already expressed, there is a certain consistency in that there is a definite, but not necessarily linear,**  **decrease in productivity for each additional 10 hours per week.** Figure 15

Figure 16**American Subcontractors Association, The Associated General Contractors Association of America and Associated Specialty**  **Contractors Inc. Washington D.C. (1979). “Owner’s Guide on**  **Overtime, Construction Costs and Productivity.” Bureau of Labor Statistics, U.S. Department of Labor. Washing**  **ton, D.C., (1947). “Hours of Work and Output.” by M. Kossoris, Bulletin 917.**  **Construction Industry Institute, Austin, TX, (1988). “The Effects of Scheduled Overtime and Shift Schedule on Construction Craft**  **Productivity.” Source Document 43.**  **Construction Industry Institute, Austin, TX, (1994). “The Effects of Scheduled Overtime on Labour Productivity: A Quantitative**  **Analysis”**

**. Source Document 98.**  **Prepared by H.R. Thomas and K.A. Rayner.** **Department of the Army, Office of the Chief of Engineers, Wash ington, D.C., (1979).**  **Modification Impact Evaluation Guide EP 415-1-3.**  **Haneiko, J.B. and Henry, W.C. (1991), “Impacts to Construction Productivity.”**  **Proceedings of the American Power Conference, Vol. 53-II, pp. 897-900.** **Howerton, J., (1969). “Do You Know the Hidden Costs of Over time?”**  **Qualified Contractor, (March).**  **Mechanical Contractors Association of America, Washington D.C., (1968). “How Much Does Overtime Really Cost?”**  **Bulletin 18A. Mechanical Contractors Association of American, Rockville, MD,**  **(1994). Change Orders, Overtime and Productivity.**  **Publication M3.**  **National Electrical Contractors Association, Washington, D.C., (1962).**  **Overtime Work Efficiency Survey. National Electrical Contractors Association, Bethesda, MD, (1969).**  **Overtime and Productivity in Construction. National Electrical Contractors Association, Bethesda, MD (1989)**  **Overtime and Productivity in Electrical Construction. 2nd edi**  **tion, Index no. 5050-2M-1999-JAN. O’Conner, L.V. (1969). “Overcoming the Problems of Construction**  **Scheduling on Large Central Station Boilers.” Proceedings of**  **the American Power Conference, Vol. 31, pp. 518-528.** **The Business Roundtable, New York, NY, (1974). “Effect of Sched uled Overtime on Construction Projects.”**  **Coming to Grips With Some Major Problems in the Construction Industry.**  **The Business Roundtable, New York, NY, (1980). Reprinted 1986 and 1989. “Scheduled Overtime Effect on Construction Pro**  **jects.” Construction Industry Cost Effectiveness Task Force**  **Report C-2. Thomas, H.R., (1992). “Effects of Scheduled Overtime on Labor**  **Productivity.” Journal of Construction Engineering and Man**  **agement, Vol. 118, No. 1, March.**



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### http://www.revay.com R. Brunies Z. Emir **Regula Brunies, Executive Vice-President and Zey Emir, Senior Consultant and Branch Manager are both working out of the Montreal Office of**  **Revay and Associates Limited.**