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Human-hours worked per week in the United States, from 2006 to 2023

A man-hour or human-hour is the amount of work performed by the average worker in one hour.[1][2] It is used for estimation of the total amount of uninterrupted labor required to perform a task. For example, researching and writing a college paper might require eighty man-hours, while preparing a family banquet from scratch might require ten man-hours.

Man-hours exclude the breaks that people generally require from work, e.g. for rest, eating, and other bodily functions. They count only pure labor. Managers count the man-hours and add break time to estimate the amount of time a task will actually take to complete. Thus, while one college course's written paper might require twenty man-hours to carry out, it almost certainly will not get done in twenty consecutive hours. Its progress will be interrupted by work for other courses, meals, sleep, and other human necessities.

Real-world applications

[edit]

The advantage of the man-hour concept is that it can be used to estimate the impact of staff changes on the amount of time required for a task, which can done by dividing the number of man-hours by the number of workers available. For example, if a task takes 20 man-hours to complete then a team of 2 people will complete it in 10 hours of work, while a team of 5 people will complete it in 4 hours.

This is, of course, only appropriate to certain types of activities. It is of most use when considering 'piece-work', where the activity being managed consists of discrete activities having simple dependencies, and where other factors can be neglected. Therefore, adding another person to a packaging team will increase the output of that team in a predictable manner. In transport industry, this concept is superseded by passenger-mile and tonne-mile for better costing accuracy.

In reality, other factors intervene to complicate this model. If some elements of the task have a natural timespan, adding more staff will have a reduced effect: although having two chefs will double the speed of some elements of food preparation, they roast a chicken no faster than one chef. Some tasks also have a natural number of staff associated with them: the time to chop the vegetables will be halved with the addition of the second chef, but the time to carve the chicken will remain the same. Economies of scale and diseconomies of scale further lead to a non-linear relationship between the number of workers doing a given task and the amount of time it takes them to complete it. Some tasks cannot be done by less than a required minimum number of workers (e.g. lifting heavy loads) or they will be done with drastically better efficiency if the workforce exceeds a minimum efficient scale. In other cases an excessive number of workers might get in each other's way, reducing efficiency and the per person productivity of the individual worker.

Another example is the adage, "Just because a woman can make a baby in nine months, it does not follow that nine women can make a baby in one month." This adage is often cited in systems development to justify the belief that adding more staff to a project does not guarantee it will get done quicker.

Another problem with this model, as Fred Brooks noted, is that organization, training, and co-ordination activities could more than outweigh the potential benefits of adding extra staff to work on a task, especially if considered only over a shorter time period.

Similar units

[edit]

The similar concept of a man-day, man-week, man-month, or man-year[3][4] is used on large projects. It is the amount of work performed by an average worker during one day, week, month, or year, respectively. The number of hours worked by an individual during a year varies greatly according to cultural norms and economics. The average annual hours actually worked per person in employment as reported by OECD countries in 2007, for example, ranged from a minimum of 1,389 hours (in the Netherlands) to a maximum of 2,316 hours (in South Korea).[5]

Productive system hours

[edit]

The concept of productive system hours (PSH) has been used in forestry in Austria and by extension to other work. It includes time for breaks and can be used to calculate how long it may take to complete a task, including required recovery times from physically strenuous work, as well as legally required breaks or other human interactions. If it includes 15-minute breaks, it is written as (PSH15).

A related concept is productive machine hours (PMH).[6]

See also

[edit]

References

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Sources

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Man-hour

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A man-hour, also known as a person-hour or human-hour, is a representing the amount of work performed or capable of being performed by one average worker in one hour. This concept quantifies labor effort in a standardized way, allowing for the estimation of total work required for tasks without specifying the number of individuals involved. It is fundamentally a metric rather than a strict time measure, as it accounts for the output of continuous, uninterrupted work under typical conditions. The term "man-hour" first appeared in English usage in the early , emerging during early 20th-century industrialization. By the mid-, it had become a standard term in and industrial contexts to forecast resource needs. Its adoption reflected a shift toward quantifying labor as an interchangeable input, similar to material costs, to improve planning accuracy in complex endeavors. In contemporary , man-hours are essential for developing schedules, budgeting labor expenses, and tracking performance across industries like , , and . For instance, a project requiring 1,000 man-hours might be completed by one worker in 1,000 hours, ten workers in 100 hours each, or any equivalent combination, facilitating scalable planning. However, due to its gendered connotation implying male labor, the term is increasingly supplanted by gender-neutral alternatives like "person-hour" in professional guidelines and organizational policies to promote inclusivity. This evolution aligns with broader efforts in standards bodies to adopt equitable language while retaining the metric's practical utility.

Definition and Origins

Core Definition

A man-hour, also referred to as a person-hour, is defined as the amount of work accomplished by an worker in one hour of uninterrupted effort, serving as an idealized measure for purposes. This unit quantifies labor input rather than output, focusing on the effort expended by workers to complete tasks. As a non-SI unit commonly employed in and project contexts, it provides a standardized way to express the total labor required without adhering to the . For example, a task estimated at 100 man-hours equates to 100 hours of work performed by one or an equivalent of labor, such as five workers each contributing 20 hours. This highlights how man-hours aggregate effort across personnel, enabling scalable planning while assuming consistent from an worker. Unlike actual elapsed or time, which tracks the passage of hours including interruptions or non-productive periods, man-hours specifically measure dedicated labor effort to better reflect the resources invested in a . The underlying assumption of inherently simplifies variations in worker , , or working conditions to facilitate broad applicability in labor assessments. This unit originated in industrial settings to normalize labor comparisons across operations.

Historical Development

The concept of the man-hour emerged in the early as part of the broader movement toward , pioneered by through his time-motion studies in the 1910s. Taylor's work emphasized precise measurement of worker tasks to optimize efficiency, laying the groundwork for quantifying labor in discrete units rather than vague estimates. Although Taylor's 1911 publication did not explicitly use the term "man-hour," it advocated for "accurate, minute, motion and time study" to replace rule-of-thumb methods, directly influencing the development of standardized labor metrics in industry. By the 1910s and 1920s, the man-hour gained traction in manufacturing and as a practical unit for labor needs and allocating expenses. In industries like , organizations such as the United Typothetae of America adopted the "productive man-hour" in their 1911 Standard Cost-Finding System, using it as the basis for hand labor costs by tracking chargeable hours tied to specific orders via daily time reports and payroll records. This approach allowed for departmental cost calculations, distinguishing between direct production time and non-chargeable activities to improve efficiency and pricing accuracy. A key milestone came in 1921 when the (ASME) collaborated with the National Association of Cost Accountants (NACA) to establish a common lexicon for , incorporating labor units like the man-hour to standardize practices across manufacturers and facilitate decisions on production and investment. The man-hour's utility became evident in wartime production during the early to mid-20th century, particularly for standardizing labor forecasts in large-scale manufacturing. Detailed applications proliferated in , where U.S. shipyards used man-hour estimates to track productivity; for instance, construction initially required about 1.1 million man-hours per vessel in 1942, dropping to around 486,000 by 1944 through improvements like . This evolution extended into fields like and by the mid-20th century, where man-hours informed project planning amid growing complexity in postwar and defense projects. In the , U.S. practices further formalized the term, integrating it into operational planning for tasks such as facility and , as reflected in Corps of Engineers documentation on troop and equipment deployment during the war.

Measurement and Calculation

Basic Calculation Methods

The basic calculation of man-hours relies on a straightforward arithmetic that quantifies the total labor effort required for a task or . The standard is Total man-hours = Number of workers × Hours per worker × Productivity factor, where the productivity factor represents under ideal conditions and is assigned a value of 1 when no adjustments for losses or gains are needed. This approach assumes uniform worker capability and perfect task allocation, focusing solely on the aggregate hours of human labor input without considering external variables. To apply this , projects are first decomposed into discrete tasks through a structured . Begin by identifying and listing all component tasks, drawing from specifications or historical data. For each task, estimate the hours required for a single worker to complete it independently, often using standardized tables or past performance records. Multiply this solo estimate by the number of workers assigned if the task allows parallel execution, or the efforts for serial tasks, then sum the results across all tasks to yield the overall total man-hours. This step-by-step aggregation ensures a comprehensive tally of effort while maintaining simplicity in the computation. A key distinction in man-hour calculations arises between serial and parallel work configurations, which affects duration but not the total effort under ideal conditions. In serial work, tasks are performed sequentially by one worker at a time, so total man-hours equal the sum of individual task durations. For parallel work, where multiple workers contribute simultaneously to a divisible task, the total man-hours remain the effort equivalent of the solo duration, as each worker's hours are aggregated without multiplication by the full group size. For instance, a task requiring 10 hours for one worker solo totals 10 man-hours; if 10 workers perform it in parallel with perfect , each contributes 1 hour, yielding the same 10 man-hours overall, not 100. This principle underscores that man-hours measure cumulative labor input, independent of scheduling compression in ideal scenarios. Illustrative examples clarify these methods in practice. Consider building a that one worker completes in 5 hours under ideal conditions, equating to 5 man-hours total. If 10 workers collaborate in parallel on an equivalently scaled task—such as a larger divided among them—each might expend 5 hours, resulting in 50 man-hours total, reflecting the expanded scope while adhering to the formula. Such calculations provide a baseline for , emphasizing the additive nature of labor across workers and tasks.

Factors Influencing Estimates

Estimates of man-hours must account for variations in worker experience, as less skilled or workers typically require more time to complete tasks compared to experienced personnel due to longer learning and execution phases. This difference arises from the need for additional instruction, error correction, and slower task familiarization among novices, particularly in skilled trades like where precision is critical. Environmental conditions also significantly alter man-hour requirements; for instance, high temperatures can increase effective labor time through reduced work pace, mandatory breaks, and heat-related . Similarly, task influences estimates, with intricate operations demanding disproportionate additional hours owing to heightened coordination, , and problem-solving demands. Productivity curves, often modeled via learning effects, further refine estimates by recognizing that initial repetitions of a task consume more time, with subsequent iterations showing reductions—for example, the first unit might require 100 man-hours, while later units drop to around 80 due to accumulated proficiency. This principle, commonly applied at an 80% rate, quantifies how direct labor hours decrease predictably with volume, aiding in serial production or repetitive project phases. Non-labor elements such as downtime for breaks, setup, and minor interruptions are incorporated through efficiency ratios, which assume less than 100% productive time within a standard workday to reflect realistic on-site conditions. These ratios adjust ideal calculations by factoring in unavoidable pauses, ensuring estimates align with observed workflow inefficiencies in fields like and . To address uncertainties, contingency allowances are added as a buffer, generally 5-10% of the base man-hour total, to cover unforeseen delays or variations without compromising viability. This practice, rooted in standards, helps maintain schedule integrity by anticipating issues like minor design changes or supply disruptions.

Practical Applications

In Project Management and Estimating

In project management, man-hours serve as a fundamental measure of labor effort to allocate resources and predict timelines in tools like Gantt charts and the (CPM). Gantt charts visualize project schedules by representing activities as horizontal bars, where the length of each bar corresponds to the activity's duration, calculated as man-hours divided by the number of assigned resources (units). This allows project managers to identify overlaps, dependencies, and resource demands across the timeline, facilitating adjustments for efficiency. The (CPM) incorporates man-hours to determine the longest sequence of dependent activities that dictates the minimum project duration, using forward and backward passes to compute early and late start/finish dates. Man-hours inform loading on the critical path, enabling techniques like crashing—adding s to shorten durations—or resource leveling to resolve overallocations without extending the project end date. By quantifying effort in man-hours, CPM helps prioritize tasks with zero float, ensuring timely completion while optimizing crew deployment. Estimating man-hours employs bottom-up and top-down techniques to support accurate planning, particularly in bids where labor forecasts drive bids and resource needs. Bottom-up estimating decomposes the project into granular work packages via the (WBS), assigning man-hour estimates to each task based on historical data or expert judgment, then aggregating upward for totals; this method yields precise results for complex projects but demands detailed input. For instance, in a bid, estimators might sum man-hours for subtasks like site preparation (200 hours), foundation pouring (500 hours), and framing (800 hours) to reach a phase total. Top-down estimating, conversely, derives overall man-hours from high-level analogies or parametric models—such as scaling from similar past projects—offering quick approximations for initial phases when full details are unavailable, though with lower accuracy. Project management software integrates man-hours to automate schedule generation from effort estimates. treats man-hours as "work" values assigned to tasks, automatically computing durations via the equation Duration = Work / Units, where units reflect (e.g., 8 hours/day per worker), and generates Gantt views with critical path highlighting based on dependencies and calendars. Similarly, Primavera P6 uses "budgeted units" to represent man-hours, allowing assignment to activities with resource curves for non-linear distribution; the software then applies CPM scheduling options, such as fixed units/time duration types, to convert these into calendar-based timelines while accounting for availability and leveling. These tools enable dynamic updates, such as recalculating schedules when actual man-hours deviate from estimates. A representative case study is the Bridge project in , a cable-stayed structure opened in 2011, which required approximately 793,000 man-hours overall to inform crew sizing across phases. For the main span construction, involving cable installation and deck placement, man-hour totals guided the deployment of specialized crews—such as 50 workers for peak periods—to align with the 60-month schedule, preventing delays on the critical path while managing a of up to 1,000. Adjustments for factors like learning curves were applied briefly to refine estimates as repetitive tasks progressed.

In Cost Accounting and Labor Tracking

In , man-hours serve as a foundational unit for converting labor inputs into financial metrics, enabling precise allocation of in budgeting and reporting. The man-hour rate is typically calculated by adding overhead costs—such as benefits, , and administrative burdens—to the base per hour, providing a fully loaded labor figure. For instance, if the is $30 per hour and overhead adds $15 per hour, the rate becomes $45 per man-hour. Total labor costs are then derived by multiplying the total estimated or actual man-hours by this rate, yielding the overall for a given task or project. This approach ensures that are proportionally distributed based on labor effort, facilitating accurate and profitability analysis. Labor tracking in relies on time sheets and similar records to log actual man-hours against pre-established estimates, supporting variance analysis to identify discrepancies in or spending. Employees or supervisors hours spent on specific activities, which are aggregated and compared to budgeted man-hours; favorable variances occur when actual hours fall below estimates, indicating gains, while unfavorable ones prompt investigations into delays or inefficiencies. This process is integral to periodic financial audits and reviews, allowing organizations to refine future estimates and control costs through targeted interventions. Efficiency metrics derived from man-hours, such as labor , quantify output relative to labor input and are routinely used in cost audits to evaluate operational . Labor is computed as the of total output to man-hours expended, expressed as units produced per man-hour; for example, a line achieving 50 widgets per 100 man-hours yields a rate of 0.5 widgets per man-hour. This metric helps auditors assess whether labor costs align with value generated, informing decisions on pricing, , and process improvements. In , man-hours are tracked per unit of production to establish standard , which serve as benchmarks for ongoing control. For a product requiring an estimated 2 man-hours per unit at a $40 rate, the standard labor is $80 per unit; actual tracking via time studies or logs reveals deviations, such as 2.5 man-hours per unit signaling potential issues like gaps or . These deviations trigger variance investigations, enabling adjustments to standards and corrective actions to maintain .

Comparable Labor Units

Comparable labor units to the man-hour provide alternative scales for measuring human effort in project estimation and productivity analysis, often adjusting for daily or neutral terminology while maintaining proportional equivalences. The man-day, for instance, represents the work accomplished by one person in a standard eight-hour workday, equating directly to eight man-hours. This unit is particularly prevalent in and planning, where tasks are aggregated over full days to simplify scheduling and . In and broader contexts, the man-day facilitates estimates for extended efforts, such as sprints or milestones, by converting finer hourly breakdowns into daily totals for oversight. For example, productivity metrics like lines of delivered are often benchmarked per man-day, assuming the eight-hour equivalence to streamline reporting without losing precision in underlying calculations. The man-month extends this to longer periods, representing the work accomplished by one person in a standard working month, typically equivalent to 20-22 man-days or 160-176 man-hours, depending on the calendar and holidays. It is commonly used in and large-scale project planning for estimating overall effort over multi-week phases. Person-hour, also known as labor-hour, serves as a direct synonym for man-hour, emphasizing in modern usage with a one-to-one conversion . This terminology is recommended by professional bodies like the (PMI) for tracking effort in diverse teams, where output is assessed per person-hour of input to evaluate factors such as management impacts. The distinction between these units lies in their granularity: man-hours (or person-hours) suit fine-grained tasks requiring hourly precision, such as operations or detailed work, while man-days and man-months offer coarser overviews ideal for high-level timelines and team . This scaling avoids overcomplication in estimates, allowing conversions like dividing total man-hours by eight to derive man-days or by 160-176 for man-months in broader reporting.

System and Machine Productivity Units

In manufacturing and engineering contexts, the machine-hour serves as a key productivity unit representing the output or work capacity of a single machine operating continuously for one hour under standard conditions. This metric is particularly useful for allocating overhead costs and assessing in mechanized environments, where it parallels the man-hour by quantifying mechanical rather than effort. Unlike man-hours, which capture individual labor contributions, machine-hours emphasize utilization and are often derived from factors like machine uptime, speed, and maintenance schedules to determine lifetime average hourly costs. Machine-hours are frequently compared to man-hours to evaluate ratios, highlighting how mechanical systems can substitute for human labor to enhance . In automated processes, for example, machine-hours can replace multiple man-hours due to the precision and speed of automated systems, reducing labor requirements while increasing output per unit time. This substitution is calculated based on empirical data from production runs, where machine offsets manual variability, though actual ratios vary by and task . Productive system hours extend this framework by measuring the total effective output across integrated human-machine teams, often as a combined measure that accounts for both labor and equipment contributions in . This approach enables holistic tracking in hybrid setups, such as those involving operators overseeing automated lines, and is commonly applied to distribute overhead via bases like direct labor and machine hours. A related concept is (OEE), which integrates machine-hours with analysis to gauge system-wide , indirectly incorporating man-hours through labor-dependent factors like setup and checks. OEE is calculated as the product of (run time divided by planned production time, accounting for breakdowns and stoppages), (actual speed relative to ideal), and (good units produced versus total), providing a score that reveals losses in productive machine time. While primarily equipment-focused, OEE often intersects with man-hours in practice, as labor inefficiencies (e.g., during changeovers) contribute to , prompting optimizations that balance human and mechanical inputs. World-class OEE targets 85% for , emphasizing reduced idle time to maximize throughput. In assembly lines, these units are tracked in combination to optimize overall throughput, where monitoring machine-hours alongside man-hours allows managers to adjust workflows for balanced human-machine . For example, in automotive production, integrating OEE with system hours helps identify bottlenecks, such as when operator delays amplify equipment , leading to targeted interventions that boost without over-relying on either resource.

Criticisms and Alternatives

Gender and Inclusivity Concerns

The term "man-hour" originated in a historical context of predominantly male workforces but has been criticized since the for implying a male-centric labor model, excluding women from conceptualizations of work and productivity. Feminist linguists, such as Julia P. Stanley, identified "man-hour" as an example of generic masculine bias in English terminology, where "man" serves as a purportedly neutral prefix but reinforces patriarchal norms in professional discourse. This critique emerged amid broader second-wave feminist efforts to challenge sexist language patterns that marginalize women's contributions across fields like and . In the 1990s, U.S. government style guidelines began addressing such biases by recommending gender-neutral alternatives to terms like "man-hour" to foster inclusive communication in official documents. For instance, the U.S. Air Force's Tongue and Quill (1997) advocated replacing "man-hour" with "work hour" to avoid exclusionary implications. By the 2020s, corporate and organizational style guides had escalated these efforts, explicitly discouraging or banning "man-hour" in favor of neutral phrasing to align with diversity initiatives. The International Organization for Migration's 2020 House Style Manual, for example, specifies "person-hour" as the preferred term, reflecting a corporate shift toward eliminating gendered language in global operations. Similarly, the Food and Agriculture Organization's FAOSTYLE guide promotes "work-hour" or "hour of labour" to ensure inclusivity in technical reporting. The impact of "man-hour" extends to creating subtle biases in diverse workplaces, particularly in male-dominated sectors, where such can perpetuate feelings of exclusion among women and reinforce stereotypes about who performs technical labor. Studies in education and have documented how gendered terms contribute to broader linguistic barriers, correlating with lower female retention and participation rates in these fields. These biases align with post-1964 inclusivity drives, as the Equal Employment Opportunity Commission (EEOC) enforced anti-discrimination measures that indirectly spurred language reforms to combat workplace inequities. Usage of "man-hour" peaked in the mid-20th century, appearing frequently in U.S. (BLS) reports on , such as annual indexes of output per man-hour for the private economy from the to . Following the establishment of the EEOC under Title VII of the 1964 Civil Rights Act, which prohibited based on sex, the term's prevalence declined as federal and economic analyses shifted toward gender-neutral phrasing to support goals; by the late , BLS measures evolved to "output per hour" without the "man" qualifier. This transition reflected broader societal pressures for linguistic equity, reducing the term's dominance in official metrics by the and 1990s.

Modern Terminology and Replacements

In contemporary usage, the term "man-hour" has largely been supplanted by gender-neutral alternatives such as "person-hour," "labor-hour," or "work-hour," which maintain the same quantitative meaning of one hour of labor without implying specificity. These replacements emerged as part of broader efforts to eliminate biased language in technical and professional documentation, ensuring equivalence in measurement while aligning with inclusivity principles. Adoption of these neutral terms gained momentum in international standards organizations during the late 20th and early 21st centuries. The European Institute for Gender Equality recommends "staff hour" as a direct substitute for "man-hour" in policy and communication guidelines, reflecting a shift toward equitable in EU contexts since the . In the United States, professional bodies like the (PMI) use "person hours" in their materials for estimating and tracking labor in project contexts. U.S. technology companies have also transitioned to specialized neutral variants by the 2010s. For instance, Google documentation and engineering practices frequently reference "engineer-hours" when quantifying development effort, emphasizing role-based productivity over gendered assumptions. This approach appears in internal resources and publications like Software Engineering at Google, where it supports cost and time tracking without legacy biases. The primary benefits of these replacements include fostering workplace equity by reducing implicit gender stereotypes, which can otherwise deter diverse participation in fields like and . In , terms like "dev-hours" promote a more inclusive environment for estimating tasks, aligning with agile methodologies that value team diversity. In , "worker-hours" has been advocated by industry groups to address marginalization of women, enhancing recruitment and retention in a traditionally male-dominated sector. Linguistic trends indicate a marked decline in "man-hour" usage across professional literature from the onward, with neutral alternatives becoming predominant, as evidenced by corpus analyses like Google Ngram Viewer showing a sharp drop in frequency relative to "person hours." By the mid-2020s, broader studies on gendered language in confirm this shift, with inclusive terms comprising the majority in updated standards and academic outputs. As of 2024, companies like have adopted "person hour" in their inclusive language guidelines to further promote .

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  62. https://www.iso.org/cms/render/live/en/sites/isoorg/home.isoDocumentsDownload.do?t=QXZeoEEB9wWrMisiSbCnlIyD2NA8rvU9-SvtmEWQ5wiHk7G61DDns3myUn-r5beu
  63. https://eige.europa.eu/publications-resources/toolkits-guides/gender-sensitive-communication/practical-tools/phrases
  64. https://workplace.stackexchange.com/questions/86002/is-the-term-man-hours-appropriate-for-the-workplace-and-if-not-how-do-i-get
  65. https://techcrunch.com/2016/04/30/estimate-thrice-develop-once/
  66. http://jinwoongkim.net/images/software-engineering-at-google-lessons-learned-from-programming-over-time-1nbsped-1492082791-9781492082798_compress.pdf
  67. https://www.hrmorning.com/articles/the-power-of-inclusive-language-in-the-workplace/
  68. https://www.totaljobs.com/advice/the-importance-of-gender-neutral-language-in-the-workplace
  69. https://www.constructiondive.com/news/women-in-construction-push-for-more-inclusive-terminology/596612/
  70. https://english.stackexchange.com/questions/209318/man-hour-vs-person-hour-is-the-former-now-considered-politically-incorrect
  71. https://www.researchgate.net/publication/390642750_Gender-specific_and_gender-neutral_language_trends_in_the_AP_Stylebook_and_online_written_news_A_comparative_corpus_analysis_of_prescribed_vs_actual_usage
  72. https://github.com/IBM/IBMInclusiveITLanguage
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