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1、February 2025Tough trade-offs:How time and career choices shape the gender pay gapNearly 80 percent of the US gender pay gap is driven by women having flatter work experience arcs compared with men,based on an analysis of 86,000 real-life online career histories.by Anu Madgavkar,Kweilin Ellingrud,Sv

2、en Smit,Chris Bradley,Olivia White,and Kanmani ChockalingamWhether sorting packages in the mailroom,coding in Python,or tending to patients,everyone starts their career somewhere.Yet in most industries,a first job is merely an entry point.What happens over the course of a career is crucial to buildi

3、ng an individuals human capital.Human capital is formally defined as the knowledge,skills,competencies,and attributes that individuals possess.1 Its accumulation begins in childhood and continues throughout educational stages and working life.The value of human capital is realized when people put it

4、 to workthat is,by gaining work experienceand pay is an important signal of that value.(Terms printed in italics are defined in the glossary.)Work experience,pay,and human capital itself are linked in complicated ways,and the threads are hard to unravel.One worker may enjoy pay hikes as she moves fr

5、om one role to another and acquires additional skills,a pattern of work experience that enhances both her human capital and the way it is valued through her pay.But another worker may see her human capital eroding over time as her skills go unused in a lower-paying role that doesnt require them.In t

6、his case,both human capital and its value diminish.Meanwhile,two workers who started out possessing similar skills may go on to earn differing levels of pay when they switch into roles with varying organizational and industry characteristics,indicating that the same human capital is valued different

7、ly in the two jobs.Overall,however,work experience is vital to both individuals and economies.For individuals,work experience underpins nearly half of lifetime earnings.For economies,work experience reflects how effectively human capital is matched with employers needs to raise productivity.In this

8、context,comparing the work experience trajectories of men and women assumes its importance.At a glance Diverging work experience patterns drive a“work-experience pay gap”that makes up nearly 80 percent of the total gender pay gap,equal to 27 cents on the dollar among US professional workers.Women te

9、nd to build less human capital through work experience than men who start in the same occupations,as seen in the tens of thousands of career trajectories we analyze.Over a 30-year career,the gender pay gap averages out to approximately half a million dollars in lost earnings per woman.One-third of t

10、hat work-experience pay gap is because women accumulate less time on the job than men.Women average 8.6 years at work for every ten years clocked by men because,on aggregate,they work fewer hours,take longer breaks between jobs,and occupy more part-time roles than men.The other two-thirds arise from

11、 different career pathways that men and women pursue over time.Womens careers are as dynamic as mens:Both men and women averaged 2.6 role moves per decade of work and traversed comparable skill distances in each new role.However,women are more likely than men to switch to lower-paying occupations,ty

12、pically ones involving less competitive pressures and fewer full-time requirements.As women switch jobs,they are less likely to move into occupations projected to grow in demand,instead often moving into shrinking occupations.Should current occupational pathways persist,by 2030,more than three-quart

13、ers of working men would be in occupations projected to grow relative to today,compared with less than two-thirds of women.The overall gender pay gap could remain at current levels.Some employers enable greater movement into growing occupations for all workers while reducing the gender pay gap,even

14、adjusting for the industry mix.These“People+Performance Winners”excel in both financial performance and building human capital.They stand out for rotating people internally,focusing on coaching,and fostering a culture that challenges employees while empowering them.2Tough trade-offs:How time and car

15、eer choices shape the gender pay gapWomen have narrowed and even reversed the gender gap in education in the United States.2 Yet only 58.7 percent of women participate in the labor force,compared with 70.2 percent of men.3 And what women and men do at work diverges significantly over time.Our resear

16、ch finds that that divergence,over a decade or more of work,drives almost 80 percent of the gender pay gap of 27 cents on the dollarwhat we call the“work-experience pay gap.”(See Box 1,“Definitions of the gender pay gap vary.”)To arrive at this conclusion,we analyzed how men and women go about accum

17、ulating work experienceswitching jobs,returning after breaks,climbing the corporate ladder,making lateral moves,downshifting,and moreand how they realize the value of human capital differently(in terms of pay).4 This privileged,close-up view is possible because we use a data set of some 86,000 de-id

18、entified online career histories of real people in the American workforce.Our data set is overweighted with white-collar,higher-paying jobs because people with public-facing,online work histories are more likely than the general population to hold themand they are of particular interest to talent-sc

19、outing employers.This research focuses on the extent,nature,and impact of divergence in work experience patterns and its effect on the pay gap between men and women.While gender pay gaps have been well studied by other researchers,we add to the discourse by dissecting the dynamics of work experience

20、 gained over time(Exhibit 1).We emphasize that we do not directly investigate the reasons that they diverge.Women and men may intentionally choose to pursue different paths for a variety of reasons relating to opportunity and personal agency,with complex underlying factors that are difficult to unta

21、ngle.For instance,personal preferences might lead women and men to opt for different kinds of work,or they may assign meaning to their work in different ways.At the same time,not all doors may remain open to all workers at every stage of life.As other research has explored,women may bear more The ge

22、nder pay gap can be measured in myriad ways,varying by the metrics used or the groups compared.The most commonly cited statistic for the gender pay gap in the United States indicates that women earn 84 cents for every dollar men earn.1 However,this figure considers only full-time workers and measure

23、s only annual median wages.When including part-time and seasonal workers and measuring either annual median wages or hourly wages,larger gaps,ranging from 17 to 22 percent,are generally observed.2 The gender pay gap can vary by age cohort,and some studies find that older women 1 “Equal pay day:March

24、 12,2024,”US Census Bureau,March 2024.2 See,for example,Francine D.Blau and Lawrence M.Kahn,“The gender wage gap:Extent,trends,and explanations,”Journal of Economic Literature,American Economic Association,volume 55,number 3,September 2017;Andrew Chamberlain,Progress on the gender pay gap:2019,Glass

25、door,March 2019;Wendy Chun-Hoon,5 fast facts:The gender wage gap,US Department of Labor,March 2023;Rakesh Kochhar,The enduring grip of the gender pay gap,Pew Research Center,March 2023;Elise Gould,Jessica Schieder,and Kathleen Geier,What is the gender pay gap and is it real?,Economic Policy Institut

26、e,October 2016;and Deborah Rho,“What causes the wage gap?,”Gender Policy Report,February 2021.3 Erin George and Gretchen Livingston,“Older and wiser,but not richer:The gender pay gap for older workers,”US Department of Labor Blog,July 1,2024.4 “Characteristics of the group quarters population by gro

27、up quarters type,”US Census Bureau Table S2602,accessed January 16,2025.5 “Civilian labor force by age,sex,race,and ethnicity,2003,2013,2023,and projected 2033,”US Bureau of Labor Statistics Table 3.1,August 2024.tend to experience larger pay gaps than younger women.3In our analysis of the gender pa

28、y gap,we take a more comprehensive approach than most studies by including workers of all ages,both part time and full time,as well as those in seasonal and nonseasonal jobs across the United States.Instead of focusing on hourly wages or median annual wages,we examine mean annual wages.We estimate t

29、he pay gap to be 27percent,observed in year ten of an average career in our data set(see Box 2,“Our data,scope,and methodology”for details of our data,which skew toward higher-skill professionals).Interestingly,mean earnings data for the entire US workforce reveal a similar pay gap.4 Our chosen appr

30、oach allows us to isolate the effects of various drivers over time to determine how they contribute to the pay gap,which we explore in this article.It is important to note that the 27 percent gender pay gap applies only to people in the workforce,and women currently constitute 47 percent of that tot

31、al.5 If we accounted for women who were not working,proportionate to their share of the working-age population,the income gap observed would be even larger.Box 1Definitions of the gender pay gap vary3Tough trade-offs:How time and career choices shape the gender pay gapExhibit 1McKinsey&CompanySource

32、:McKinsey Global Institute analysisIllustrative diagram of two workers career trajectories over 10 yearsStarting pointBoth workers startas customer servicerepresentativesOccupationaltrajectoriesEach worker follows adiferent career pathwayWithin-occupationadvancementsEach worker advancesinto a more s

33、enior role10Year 123456789TopSecondThirdFourthBottomIncomequintilesOccupation switch:Pivots to project coordinator,acquiring skills in data and scope managementAdvancement:Gets promoted to forecasting and planning managerOccupation switch:Applies skills to become a salespersonAdvancement:Gets promot

34、ed to frst-line supervisor,acquiring managerial skillsIndividuals follow diferent career trajectories,even starting from the same point.responsibility for caregiving and household chores,while men may shoulder greater breadwinning responsibilities,which can restrict career choices for both.5 Whether

35、 or not those traditional or stereotypical responsibilities hold sway lies outside the scope of this article.(For details,see Box 2,“Our data,scope,and methodology.”)The gender pay gap highlights differences in how men and women realize value from their human capital.Over a 30-year career,we estimat

36、e,women earn about$500,000 less than men,on average.6 This loss of payand productivity,by implicationtakes on particular importance in the context of tight labor markets and future demographic headwinds,with fewer workers potentially needing to support more retirees and fuel the nations economic eng

37、ine.As automation and AI transform the nature of work and the skills required in the economy,optimal talent utilization is becoming a critical issue.74Tough trade-offs:How time and career choices shape the gender pay gapData sources.Our research uses licensed,de-identified data from US-based online

38、public professional profiles to trace self-reported employment statuses and job changes.Our data set contains information on gender,education,job title,employer,and date,but it does not contain information on individuals names,locations within the United States,race,ethnicity,or other personal chara

39、cteristics.We selected a randomized sample of one million men and one million women that was gender identified based on a machine learning model that predicts gender using names,birth years,and name origin.From this data set,we selected a subset of individuals who declared their education,changed ro

40、les at least once,and had at least ten years of work experience following their highest educational attainment.This winnowed the sample down to 50,529 men and 35,235 women for a total of 85,764 individuals in the United States.1 It excludes those who may have exited the workforce altogether.This sel

41、ection procedure in and of itself could result in a skewed sample,which we explore in more detail in the next section.These approximately 86,000 profiles include about 36,000 unique job titles,which can be mapped to 705 occupations classified by the US Bureau of Labor Statistics.Because sectors are

42、determined at the company level,note that individuals can work in different sectors while performing the same occupation.We integrate these individual-level career profile data with several occupation-level data sets for the overall US workforce,including wages and wage distribution by occupation fr

43、om the US Bureau of Labor Statistics,gender wage gap within occupations from IPUMS(formerly Integrated Public Use Microdata Series),working hours from the US Census Bureaus American Community Survey,and occupational characteristics(such as competitiveness,flexibility,physical 1 We present the number

44、 of individual profiles as rounded figures in the main article text:that is,about 35,000 women,51,000 men,and 86,000 total.2 Women in the Workplace 2024:The 10th-anniversary report,McKinsey&Company and LeanIn,September 2024.3 The gender pay gap has been decreasing consistently over the past three de

45、cades.By using 2022 wages for workers from earlier periods,our pay gap estimates for the sample are conservative.demands,and more)from the Occupational Information Network(O*NET).We also validate our findings on the distribution of the workforce by seniority levels(entry level,manager,top manager,C-

46、suite position)against McKinseys Women in theWorkplace survey.2Scope of data.Our sample reflects online work histories and skews toward men(59 percent in the sample,compared with 53 percent in the US workforce)and higher-educated workers in higher-paying occupations such as managers,STEM professiona

47、ls,and business and legal professionals(exhibit).The sample of men is somewhat differently skewed compared with the sample of women,perhaps reflecting womens lower representation in higher-paying occupations and,consequently,in online profiles.We did not reweight our sample to mirror the US occupati

48、onal mix,because predicting each stage of an individuals career path across various occupations would be prohibitively difficult.Although this approach means our findings are not representative of the entire economy,it allows us to use reported data more directly and minimize assumptions.Even though

49、 our analysis covers the first ten years of a career,our findings for the next ten years have been directionally similar.Methodology.In earlier research by the McKinsey Global Institute(MGI),we measured the value of human capital in terms of lifetime earnings,while in this research,we focus on annua

50、l wages.For our analysis,we built a data set with details on each worker for every year of work experience,along with their corresponding role,occupation,and wage.This data set allows us to distill insights on changing roles,occupational trajectories,career breaks,pay gaps,and more.About two-thirds

51、of workers in our sample started their careers after 2000,with about half entering after 2005.We use real annual wages in 2022 as the base year for average wages in any occupation in the tenth calendar year of a career,and then apply the 2022 gender wage gap by occupation.3 We use this approach beca

52、use career pathway patterns are similar for women irrespective of their entry year into the workforce,and the same holds true for men.To understand differences in career trajectory patterns between men and women,we categorize all occupations into quintiles based on their average wages in 2022.We the

53、n track the movements of individuals between these quintiles from the occupation they began their careers in to their occupation at year ten,keeping the quintile classification of the occupation constant throughout the entire period.To analyze the drivers of the gender pay gap,we hold all variables

54、except one constant to isolate its specific effect.For example,we hold wages constant while analyzing the wage distribution that women would have if they followed the same career pathways as men.We separately control for average,occupation-specific working hours of men and women,and we model differe

55、ntial pay levels within each occupation based on role titles and tenures.We account for the impact of education level and type of degree on the pay gap by analyzing cohorts of individuals who began their careers in the same occupation and tracing their career arcs.We also recognize that an individua

56、ls age and years of experience can influence the pay gap.To control for this,we focused on individuals with at least ten years of work experience,examining their career trajectories from their entry into the workforce to year ten.As discussed earlier,we also validated our findings for a separate sub

57、set of 27,000 individuals who had at least 20 years of recorded experience,distilling the drivers of the pay gap at year20,and found that the results remained Box 2Our data,scope,and methodology5Tough trade-offs:How time and career choices shape the gender pay gapconsistent,with continuing differenc

58、es in career trajectories between men and women in the second ten-year period.In this report,we typically present average trends for men and women,while recognizing that there are variations in these averages.We also checked for statistical significance across all metrics represented in this article

59、 and included only those that are statistically significant at a 5 percent level.4Limitations.While we draw on a detailed and rich data set,our analysis reflects the challenges of working with de-identified,4 That is to say,the p-value is less than 5 percent(p8 points)Occupations groupedby pay gap d

60、ue towhere workers starttheir careers and whichpathways they pursue58.389.787.160.9Occupations inwhich men earnmoderately more(Pay gap:up to 8 points)57.586.985.058.9Occupations inwhich women earnmore (“pay premium”trajectories)Measures of full-time work and competition across occupations18Tough tra

61、de-offs:How time and career choices shape the gender pay gapAmong the women who started out as tech managers,for example,only about one-third remained in the tech profession,compared with half of all men.Specifically,just 6 percent of women continued as tech managers,while 16percent of men did.Among

62、 the women who left,about half transitioned to similarly high-paying roles,for example,marketing managers,while the rest moved to lower-paying positions,for example,community service managers.In contrast,of the men who exited tech,three-fifths(29 percent out of the 50percent)shifted to other high-pa

63、ying occupations.Similarly,only about 40 percent of women who began their careers as tech support staff stayed in the tech field,compared with 60 percent of men.Among those who stayed in tech,a slightly higher proportion of women than men advanced to better-paying tech positions like engineers and m

64、anagers.However,40 percent of women who left tech(or 24 percent of all women)left for lower-paying occupations like customer service representatives,while only one-third of the men(or 12 percent of all men)did so(Exhibit 10).Overall,women make up about one-quarter of the workforce employed as tech p

65、rofessionals and experience a lower-than-average 23 percent pay gap.19Tough trade-offs:How time and career choices shape the gender pay gapOther examples also illustrate this trend.In the Spotlight box,we present two occupations currently dominated by womennurses and office supportand another two si

66、milar to tech with male majoritiesmanagers and production workers.Two of these are growing,as tech isnurses and managersand two are shrinkingoffice support and production workers.(See Spotlight“Diverging career trajectories among managers,nurses,office support,and production workers.”)Exhibit 10McKi

67、nsey&CompanyNote:Figures based on de-identifed work-history profles of 3,000 women and 9,000 men.See technical appendix for details on the data set.Figures may not sum to 100%,because of rounding.Sixteen tech occupations categorized based on role descriptions and skills required.Salaries indexed to

68、2022 occupation average salary.Source:IPUMS,2022;American Community Survey,2022;US Bureau of Labor Statistics;McKinsey Global Institute analysisDistribution of occupations whereworkers end up 10 years after startingas tech professionals,%SimilarlevelLowerHigherLowerSimilarHigherLowerSimilarYear 1:Wh

69、ere they starttheir careersYear 10:Where they end upOccupationsoutside tech,by income levelProfessional techoccupations,by income levelHigher quintileManagersEngineersSupport stafSame quintileLower quintileWomenMen61616382125311521185623119353425301844282251312122411321 29Marketing managersExample o

70、ccupationsoutside techExamples:Networksystem managers,computer networkarchitects(top payquintile)Examples:Software developers,hardware engineers(top,2nd quintiles)Examples:User-support specialists,computer operators(2nd4th quintiles)Community servicemanagersGeneral andoperations managersFinancial ma

71、nagersBusiness operationsspecialistsManagement analystsCustomer servicerepresentativesAssistantsTech managers(average salary:$132,000 a year)Tech engineers($102,000)Tech supportstaf($75,000)20Tough trade-offs:How time and career choices shape the gender pay gapManagers.In this male-dominated,high-pa

72、ying occupational group,women were less likely to remain in management and more often shifted from frontline functions to lower-paying support roles.When women left management,they tended to secure higher-or similar-paying jobs like real estate broker or organizational consultant.Note:Figures based

73、on de-identifed work-history profles of 4,000 women and 7,000 men.See technical appendix for details on the data set.Figures may not sum to 100%,because of rounding.Frontline managers are core to operations and the revenue-generating units of an organization,and support managers focus on other units

74、.Salaries indexed to 2022 occupation average salary.Source:IPUMS,2022;American Community Survey,2022;US Bureau of Labor Statistics;McKinsey Global Institute analysisDistribution of occupations whereworkers end up 10 years after startingas managers,%SimilarLowerHigherLowerSimilarYear 1:Where they sta

75、rttheir careersYear 10:Where they end upManagerialoccupations,by income levelFrontlineSupportHigherlevelWomenMen21Real estate brokersFinancial specialistsMarket research specialistsOrganizational consultantsWebsite administrators,document managementspecialstsAuditorsExample occupationsoutside manage

76、ment412338202430263033219292833161410Occupationsoutside management,by income levelHigher quintileSame quintileLower quintileExamples:Sales orgeneral managers(top,2nd payquintiles)Frontlinemanagers(average salary:$104,000 a year)Examples:Humanresources managers,administrativemanagers(top3rd quintiles

77、)Supportmanagers($84,000)SpotlightDiverging career trajectories among managers,nurses,office support,and production workers21Tough trade-offs:How time and career choices shape the gender pay gapNurses.This women-dominated occupation represents an interesting difference.Women more often remained in t

78、hese roles,with nearly half staying on as nurses,compared with just over a quarter of men.More male nurses advanced to even higher-paying occupations in the health field,such as medical and health services managers.McKinsey&CompanyNote:Figures based on de-identifed work-history profles of 700 women

79、and 250 men.See technical appendix for details on the data set.Figures may not sum to 100%,because of rounding.Includes licensed practical nurses,licensed vocational nurses,and registered nurses.Salary indexed to 2022 occupation average salary.Source:IPUMS,2022;American Community Survey,2022;US Bure

80、au of Labor Statistics;McKinsey Global Institute analysisDistribution of occupations whereworkers end up 10 years after startingas nurses,%WomenMen2019184714152741Nurses(average salary:$75,000 a year,2nd pay quintile)Year 1:Where they starttheir careersYear 10:Where they end upSimilarLowerHigherleve

81、lMedical and health services managersNursing instructorsMedical records andhealth informationtechniciansExample occupationsRemainednursesDiferentoccupations,by income levelHigher quintileSame quintileLower quintileDiverging career trajectories among managers,nurses,office support,and production work

82、ers(continued)22Tough trade-offs:How time and career choices shape the gender pay gapOffice support workers.Even in low-paying occupation groups likely to shrink due to automation and AIsuch as office supportthe trend is similar.Women who left were more likely to find work in other low-paying occupa

83、tions,like counter attendants and customer service representatives.McKinsey&CompanyNote:Figures based on de-identifed work-history profles of 5,000 women and 3,000 men.See technical appendix for details on the data set.Figures may not sum to 100%,because of rounding.Salaries indexed to 2022 occupati

84、on average salary.Source:IPUMS,2022;American Community Survey,2022;US Bureau of Labor Statistics;McKinsey Global Institute analysisDistribution of occupations whereworkers end up 10 years after startingas ofce support workers,%SimilarlevelLowerYear 1:Where they starttheir careersYear 10:Where they e

85、nd upOfce supportoccupations,by income levelHigherModerateLowerWomenMen193283111353171450Computer systems analystsHuman resources managersProcurement managersCounter attendantsPublic relations specialistsLegal assistantsExample occupationsoutside ofce supportCustomer servicerepresentativesHigherHigh

86、erLowerLowerSimilarSimilarOccupationsoutside ofce support,by income levelHigher quintileSame quintileLower quintile441959757414111249101264Medical record technicians1132210728Example:First-linesupervisors ofofce workers(2nd4th quintiles)Moderate income($52,000 a year)Example:Order fllers(4th,bottom

87、quintiles)Lower income($37,000 a year)Example:Databaseadministrators(top,2nd payquintiles)Higher income(average salary:$92,000 a year)Diverging career trajectories among managers,nurses,office support,and production workers(continued)23Tough trade-offs:How time and career choices shape the gender pa

88、y gapProduction workers.A similar trend is on display in production work.When men left,they tended to transition to higher-paying occupations like procurement managers or industrial engineers.When women left,they were more likely to take on lower-paying work as administrative assistants or stock cle

89、rks,which are also being automated.McKinsey&CompanyNote:Figures based on de-identifed work-history profles of 500 women and 1,200 men.See technical appendix for details on the data set.Figures may not sum to 100%,because of rounding.Salaries indexed to 2022 occupation average salary.Source:IPUMS,202

90、2;American Community Survey,2022;US Bureau of Labor Statistics;McKinsey Global Institute analysisDistribution of occupations whereworkers end up 10 years after startingas production workers,%SimilarSimilarLowerLowerYear 1:Where they starttheir careersYear 10:Where they end upProduction workoccupatio

91、ns,by income levelModerateLowerHigherlevelHigherWomenMenIndustrial production managersIndustrial engineersMaintenance and repair workersSafety specialistsAdministrative assistantsExample occupationsoutside production workStock clerks2513718241212141553824467737656Example:First-linesupervisors ofprod

92、uction work(2nd4th payquintiles)Moderate income(average salary:$57,000 a year)Example:Machinists(4th,bottom quintiles)Lower income($35,000 a year)Occupations outsideproduction work,by income levelHigher quintileSame quintileLower quintileDiverging career trajectories among managers,nurses,office sup

93、port,and production workers(continued)24Tough trade-offs:How time and career choices shape the gender pay gapFewer women are moving into occupations that are projected to grow,but some employers are altering this trend The mix of occupations needed by Americas economy is evolving.Demand for workers

94、in some fieldsnotably,healthcare,technology,and managementis expected to grow through 2030 as adoption of automation and AI technologies accelerates,while some roles in office support and production work will disappear in aggregate by then,according to previous MGI research.35 Millions of US workers

95、 will likely need to transition out of“shrinking”fields of work into“growing”ones.36Today,women are not only less concentrated in growing occupations but also less likely than men to move into themDespite their outsize presence in growing healthcare occupations,women are underrepresented in growing

96、occupations overall.Only 59 percent of women are in these occupations,compared with 67 percent of men.Conversely,women are overrepresented in shrinking occupations.Looking back,we also see that women moved into and remained in growing occupations less often than men in our sample.Women accounted for

97、 just 42 percent of the workers who transitioned from shrinking occupations to growing ones or stayed back in growing occupations over time.For example,historically,more women than men have moved into healthcare,a fast-growing occupational group,and into creative and education industries,which are e

98、xpected to grow more modestly.The question of why more men dont enter these high-growth“pink-collar”occupations as often as women is also something to consider.37 At the same time,women are underrepresented by a wide margin among workers moving into fast-growing STEM jobs and management roles.Employ

99、ers can be expected to adjust wages and work arrangements to meet their future demands,providing an incentive for qualified individuals to move into growing occupations,as they have in the past.For example,in 2022,18 percent of women in the workforce were in management fields,up from 15 percent in 2

100、012.Similarly,the share of men in these fields increased,albeit at a slower pace,from 17 percent to 19 percent.Conversely,in shrinking fields like office and administrative support,the concentration of women decreased from 19 percent to 16 percent,while the share of men declined from 6 percent to 5

101、percent.Overall,historical patterns suggest that womens current underrepresentation in growing occupations could become even more pronounced over time.38 That is,while the proportion of women working in growing segments could rise to nearly two-thirds by 2030,the proportion of men could increase mor

102、e rapidly so that more than three-fourths of them are working in growing segments by then(Exhibit 11).The disproportionate presence of men in growing and higher-paying occupations,coupled with the overrepresentation of women in shrinking occupations,could cause the pay gap to stay the same or increa

103、se over time.25Tough trade-offs:How time and career choices shape the gender pay gapSome employers have facilitated movement to growing occupations for all employees while also reducing the gender pay gap Some companies are at the forefront of building human capital for all workers,both men and wome

104、n,while at the same time delivering top-tier financial performance.We labeled those employers People+Performance Winners(P+P Winners)in previous research.In that research,we found that employees who pass through P+P companies go on to have higher lifetime earnings on average than those who did not.3

105、9(See Box 3,“What are People+Performance Winners and what might they show us?”)Now,we build a gender-disaggregated view for 12,000 career histories spanning 1,100 US-based employers.We find that,adjusting for industry mix,women who passed through the halls of P+P Winners at any time in the first ten

106、 years of their careers ended up with higher average salaries and lower gender pay gaps than those who had passed through People-Focused Companies,Performance-Driven Companies,or Typical Performers.40 Although these are correlations and we cannot directly ascertain the causes,we found that,on averag

107、e,both men and women who worked for P+P Winners moved more often into growing occupations,experienced more internal role moves,and had longer tenures at the company.In our analysis,we did not find higher womens representation in P+P Winners per se;instead,we identified a strong emphasis on both expe

108、cting and facilitating skills development for all employees,including women.Exhibit 11McKinsey&CompanyEstimate based on trajectory patterns followed by men and women in the sample over the frst 10 years of their careers applied to future nonfarm labor demand by occupation in 2030.Source:IPUMS,2022;A

109、merican Community Survey,2022;US Bureau of Labor Statistics;Generative AI and the future of work in America,McKinsey Global Institute,2023;McKinsey Global Institute analysisUS nonfarm workers moving between growing and shrinking occupations through 2030,million44385767%5214614289621312030Men2022Wome

110、n202220301321New entrants to workforce,202230Growing occupationsShrinking occupations64%76%59%26Tough trade-offs:How time and career choices shape the gender pay gapIn MGIs 2023 report Performance through people:Transforming human capital into competitive advantage,we introduced a framework that cla

111、ssified 1,800 global companies according to two factors relative to their sector peers:(1)how much they focused on developing human capital;and(2)whether they financially outperformed.We classified the majority of the companies we analyzed as Typical Performers,which do not stand out in either dimen

112、sion;a small subset as People-Focused Companies,for the significant resources they devoted to developing employees,even if performance was unremarkable);and another subset as Performance-Driven Companies,for their top-tier financial results,even if human capital development was average or typical.Bu

113、t it is the fourth set,People+Performance Winners(P+P Winners)about 10 percent of the companies we analyzedthat we want to draw attention to here.P+P Winners were the select subset of firms that we saw excel at creating opportunities for their employees to build skills,which we measured through inte

114、rnal mobility opportunities,training hours,and organizational health scores.At the same time,this subset consistently cleared the highest bar for financial performance.We found that P+P Winners spanned all sectors in our sample and showed greater resilience and more consistent earnings relative to t

115、heir peers.Drawing on our previous research,in this work we updated data for the 1,000 US-based global businesses analyzed previously,added about 100 US-based companies,and categorized them into the four subsets described above.Of the approximately 86,000 individuals in our present study sample,we f

116、ound that 7,409 men and 5,067 women(12,476 unique workers in total)had worked at one of the 1,100 companies analyzed at some point in their careers.We note that more than 50 percent of the individuals employed by these businesses in our sample were in management or STEM professional positions;that i

117、s,they were not representative of the workforce as a whole.For those 12,000 individuals in our sample,we analyzed the occupational trajectories of both men and women by the type of company they passed through.We studied which occupations they moved to(whether growing or shrinking),the number of role

118、 moves they made within the company,the time they spent in the company,and the associated gender pay gaps.We did the same for workers classified based on which type of company they began their careers at,where they had worked early in their careers,and which one they had worked at the longest.Our fi

119、ndings about the relative benefits of P+P Winners remained consistent across all four approaches.Box 3What are People+Performance Winners and what might they show usImportantly,P+P Winners provide workers with clear organizational vision,translated for the specific contexts of individual teams and r

120、oles.They offer a performance culture with transparent expectations and incentives that challenges employees while empowering them,as well as a focus on innovation that encourages risk-taking with appropriate coaching.By contrast,People-Focused Companies excel on human capital development measures l

121、ike internal rotation and training but lack P+P Winners performance-oriented culture,while Performance-Driven Companies focus on defined performance goals,efficiency,and a strong external orientation rather than empowering employees.The distinctive organizational culture of P+P Winners offers lesson

122、s to employers intensifying efforts to attract talent and reskill workers given trends expected for the future of work(Exhibit 12).27Tough trade-offs:How time and career choices shape the gender pay gapDrawing from the P+P Winner advantages observed in our study samples,some broad ideas stand out th

123、at could be useful to other employers.P+P Winners cultivate internal mobility opportunities that can build skills and retain talent.They also target training and apprenticeship programs,especially for midcareer talent.Other evidence documents the promise in these approaches.For example,skill-enhanci

124、ng opportunities within organizations have increased employee satisfaction and retention.41 According to LinkedIns Global Talent Trends 2020 research,employees tend to remain at a company 41 percent longer if the company regularly promotes from within.42 And a recent Gallup survey suggests that midl

125、evel and mid-tenure employees,who constitute the majority in most organizations,would benefit from targeted training and development programs.43 As labor markets remain tight amid demographic shifts,employers should keep in mind that workers will have more options in choosing their work and choosing

126、 their employer.Both men and women can,and will,make strategic career moves that help them grow.Each individuals choice is their own,but employers can do more to position themselves for this future.A persons first job is just the first step in a long journey.Work experience matters and defines the q

127、uality of workers career arcs as well as their pay.Gender pay gaps that grow over time reflect different choices made by men and women in utilizing and building their human capital.Companies can influence those choices by fostering organizational cultures that emphasize role mobility and skill build

128、ing for all workers,ensuring that both women and men realize more value from their human capital over their careers at the same time that they prepare for the future of work.Exhibit 12McKinsey&CompanyNote:Figures based on de-identifed work-history profles of 5,000 women and 7,000 men who passed thro

129、ugh 1 of 1,100 companies classifed as 1 of the 4 company types above.See technical appendix for details on the data set.Growing occupations are occupations that are expected to see an increase in labor demand between 2022 and 2030.Source:IPUMS,2022;American Community Survey,2022;US Bureau of Labor S

130、tatistics;Generative AI and the future of work in America,McKinsey Global Institute,2023;Performance through people,McKinsey Global Institute,2023;McKinsey Global Institute analysisRanking of four company types on diferent human capital metricsWomenswages,$thousandPay gap betweenwomen and mendue to

131、diferencesin starting point andoccupational trajectories,percentage pointsNumber of rolemoves withincompany in frst10 years of career,all workersShare of allworkers movinginto growingoccupations,%Average tenureat company,all workers,years93864.04.64.84.12.21.81.72.11557People+PerformanceWinnersPerfo

132、rmance-DrivenCompaniesPeople-FocusedCompaniesTypicalPerformers62696663878828Tough trade-offs:How time and career choices shape the gender pay gapAcknowledgmentsThis research was led by Anu Madgavkar,a McKinsey Global Institute partner in New Jersey;Kweilin Ellingrud,a McKinsey senior partner and dir

133、ector of MGI in Minneapolis;Sven Smit,a McKinsey senior partner and chair of MGI in Amsterdam;Chris Bradley,a McKinsey senior partner and director of MGI in Sydney;Olivia White,a McKinsey senior partner and director of MGI in San Francisco;and Kanmani Chockalingam,an MGI Fellow in San Francisco.Kanm

134、ani Chockalingam led the working team,which included Ananya Sivaraman,Dapo Folami,Mackenzie Manofsky,Paige Hasebe,Rebecca Solcia,and Sirui Wang.This project benefited immensely from the perspectives of McKinsey colleagues.Our thanks go to Dana Maor,Davis Carlin,Eric Kutcher,Jason Bloch,Mekala Krishn

135、an,Sarah Gitlin,and Tracy Nowski.We are grateful to the academic advisers who challenged our thinking and sharpened our insights:Sir Christopher Pissarides,Nobel Prize winner and Regius Professor of Economics at the London School of Economics;Matthew Slaughter,Paul Danos Dean of the Tuck School of B

136、usiness and the Earl C.Daum 1924 Professor of International Business,Dartmouth College;and Jess Crespo Cuaresma,professor of macroeconomics at the WU Vienna University of Economics and Business.The article was edited and produced by MGI senior editors Cintra Scott and Stephanie Strom,together with s

137、enior data visualization editor Chuck Burke.We also thank David Batcheck,Rachel Robinson,Rebeca Robboy,and Rishabh Chaturvedi for their support.We thank McKinsey Global Publishing for designing this visual narrative,including team members Charmaine Rice,Dana Sand,Diane Rice,Katrina Parker,Mary Gayen

138、,and Nathan R.Wilson.As with all MGI research,this work is independent and has not been commissioned or sponsored in any way by any business,government,or other institution.While we gathered a variety of perspectives,our views have been independently formed and articulated in this report.Any errors

139、are our own.29Tough trade-offs:How time and career choices shape the gender pay gapCareer breaks are intervals during which workers temporarily leave the workforce,affecting the accumulation of work experience and career progression.We quantify the duration of a career break as the number of days be

140、tween the end of one role and the start of a new role,excluding a one-month transition period.Career pathways or trajectories are the sequence of roles and role moves undertaken by a worker over a career(in our study,a ten-year period)that inform the accumulation of skills,work experience,and pay.Co

141、mpetition score is an O*NET work context score based on the extent to which a job requires the worker to compete or to be aware of competitive pressures(0=low,100=high).An example of a low-competition occupation is receptionist or clerk,and a high-competition occupation is real estateagent.Flexibili

142、ty or full-time score is measured as the share of workers in the US workforce that work full time in each occupation,multiplied by 100.An occupation is said to be more flexible when it has a lower share of workers in full-time roles;that is,the occupation can be carried out even in a part-time capac

143、ity.Gender pay gap in this research is defined as the difference in mean annual wages between all men and all women in the sample.(For more detail,see Box 1“Definitions of the gender pay gap vary.”)Growing occupations are expected to increase their demand for labor between 2022 and 2030(for example,

144、STEM professionals),based on MGI research,while shrinking occupations are expected to eliminate jobs in the same period(for example,office support).Income quintiles in this research refer to the quintiles of occupations by their average wage in 2022.Under this definition,each quintile can represent

145、more or less than one-fifth of all men and women employed.Occupational categories are groupings of occupations requiring a similar set of knowledge,skills,and abilities.For example,general and operational managers,construction managers,and industrial production managers all fall within the occupatio

146、nal category of“managers.”Occupations are defined by the US Bureau of Labor Statistics and O*NET as requiring different mixes of knowledge,skills,and abilities,and are performed through a variety of activities and tasks.P+P Winners are companies that excel in both human capital development and finan

147、cial performance.Performance-Driven Companies achieve high financial results without prioritizing skills development and the work environment.People-Focused Companies invest in employee development but lack strong financials.Most companies,Typical Performers,excel in neither area.(For more detail,se

148、e Box 3“What are People+Performance Winners and what might they show us?”)Residual pay gap refers to the immeasurable portion of the gender pay gap after accounting for all observable characteristics in our sample.This gap is not solely an indicator of gender discrimination;it can also be driven by

149、other factors,such as industry-and firm-level differences.Role is defined as a combination of an individuals title(such as manager or senior manager),occupation(for example,general and operations manager or training and development manager),occupation category(for example,managers or business and le

150、gal professionals),and the organization within which they work.Role move is a change in an individuals job,occupation,or organization.It includes promotions or lateral moves within the same organization as well as moves from one employer to another.Role moves can be initiated by the employee(quittin

151、g)or the employer(in layoffs or dismissals for cause).Skill distance is expressed as the weighted share of skills required for a new job that do not overlap with those required by the job that immediately preceded it.The skills are weighted by frequency of use to emphasize skills that are unique to

152、a particular role over those that are common across roles.Work experience encompasses the accumulated knowledge that workers gain by being in the labor market.This can occur through carrying out the work itself,participating in employer-provided learning and development programs,changing jobs to bet

153、ter match existing skills,and acquiring new skills through role changes.Work-experience pay gap is the portion of the total gender pay gap that can be attributed to career pathways and time spent out of work in our analysis.The career pathway differences we track include career starting points,occup

154、ational trajectories,and advancements within occupations.Glossary 30Tough trade-offs:How time and career choices shape the gender pay gapEndnotes1 See Human capital at work:The value of experience,McKinsey Global Institute,June 2022.The report analyzes the records of four million peoples work experi

155、ence trajectories in four countriesGermany,India,the United Kingdom,and the United Statesto trace how people accumulate human capital throughout their working lives.2 Women accounted for as much as 59percent of bachelors degrees awarded in 2022,63 percent of masters degrees,and 57 percent of doctora

156、l and professional degrees.More than half the postsecondary graduates majoring in English literature,social sciences,and history are women,but women are increasingly moving into fields traditionally dominated by men.For example,23 percent of recent engineering graduates were women,compared with less

157、 than 1 percent in 1970.See tables 318.10,325.50,and 325.90,National Center for Education Statistics,US Department of Education.By many measures,American boys and men are struggling to keep up with girls and women in educational attainment.Richard Reeves,author of Of boys and men:Why the modern male

158、 is struggling,why it matters,and what to do about it(Brookings,2022),calls this an“education crisis for boys and men.”3 “Civilian labor force participation rate,”US Bureau of Labor Statistics,December 2024.4 Our data set draws on licensed,de-identified public professional-profile data and traces se

159、lf-reported employment statuses and job changes for at least ten years after a persons highest educational attainment,whether that be a high school diploma or a doctoral-level degree.We pay particular attention to the first ten years of a career because this period provides sufficient time for indiv

160、iduals to begin establishing their work experience trajectories.Additionally,this time frame offers ample,comparable data for men and women.Note that this data set includes only a binary gender classification,a limitation being that individuals identifying as nonbinary are likely categorized as eith

161、er male or female.See Box 2,“Our data,scope,and methodology”for more details on our sample and approach.5 American Time Use Survey,IPUMS,201621;Richard Fry et al.,“In a growing share of US marriages,husbands and wives earn about the same,”Pew Research Center,April 2023.6 Other research calculates sa

162、lary losses for women in the range of approximately$400,000 to$600,000 over their careers.See Amina Khalique,What you should know about the 2023 gender wage gap,Center for American Progress,October 2024,and“The lifetime wage gap,state by state,”National Womens Law Center,March 2024.7 Generative AI a

163、nd the future of work in America,McKinsey Global Institute,July2023.8 We acknowledge that measuring career breaks can be prone to errors because not all breaks are explicitly reported in online work histories,especially when a person returns to the same role afterward.We want to emphasize that we lo

164、ok at directional patterns in this analysis and that figures(the numbers of breaks and the total time spent off work)are probably too low because breaks are underreported.9 Note that the data set we worked with did not reveal whether individuals in the sample had children.Childrearing years are gene

165、rally considered to span ages 25 and 50.In the United States,the average age of first-time mothers is 27,and they are typically seen as rearing a child till the child turns 18.See Katherine Schaeffer and Carolina Arago,Key facts about moms in the U.S.,Pew Research Center,May 2023.10 In our sample,wo

166、men with only a high school degree took 565 days of break from paid work over ten years,on average,compared with 390 days for women with bachelors degrees and 378 days for women with doctorates.11 Georgia Poyatzis and Gretchen Livingston,“New data:Childcare costs remain an almost prohibitive expense

167、,”US Department of Labor Blog,November 19,2024;and Shelly Lundberg,Robert A.Pollak,and Jenna Stearns,“Family inequality:Diverging patterns in marriage,cohabitation,and childbearing,”Journal of Economic Perspectives,volume 30,number 2,spring2016.12“American Time Use Survey:2023 results,”US Bureau of

168、Labor Statistics,June 2024.13 Kim Parker and Wendy Wang,“How mothers and fathers spend their time,”in Modern parenthood:Roles of moms and dads converge as they balance work and family,Pew Research Center,March 2013.14 Average weekly working hours were self-reported for part-time and full-time worker

169、s in 2022 as part of the US Census Bureaus American Community Survey.15 For example,among full-time workers,women surgeons report working more hours than men.In the childcare-worker occupation,there are more men working part time than women.16 Based on methodology established in previous MGI researc

170、h on human capital.Entry-level skills account for the remaining portion of lifetime earnings.See Human capital at work:The value of experience,McKinsey Global Institute,June 2022.17 Human capital at work:the value of experience,McKinsey Global Institute,June2022.18 Other research has suggested that

171、women areor are perceived to bemore risk averse than men and may particularly avoid risk under stress.See,for example,Christie Hunter Arscott,“Why women should make bold moves early in their careers,”Harvard Business Review,July 2022;Doug Sundheim,“Do women take as many risks as men?,”Harvard Busine

172、ss Review,February 2013;M.Mather and N.R.Lighthall,“Risk and reward are processed differently in decisions made under stress,”Current Directions in Psychological Science,volume 21,number 1,2012;and S.Ball,C.Eckel,and M.Heracleous,“Risk aversion and physical prowess:prediction,choice and bias,”Journa

173、l of Risk and Uncertainty,volume 41,number 3,2010.19 See,for example:“The state of working class men,”American Institute for Boys and Men,August 2024,which summarizes:“While the shift to a knowledge-based economy has blessed the more highly educated with strong and rising wages,working class men fac

174、e dwindling job prospects,stagnant wages,and declining health”;Anne Case and Angus Deaton,Deaths of despair and the future of capitalism,Princeton University Press,2020.20“Quartiles and selected deciles of usual weekly earnings of full-time wage and salary workers by selected characteristics,not sea

175、sonally adjusted,”US Bureau of Labor Statistics,accessed January 17,2025.For a discussion of this trend,see,for example,John Burn-Murdoch,“Young women are starting to leave men behind,”Financial Times,September 20,2024.21 The income distribution observed here offers an important reminder that our sa

176、mple is overweighted with higher-income workers:Note that 51 percent of men and 35percent of women in our sample began their careers in top-earning occupations,31Tough trade-offs:How time and career choices shape the gender pay gapwhile 18 percent of men and 10 percent of women in the workforce as a

177、 whole are in these top-earning occupations.22 These estimates are generally in line with the Women in the Workplace survey conducted by McKinsey and LeanIn,which collected information from HR leaders on the overall talent pipeline in 280 companies employing more than three million workers.See Women

178、 in the Workplace 2024:The 10th-anniversary report,McKinsey and LeanIn,September 2024.23 This estimate is likely conservative.Information about the corporate talent pipeline is in line with other surveys,but our data set does not capture company-specific salary details and does not fully account for

179、 the various ways in which companies approach wage increments(yearly increments in role,for lateral moves,or for promotions).24“Understanding the gender wage gap,”US Department of Labor Womens Bureau Issue Brief,March 2023.25 Claudia Goldin,Hours flexibility and the gender gap in pay,Center for Amer

180、ican Progress,April 2015.26 Kory Kroft,Fabian Lange,and Matthew J.Notowidigdo,“Duration dependence and labor market conditions:Evidence from a field experiment,”The Quarterly Journal of Economics,volume 128,number 3,August 2013;and K.Katherine Weisshaar,“From opt out to blocked out:The challenges fo

181、r labor market re-entry after family-related employment lapses,”American Sociological Review,volume 83,number 1,2018.27 David Card,Ana Rute Cardoso,and Patrick Kline,“The gender wage gap:How firms influence womens pay relative to men,”Microeconomic Insights,2016.28 Katie Meara,Francesco Pastore,and

182、Allan Webster,“The gender pay gap in the USA:A matching study,”Journal of Population Economics,volume 33,2020.29 For example,research published in 2023 finds that job search patterns that diverge by gender can be partly explained by the greater risk aversion displayed by women and the higher levels

183、of overoptimism displayed by men.See Patricia Corts et al.,“Gender differences in job search and the earnings gap:Evidence from the field and lab,”The Quarterly Journal of Economics,volume 138,number 4,2023.30 Sigon Alon and Thomas A.DiPrete,“Gender differences in the formation of a field of study c

184、hoice set,”Sociological Science,2015;and Adriana D.Kugler,Catherine H.Tinsley,and Olga Ukhaneva,“Choice of majors:Are women really different from men?,”Economics of Education Review,volume 81,2021.31 Francine D.Blau and Lawrence M.Kahn,Gender differences in pay,National Bureau of Economic Research w

185、orking paper number 7732,June 2000;and Corinne A.Moss-Racusin et al.,“Science facultys subtle gender biases favor male students,”Proceedings of the National Academy of Sciences,September 2012.32 Including licensed practical nurses,licensed vocational nurses,and registered nurses.33 Homing in on thes

186、e two characteristics follows our testing of several others measured by O*NET for more than 700 occupations.Our analysis showed that most of these factors had no significant bearing on pay gap related to career pathways.Apart from workplace competition and flexibility,the characteristics we tested i

187、nclude the physical movement required,time pressure,and decision-making freedom,among others.See,for example,“Occupational requirements,”O*NET,accessed January 17,2025.34 Beyond measurable occupational traits,a study of German workers found that when heterosexual couples relocate geographically,the

188、mans earnings increase significantly,while women suffer substantial losses,suggesting another cause for trajectory gaps.See Lea Nassal and Marie Paul,“Couples,careers and spatial mobility,”Centre for Research and Analysis of Migration Discussion Paper Series,September 2022.35 Generative AI and the f

189、uture of work in America,McKinsey Global Institute,July2023.36 Declines in office support and production worktogether with food services,customer service,and sales jobsare expected to account for most of the 12million occupational shifts anticipated by 2030.Generative AI and the future of work in Am

190、erica,McKinsey Global Institute,July2023.37 Alexia Delfino,“Breaking gender barriers:Experimental evidence on men in pink-collar jobs,”American Economic Review,volume 114,number 6,June 2024.38 If historical patterns of movement over the first ten years of a career by gender were to continue until 20

191、30,only 12 percent of women in the workforce might be expected to transition from shrinking occupations to growing ones,compared with 16 percent of men.Additionally,just 48 percent of women might be expected to stay employed in growing occupations,compared with 59percent of men.39 Performance throug

192、h people:Transforming human capital into competitive advantage,McKinsey Global Institute,February 2023.40 Note that our estimates for pay gap and average salary assume that occupational pay differences hold across companies.We do not factor in company-specific paypractices.41 Michael Timmes,“Interna

193、l mobility:The missing piece of 2023 business strategy,”Forbes,February 17,2023.42“Global Talent Trends 2020:4 trends changing the way you attract and retain talent,”LinkedIn Talent Solutions,2020.43 Emily Lorenz,“Employee upskilling is vital in rapidly evolving job market,”Gallup,November 2024.Designed by McKinsey Global Publishing Copyright 2025 McKinsey&Company.All rights reserved.32Tough trade-offs:How time and career choices shape the gender pay gap