{"id":2944,"date":"2020-08-02T23:01:18","date_gmt":"2020-08-02T22:01:18","guid":{"rendered":"https:\/\/marriott-stats.com\/nigels-blog\/?p=2944"},"modified":"2021-05-27T12:04:40","modified_gmt":"2021-05-27T11:04:40","slug":"closing-gender-pay-gap-will-take-a-generation","status":"publish","type":"post","link":"https:\/\/marriott-stats.com\/nigels-blog\/closing-gender-pay-gap-will-take-a-generation\/","title":{"rendered":"Pay Gaps #16 – Eliminate your gender pay gap by playing Blackjack!"},"content":{"rendered":"

Imagine where you work, the median women earns 33% less than the median man.\u00a0 Although your workplace is gender balanced with 50:50 men:women, the pay gap exists because 1 in 4 of managers and 3 in 4 of the lowest paid admin staff are women.\u00a0 How long will it take for the pay gap to disappear assuming that all future recruitment at all levels have 50:50 candidate pools with men and women equally likely to be appointed to the role?<\/p>\n

Up to 25 years i.e. a generation<\/strong><\/span><\/h4>\n

<\/p>\n

When I point this out to people, I get a variety of reactions ranging from disbelief, despair and discouragement.\u00a0 I am not surprised by these sentiments because when I hear and read what others have to say about the gender pay gap, too often I get the sense that people think it can be solved with a 5 year project plan and the only reason it doesn’t happen is because people don’t want to make the effort.\u00a0 In part, this might be because some people still confuse gender pay gaps with unequal pay when in fact they have nothing to do with each other<\/a> but if you do think this, even subconciously, then of course you will tend to think resolution is simple because all you have to do is give women a pay rise which can be done tomorrow.<\/p>\n

I will first demonstrate why closing a gender pay gap is a 25 year generational project with a simple example of an employer with 16 male and 16 female employees.\u00a0 This demonstration will be backed up with a more sophisticated analysis using a simulation model in a spreadsheet which can be downloaded.\u00a0 Finally I will explain how the timeframe can be shortened if you adopt the mindset of a card counter playing blackjack in a casino.<\/p>\n

5050 STEM Ltd Today<\/span><\/strong><\/h4>\n

\"\"My fictional company 5050 STEM Ltd is so-called because it has the same number of male and female employees (16 of each) covering 4 types of jobs of which 2 (Engineers and Analysts) are STEM related.\u00a0 There are 8 employees in each job type and men and women are paid the same for doing the same type of job i.e. there is no equal pay issue.\u00a0 As highlighted in the graphic, the median man earns \u00a330 an hour and is an Engineer whilst the median woman is an Analyst earning \u00a320 an hour.\u00a0 So for every \u00a31 earned by the median man, the median woman earns 33p less i.e. the official median gender pay gap that would have to be reported to the government would be +33%.<\/p>\n

The reason for this pay gap is obvious.\u00a0 Men are more likely to be Managers & Engineers and women are more likely to be Analysts & Administrators.\u00a0 To eliminate a pay gap, the first step is ensure that each job type has the same gender ratio.\u00a0 Since 5050 STEM Ltd’s gender ratio is 1:1 that means our goal is transform this company so that each of the 4 job types has 50% men and 50% women.\u00a0 To achieve this, 6 employees need to change gender with 2 Managers & 1 Engineer becoming female and 1 Analyst & 2 Administrators becoming male.<\/p>\n

Important! When I say that the first step to eliminating a gender pay gap is to have the same gender ratio in each job type, the gender ratio does not have to be 50:50.\u00a0 An employer with a 90% male workforce can eliminate their gender pay gap if wherever you look in that employer boardroom, shop floor, department, location, pay grade, etc, you always see a 9:1 male:female ratio.<\/em><\/span><\/p>\n

\"\" \u00a0\"\"<\/p>\n

5050 STEM Ltd – Recruiting for the future<\/strong><\/span><\/h4>\n

When I state that closing a gender pay gap takes a generation, I am making three major assumptions.<\/p>\n

    \n
  1. The total number of employees remains unchanged.<\/li>\n
  2. For all future recruitment, on average, the gender ratio of candidates will be 50:50 for all job types.<\/li>\n
  3. Both male and female candidates for all job types are equally qualified and the probability of a vacancy being filled by a woman is equal to a man’s i.e. 50%.<\/li>\n<\/ol>\n

    My more sophisticated model which can be downloaded later on allows you to modify these assumptions and see what the effect is but I will be using these for 5050 STEM Ltd.<\/p>\n

    I want to emphasise assumption 3 now because this implies no sex discrimination at the recruitment stage.\u00a0 One obvious way to shorten the timeframe to closing the pay gap is to only appoint women to senior roles and only appoint men to junior roles.\u00a0 I am working on the understanding that this is illegal under British law and even if it is not, it not something I can ever endorse.\u00a0 Equality in my view is about men and women having equal chances to work wherever they wish and you cannot fight discrimination of one kind by replacing it with a different kind of discrimination.\u00a0 Any employer violating assumption #3 would leave themselves open to charges of discrimination either in a court of law or the court of public opinion.<\/p>\n

    If 5050 STEM Ltd wishes to change its gender ratio for all 4 job types through recruitment and promotion and not through growth (assumption 1), the first thing that has to happen is that jobs have to become vacant due to existing employees leaving the company.\u00a0 It should be obvious that an employer with high turnover of employees can achieve its desired gender ratio much quicker than an employer with low employee turnover which raises an interesting paradox.\u00a0 I think most people would agree that employers with low turnover are more likely to be desirable places to work than places with high turnover.\u00a0 Yet it would appear that high turnover employers can achieve the kudos for closing their pay gaps simply by being a horrible place to work at.<\/p>\n

    For my demonstration, I will assume for each round of recruitment, 1 in 8 employees within each of the 4 job types leave the company.\u00a0 I will also assume that every employee (male and female) has an equal chance of leaving.\u00a0 That means the probability that the employee leaving is a man is 3 in 4 for Managers, 5 in 8 for Engineers, 3 in 8 for Analysts and 1 in 4 for Administrators.\u00a0 By assumption 3 above, there is a 1 in 2 chance that they will be replaced by a woman and 1 in 2 chance they will be replaced by a man.\u00a0 Therefore we have 4 possible scenarios that can happen in\u00a0 a single round of recruitment which are –<\/p>\n

      \n
    1. Man replaced by a womaen<\/li>\n
    2. Man replaced by a man<\/li>\n
    3. Woman replaced by a woman<\/li>\n
    4. Woman replaced by a man<\/li>\n<\/ol>\n

      Scenarios 2 & 3 do not change the gender ratio.\u00a0 Scenario 1 improves the gender ratio if it occurs among Managers & Engineers and worsens the gender ratio if occurs among Analysts and Administrators.\u00a0 Scenario 4 is the reverse of scenario 1.\u00a0 Whilst the probability of the new employee being female is the same for all 4 job types, the probability of the leaving employee being female is different and hence the probabilities of each scenario are different for the 4 job types as shown below.<\/p>\n

      \"\"<\/p>\n

      For Managers, scenario 4 (Man to Woman) is desirable but the left hand crosstab table tells us the chances of this happening without discriminatory behaviour (assumption 3) and a gender balanced candidate pool (assumption 2) is 3 in 8 (=0.75 x 0.5).\u00a0 There is a 50% chance nothing changes and a 1 in 8 chance (=0.25 x 0.5) of a regression whereby a female manager is replaced by a male manager.\u00a0 Therefore the net probability that the number of female managers will increase by 1 in the next recruitment round is 25% (=37.5%-12.5%).<\/p>\n

      That tells us that on average it will take more than 1 recruitment round to achieve an increase in female representation among managers.\u00a0 The expected number of recruitment rounds is easy to calculate as it’s equal to 1 divided by the net probability of there being an additional female manager (0.25) which equals 4 recruitment rounds.\u00a0 It should be obvious that some employers will be unlucky and will take more than 4 rounds to improve female representation among managers even if they are genuinely non-discriminatory in their recruitment practices and others will be lucky and get there in 1 round.<\/p>\n

      If it take 4 recruitment rounds on average to increase the number of female managers by 1 , you should be able to see why employee turnover determines the timeframe to undertake 4 rounds of recruitment.\u00a0 A good employer with a loyal workforce might have to wait 10 years whilst a bad employer might achieve that within 2 years.\u00a0 Exactly the same applies to Administrators except this time the goal is to increase male representation so it will take on average 4 rounds of recruitment to increase the number of men by 1.\u00a0 But of course, this is not our end goal.\u00a0 All 5050 STEM Ltd has managed so far is to change the gender ratio from 1 in 4 women\/men for Managers\/Administrators to 3 in 8 men\/women.\u00a0 In other words, after 4 rounds, Managers and Administrators will be in the same position that Engineers and Analysts started out with.<\/p>\n

      Narrowing a pay gap makes it harder to close it!<\/strong><\/span><\/h4>\n

      In the graphic above, the same calculation of the probabilities of the 4 scenarios shows that for Engineers and Analysts, it will take an average of 8 rounds of recruitment to change the gender of an employee.\u00a0 For Managers & Administrators who needed 4 rounds to put themselves in the same position as Engineers and Analysts, that adds up to 12 rounds of recruitment that is needed to eliminate the gender pay gap.<\/p>\n

      Here is the key point that I think those who imagine closing the gender pay gap to be a relatively simple exercise are missing.\u00a0 When a role is very gender dominant, you can make rapid changes to the gender ratio with gender balanced recruitment simply because the employee that leaves is much more likely to be of a particular gender.\u00a0 But when a role is nearly but not quite gender balanced then the probability that the employee that leaves is of the gender you want to see more of is much higher.\u00a0 Consequently, the 4 scenarios become much more equal in their probabilities and it becomes largely a matter of luck as to which non-discriminatory employer ends up making progress in the desired direction.\u00a0 For many such employers they will end up regressing in the “wrong” direction and having to start all over again.\"\"<\/p>\n

      This is not an esoteric mathematical point, there is real data to back up this contention.\u00a0 In my post “Did the UK gender pay gap narrow in 2019?<\/em><\/a>“, I showed this chart for small employers (less than 500 employers) split into 3 groups based on the years they had reported data for.\u00a0 A point I didn’t comment on was that the Triangles (reported in 2018 & 2019 only) had the largest gender pay gap of the 3 groups in 2018 but made more progress on closing it in 2019 than the Squares (reported in all 3 years).\u00a0 Triangles narrowed their median pay gap by 1.6p from 14.7 pence in the pound against women to 13.1p whilst Squares only narrowed their median pay gap by 0.5p from 11 pence in the pound to 10.5p.\u00a0 The progress for Triangles is 3 times that of Squares which is a similar order of magnitude to the fact that it takes twice as many recruitment rounds to increase the number of Engineers by 1 women in 5050 STEM Ltd as it does for Managers.<\/p>\n

      Obviously one way 5050 STEM Ltd can speed up the process is to prevent female Engineers, say, from leaving in the first place.\u00a0 If the probability was reduced from 3\/8 to 1\/4 then the crosstab table for Engineers would be same as for Managers and the extra female Engineer can be expected after 4 rounds of recruitment rather than 8.\u00a0 I have seen plenty of employer activity aimed at female retention e.g. family friendly policies, part time working, but is it a good thing for female employees to be encouraged to remain at their existing employer?<\/p>\n

      Other HR professionals can answer this better than me but these days I think it is unusual for men to reach senior positions such as director or CEO without having changed employer at some point in their career.\u00a0 I am not sure if treating women differently in this regard is helpful to their career prospects.\u00a0 In any event, at an industry sector level, a gain for one employer is a loss for another employer.\u00a0 In sectors like airlines where the gender pay gap is driven almost entirely by the lack of female pilots across the industry, the challenge for the sector to increase the number of women becoming pilots rather than retaining or poaching existing female pilots.<\/p>\n

      Using Simulation to measure time to close a pay gap.<\/strong><\/span><\/h4>\n

      If you’re not convinced by my simple demonstration for 5050 STEM Ltd, then you should download my Recruitment Simulation Spreadsheet<\/strong><\/span><\/a>\u00a0and check it for yourself.\u00a0 In this spreadsheet, you can enter a variety of parameters including –<\/p>\n