Women in STEMTechnology, career pathways and the gender pay gapJulie Mercer, Harvey Lewis | 24 October 2016
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Julie Mercer
• Julie is the Industry Leader for Education at Deloitte both for the UK and globally, working with government, private and third sector organisations involved in designing, regulating, delivering or supporting the education system.
• +44 20 7007 8292
Women in STEM
Presenters
Harvey Lewis
• Harvey is a director in the technology consulting practice and the UK lead for cognitive computing.
• +44 20 7303 6805
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Women in STEM: a data analysis
4
Setting the scene
According to the Women’s Engineering Society:
• Only 9% of the UK’s engineering workforce is female, and only 6% of all registered engineers and technicians are women
• The UK has the lowest percentage of female engineering professionals in Europe, at less than 10%, while Latvia, Bulgaria and Cyprus lead with nearly 30%
• 14% of engineering and technology undergraduates in the UK are female
• The proportion of young women studying engineering and physics has remained virtually static since 2012
• In 2013/14, women accounted for only 3.8% of Engineering apprenticeship starts and 1.7% of Construction Skills starts
• Only around 20% of A Level physics students are girls and this has not changed in 25 years
• There is now very little gender difference in take up of and achievement in core STEM GCSE subjects
• 64% of engineering employers say a shortage of engineers in the UK is a threat to their business. 32% of companies across sectors currently have difficulties recruiting experienced STEM staff, and 20% find it difficult to recruit entrants to STEM
• The UK needs to significantly increase the number of people with engineering skills. In 2014, one report put the annual shortfall of STEM skills at 40,000. In 2015, the annual shortfall of the right engineering skills is 55,000 We need to double, at least, the number of UK based university engineering students
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Women vs men
The proportion of female vs male students taking STEM subjects at various stages of their education remain approximately the same
48.2%51.8%
41.0%59.0%
53.2%46.8%
TOTAL: 2,330,000
TOTAL: 317,000
TOTAL: 150,000
Percentage of students who are male Percentage of students who are female
GCSE
A-Level
Degree
Note: STEM subjects at GCSE and A-Level include Mathematics, Biology, Chemistry, Physics, Economics, Statistics, Further Mathematics, Design & Technology, ICT, Computing, All Sciences. STEM subjects at degree level include Medicine & dentistry, Subjects allied to medicine, Biological sciences, Veterinary science, Agriculture & related subjects, Physical sciences, Mathematical sciences, Computer science, Engineering & technology, and Architecture, building and planning (STEM subjects as defined by the Parliamentary Science and Technology Committee)Sources: 2016 GCSE and A-Level results from UK Joint Council for Qualifications, Higher Education data from the 2014-15 Destination of Leavers from Higher Education Survey
6
Women vs men
How does this compare with other European countries?
Note: STEM subjects in EF4,EF5, EF6 and EF7 chosen to best match UK equivalents.Source: Eurostat, Deloitte analysis
0
10
20
30
40
50
60
70
80
90
100
Percen
tag
e
Proportion of women vs men studying STEM subjects at tertiary level Percentage_Women
Percentage_Men
7
Women vs men
But significant differences emerge when we consider individual STEM subjects, such as Computing/Computer Science…
20.6%79.4%
14.3%85.7%
16.8%83.2%
TOTAL: 63,000
TOTAL: 7,000
TOTAL: 12,900
Percentage of students who are male Percentage of students who are female
Sources: 2016 GCSE and A-Level Computing results from UK Joint Council for Qualifications, Computer Science Higher Education data from the 2014-15 Destination of Leavers from Higher Education Survey
GCSE
A-Level
Degree
8
Women vs men
…and across all STEM subject areas at degree-level
80%20%
Percentage of students who are male Percentage of students who are female
Subjects allied to medicine
76%24%Veterinary science
62%38%Agriculture & related subjects
61%39%Biologicalsciences
58%42%Medicine & dentistry
39%61%
39%61%
Physicalsciences
Mathematicalsciences
32%68%Architecture, building & planning
17%83%Computer science
14%86%Engineering & technology
Note: STEM subjects as defined by the Parliamentary Science and Technology Committee.Source: 2014-15 Destination of Leavers from Higher Education Survey
9
Women vs men
How does this compare with other European countries?
Note: STEM subjects in EF48 (ISCED97).Source: Eurostat, Deloitte analysis
0
10
20
30
40
50
60
70
80
90
100
Percen
tag
eProportion of women vs men studying Computing at tertiary level Percentage_Women
Percentage_Men
10
Women vs men
How does this compare with other European countries?
Note: STEM subjects in EF72 (ISCED97).Source: Eurostat, Deloitte analysis
0
10
20
30
40
50
60
70
80
90
100
Percen
tag
e
Proportion of women vs men studying Health at tertiary level Percentage_Women
Percentage_Men
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Women vs men
Women outperform men in STEM subjects at every level of education
67.4%63.1%
77.3%75.6%
61.8%56.8%
Percentage of students who are male Percentage of students who are female
GCSE (A* - C)
A-Level (A* - C)
Degree (With honours)
Sources: 2016 GCSE and A-Level results from UK Joint Council for Qualifications, Higher Education data from the 2014-15 Destination of Leavers from Higher Education Survey
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Women vs men
But very few women with STEM degrees go on to work in STEM occupations
8%29%
50%42%
Percentage of students who are male Percentage of students who are female
STEM occupations (not incl. occupations in medicine or dentistry)
STEM occupations (incl. occupations in medicine, pharmacy and dentistry)
Note: STEM occupations were based on SOC2010 occupational classifications and descriptionsSource: 2014-15 Destination of Leavers from Higher Education Survey, employment six months after graduation
13
Women vs men
Where do all the men go?
Note: STEM occupations were based on SOC2010 occupational classifications and descriptionsSource: 2014-15 Destination of Leavers from Higher Education Survey, employment six months after graduation, all those for whom salary information was known
All STEM subjects
7.0
%
6.2
% Medical practitioners
4.2
%
Programmers and software development professionals
Nurses
3.2
%Mechanical engineers
2.5%
Design and development engineers
2.0
%
Business & related associate professionals n.e.c.
1.9
%
Pharmacists
1.7
%
Information technology and telecommunications professionals n.e.c.
Quantity surveyors
Architects
University researchers, unspecified discipline
3.2
%Civil engineers
3.1
%
Engineering professionals n.e.c.
1.7
%
Architectural and town planning technicians
IT business analysts, architects and systems designers
14
Women vs men
Where do all the women go?
Note: STEM occupations were based on SOC2010 occupational classifications and descriptionsSource: 2014-15 Destination of Leavers from Higher Education Survey, employment six months after graduation, all those for whom salary information was known
All STEM subjects
28.2%
6.1
% Medical practitioners
3.1
%
Nurses
Pharmacists
2.4
% Midwives
1.9
%Occupational therapists
1.9
%
Physiotherapists1.6
%
Medical radiographers
1.5
%
Business & related associate professionals n.e.c.
Health professionals n.e.c.
Laboratory technicians
Biochemists, medical scientists
Dental practitioners
Other administrative occupations n.e.c.
Welfare & housing associate professionals n.e.c.
Therapy professionals n.e.c.
15
Men are paid more than women, even in top STEM destinations
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
Pay gap – top occupations for female STEM graduates
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
Pay gap – top occupations for male STEM graduates
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Routine and repetitive tasks are increasingly automatable
Cognitive Manual
No
n-r
ou
tin
eR
ou
tin
e
IMPACT OF TECHNOLOGY:STRONG COMPLEMENTARITIES
IMPACT OF TECHNOLOGY:LIMITED OPPORTUNITIES FOR SUBSTITUTION, SOME COMPLEMENTARITIES
IMPACT OF TECHNOLOGY:SIGNIFICANT SUBSTITUTION
IMPACT OF TECHNOLOGY:SIGNIFICANT SUBSTITUTION
E.g. Management consultants and business analysts
E.g. Care workers and home carers
E.g. Metal making and treating process operatives
E.g. Bank and post office clerks
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The future of employment looks bleak for many occupations
As forecast by Frey and Osborne in 2013
18
Automation will affect different occupations to different degrees
Potential impact on UK occupations in the next 10-20 years
0
10
20
30
40
50
60
70
80
90
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Em
plo
ym
en
t (T
ho
usan
ds)
Probability of Computerisation
Managers directors and senior officials Professional occupations
Associate professional and technical occupations Administrative and secretarial occupations
Skilled trades occupations Caring leisure and other service occupations
Sales and customer service occupations Process plant and machine operatives
Elementary occupations
Low probability of automation Strong complementarities
Medium probability of automation
Some complementarities
High probability of automation
Strong substitutive effects
Source: ONS, Frey and Osborne, Deloitte
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We can already sense the shifts
Change in employment in UK occupations, 2001-15
-10
-5
0
5
10
15
20
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Ch
an
ge i
n e
mp
loym
en
t (T
ho
usan
ds)
Probability of Computerisation
Managers directors and senior officials Professional occupations
Associate professional and technical occupations Administrative and secretarial occupations
Skilled trades occupations Caring leisure and other service occupations
Sales and customer service occupations Process plant and machine operatives
Elementary occupations
Source: ONS, Frey and Osborne, Deloitte
Low probability of automation Strong complementarities
Medium probability of automation
Some complementarities
High probability of automation
Strong substitutive effects
22
What skills are needed by workers to help them remain employed?
We asked 100 London-based businesses in 2014
4%
5%
5%
6%
8%
9%
9%
10%
13%
15%
16%
Cultural know-how…
Persuasiveness
Social perceptiveness
Processing, support and clerical …
Professional qualifications
Negotiation
Problem solving
Entrepreneurship
Creativity
Management
Digital know-how
The skills increasingly required by businesses and public sector organisations
(weighted score)
Source: Deloitte survey of 100 London based businesses, 2014
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Now, we have built 366 separate occupation profiles for the UK, using 120 different skills, knowledge and abilities attributes…
Abilities
Basic skills
Cross-functional
skills
Knowledge
Cognitive abilities
Sensory abilities
Psychomotor abilities
Physical abilities
Content skills Process skills
Social skills
Complex problem-
solving skills
Systems skills
Technical skills
Resource
management skills
Business and
management
Manufacturing and
production
Mathematics and
science
Health services
Education and
training
Arts and humanities
Law and public
safety
Engineering and
technology
Transportation
Communications
Web design & development professional
25
We’ve found that cognitive skills and abilities, and social skills are most important right now
Most important attributes Least important attributes
1. Customer and personal service knowledge 111. Food production knowledge
2. Oral comprehension (ability) 112. Repairing skills
3. Oral expression (ability) 113. Fine arts knowledge
4. English language knowledge 114. Glare sensitivity (ability)
5. Active listening skills 115. Sound localisation (ability)
6. Written comprehension (ability) 116. Peripheral vision (ability)
7. Problem sensitivity (ability) 117. Night vision (ability)
8. Speaking skills 118. Explosive strength (ability)
9. Near-vision (ability) 119. Installation skills
10. Critical thinking skills 120. Dynamic flexibility (ability)
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But the relative importance of these talents is changing…
-15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0%
pyschomotor_abilities
physical_abilities
technical_skills
manufacturing_and_production_knowledge
sensory_abilities
engineering_and_technology_knowledge
transportation_knowledge
cognitive_abilities
business_and_management_knowledge
content_skills
complex_problem_solving_skills
law_and_public_safety_knowledge
resource_management_skills
social_skills
process_skills
communications_knowledge
systems_skills
mathematics_and_science_knowledge
education_and_training_knowledge
arts_and_humanities_knowledge
health_services_knowledge
Percentage change in attribute importance 2001-30 (forecast)
-6
-4
-2
0
2
4
6
8
10
12
14
16
Perc
enta
ge c
hange
Percentage change in knowledge
business_and_management_knowledge
manufacturing_and_production_knowledge
engineering_and_technology_knowledge
mathematics_and_science_knowledge
health_services_knowledge
education_and_training_knowledge
arts_and_humanities_knowledge
law_and_public_safety_knowledge
communications_knowledge
transportation_knowledge
-6
-4
-2
0
2
4
6
8
Perc
enta
ge c
hange
Percentage change in skills
content_skills process_skills
social_skills complex_problem_solving_skills
technical_skills systems_skills
resource_management_skills
-10
-8
-6
-4
-2
0
2
4
Perc
enta
ge c
hange
Percentage change in abilities
cognitive_abilities pyschomotor_abilities
physical_abilities sensory_abilities
27
Some attributes have a positive effect on employment
-25
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Job importance decile
Process skills
-30
-20
-10
0
10
20
30
1 2 3 4 5 6 7 8 9 10
Job importance decile
Social skills
-20
-15
-10
-5
0
5
10
15
20
25
30
35
1 2 3 4 5 6 7 8 9 10
Job importance decile
Complex problem-solving skills
-20
-10
0
10
20
30
40
1 2 3 4 5 6 7 8 9 10
Job importance decile
Systems skills
High risk of automation
Medium risk of automation
Low risk of automation
Most important
Least important
Most important
Least important
Most important
Least important
Most important
Least important
Perc
enta
ge c
hange in
em
plo
ym
ent share
Perc
enta
ge c
hange in
em
plo
ym
ent share
Perc
enta
ge c
hange in
em
plo
ym
ent share
Perc
enta
ge c
hange in
em
plo
ym
ent share
28
While others have a negative effect
-15
-10
-5
0
5
10
15
20
1 2 3 4 5 6 7 8 9 10
Job importance decile
Sensory abilities
-30
-25
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Job importance decile
Psychomotor abilities
-20
-15
-10
-5
0
5
10
15
1 2 3 4 5 6 7 8 9 10
Job importance decile
Physical abilities
High risk of automation
Medium risk of automation
Low risk of automation
Most important
Least important
Most important
Least important
Most important
Least important
Most important
Least important
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
Job importance decile
Technical skills
Perc
enta
ge c
hange in
em
plo
ym
ent share
Perc
enta
ge c
hange in
em
plo
ym
ent share
Perc
enta
ge c
hange in
em
plo
ym
ent share
Perc
enta
ge c
hange in
em
plo
ym
ent share
29
Women vs men
Differences in the nature of employment in the UK
1.0m 0.5m 0.0m
Number of people employed
1.0m 0.5m 0.0m
Number of people employed
Men WomenH
igh
Low
Import
ance o
f cognitiv
e a
nd s
ocia
l skills
HighLow
Importance of technical skills
Hig
hLow
Import
ance o
f cognitiv
e a
nd s
ocia
l skills
HighLow
Importance of technical skills
30
Summary of our analysis
According to our analysis
• Girls/women outperform boys/men at every level of STEM education
• Although similar numbers of girls and boys/women and men study STEM-related subjects, overall, very few women enter STEM occupations except in health and social care
• There are substantial differences in the proportion of women vs men taking different STEM subjects
• As a consequence, women with STEM qualifications are more likely than men to be working in low-skilled, low-paid occupations
• Even where men and women are working in the same occupations, men are typically paid more than women
• Across the UK’s workforce, women are more likely than men to be working in jobs that do not require technical skills
Challenges
• How can more women be persuaded to study non-medicine/biology-related STEM subjects?
• How can more women be persuaded to enter STEM occupations outside healthcare?
31
What can we do to change the outlook for women in STEM?
32
Unconscious bias and role models
I hadn’t been aware that there were doors closed to me until I started knocking on them. I went to an all-girls school. There were 75 chemistry majors…most were going to teach … When I got out and they didn’t want women in the laboratory, it was a shock . . . we’ve never had a woman in the laboratory before, and we think you’d be a distracting influence.’
33
The role of schools, university, business and society
In the 2015 nominee pool, 83% were male and 17% were female compared to ACS membership demographics of 71% male and 29% female.”
American Chemistry Society
• When do you start
• How we teach
• Can we describe the breadth and depth of STEM opportunities
• Careers advice and guidance
• Who are the role models and how are they profiled?
• And when do we stop
• What we teach
• Business mentors, profiling and engagement with schools and colleges
• Stemnet mentors 40% female and most under 35
• L'Oréal science awards
34
What can we do?
Like most organisations Deloitte recognised we had a problem and a role to play in addressing women in stem and in our business
Return to work
programme
Flexible working
environment
Blind applications
Monitoring the
numbers
TeachFirstand school mentoring
Parental leave
Respect and Inclusion
Calling it out
35
Further resources
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Further resources
Forthcoming publications
• Hidden talents: The search for tomorrow’s business stars
• Veterans Work: The benefits to UK businesses of employing military veterans
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