Attracting and Retaining Women in IT Prof Liz Bacon BCS Past President (The Chartered Institute for IT) Past Chair CPHC (Council of Professors and Heads of Computing) Deputy Pro Vice-Chancellor, University of Greenwich, e.bacon@gre.ac.uk
Overview of Talk – Statistics – What puts women off – Why it matters – Solutions – Case study – change in school curriculum – Developing women leaders
UK Statistics e-Skills UK 2014 (2013 data) – “ Females consistently achieve higher grades than males in IT-related subjects” – “They fill just 16% of IT & Telecoms professional occupations” – a slight decline! – Only 11% of information security professionals are women (ISC)2 – Across all subjects in Higher Education in 2013, females accounted for 57% of UK domiciled applicants and 55% of acceptances. – Across STEM subjects, applicants = 34%, acceptances = 35% – Computer Sciences applicants = 12%, acceptances = 13% – Engineering applicants = 11%, acceptances = 12% – Gender imbalance in both the IT industry and in IT occupations is an issue to all EU15 nations – Female representation in these industries/occupations is lower in the UK than the EU 15 average – 16% pay gap (£120 / week less)
USA (TechRepublic - Lyndsey Gilpin 2014) – In the mid-1980s, 37% of computer science majors were women; in 2012, it was 18% – 57% of bachelor's degrees earned by women, 12% of computer science degrees were awarded to females
Other Countries • In 1987 more than 50% of application/analyst programmers and system analyst/designers in Singapore were female, and the majority of graduates from computer courses were female (Galpin) • Why? Government promotion, perception of good careers, preference for computing vs engineering, gender-neutral exposure, assistance with domestic responsibilities (Uden) • Many countries around the world (Middle East, some in Africa and Far East where women dominate in IT) 5
Effect of culture and society • Girl only schooling • Compulsory maths and science at secondary school • Societal perceptions of a discipline • Class issues 6
Leaky Pipeline Early years 11-16 16-18 Workforce University <11 A fall in numbers at every stage of education and employment! UK - Girls take 51% of all GCSEs (age 16) and 44% of IT GCSEs – but only 6.5% of computer A-levels (age 18) 7
Leaky pipeline - Scotland 2008 data, RSE Report: Tapping all our Talents
Attracting Women into Computing (UK – not alone….) • Often perceived to be a western culture issue • Gender bias early on at home and at school • School curriculum • Lack of understanding by careers advisors • Uninspiring teachers with no real world experience • School league tables – pressure not to study IT • Male dominated • Male culture in workplace • Skills date quickly if take time out for family – harder to get back in and if do, often not technical roles • Lack of Role models at all levels • Pay differences • Media images of IT professionals as nerds etc.
Nerd / Geek – what do they look like? • Unattractive • Glasses • Poor teeth • Maybe overweight • Usually male • Someone who doesn’t have a girlfriend • Socially awkward • Hair in a ponytail • Scandals • Can be girls • Or even cats! 10
What is a Nerd? (wikipedia) • Overly intellectual • Obsessive • Socially impaired • May spend inordinate amounts of time on unpopular or obscure technical or fiction activities, to the exclusion of more mainstream activities • Shy, quirky, and unattractive • Often on autistic spectrum (~1% of the population) • Good news SAP (2013): • “ Some people with the condition are highly intelligent and have a keen attention to detail.” • Recruiting autistic people - said its productivity had increased as a result of their efforts 11
Recruitment • “Old boys network” tends to hire people like them – women will bring other women! • Poor project management requires 24/7 to save a project: • Anecdotal evidence in hiring bias • Women tend to have primary responsibility for the household – senior women more likely to have partner with primary responsibility (NetworkWorld 2010). • Women often judged on performance, men on potential (McKinsey 2012) • 'Ladder Pullers'. Women who climb the ladder and pull it up after them.
Pay – all fields • USA – all jobs - women earn 77 cents Vs men earn one dollar • Adjust for age, experience or industry – 4% pay gap • 9/10 most remunerative majors were dominated by men • Women pause for families then seek jobs with more flexible hours but lower pay and choose careers that tend to have lower pay • Pay negotiation - University of Texas study – women asked for 7K less for themselves, if for friend / colleague, no difference!
Why does it matter? Common Reactions: • Cherry picked stats – they are still true! • Can we just recognise women don’t like IT? • Can we stop trying to force women to do something they don’t want to do? • Get over it, people just do what they want! • No need to require a profession to be equally split. There is no male push in nursing or teaching. • Gender of users does not imply gender of developers (Women in western countries use the internet 17% more than their male counterparts - Intel)
It does matter! • Shortage of IT skills getting worse! • On average women have higher social intelligence • “It is notable that performance increased significantly once a certain critical mass is attained: namely, at least three women on management committees for an average membership of 10 people. Below this threshold, no significant difference is observed.” (McKinsey 2007). • Increasing impact of technology on society means women need to understand and influence their future. • Important for women to make an informed choice.
Shortages 16
Demand: ICT Workforce Development in Europe 2012 – 2015 - 2020 Management, business 44.2% architecture and analysis 15.5% 8.5% ICT practioners - 15.9% professional level 10.1% 3.7% ICT practitioners - associate/ -16.8% -11.8% technician level 2020 -3.9% Long term trend in IT 2015 9.3% market is growth in jobs 2012 Total and high youth 3.2% compared to 2011 1.8% unemployment in Europe Source: Gareis, K., Hüsing, T., Bludova, I., Schulz, C., Birov, S., Korte, W.B.: e-Skills: Monitoring and Benchmarking Policies and Partnerships in Europe (Final Report for the European Commission, January 2014) 17
Predicted Vacancies • Europe: At least 509,000 vacancies predicted for 2015 - UK (25%) + Germany (24%) • Europe: By 2020, 900,000 vacancies UK (27%) + Germany (17%) • Since 2007, market has annually absorbed up to twice as many new workers (growth plus replacement) as ICT/CS graduates available • Global market for IT professionals having significant effect on some countries
Workforce – skills shortage • “By 2020, the African economy is projected to add 220 million people to the workforce, creating a continent wide labour force of more than 500 million ” (Brent Wilton - International Organisation of Employers, Eroke, 2013). • The ability of Africa to engage in the ICT industry is often understated, and is likely to change. (European Commission e-skills report 2014) • Survey of 70 European CIOs/senior IT managers - Likely Offshored: coding, software testing and ICT support. • “Labour market institutions and policies have not kept up to date with the changes in business practices and technology that are defining what kind of jobs will be created and where they will be created” (McKinsey). 19
Cybersecurity Verizon report – 92% of 100,000 incidents analysed over 10 years can be described by 9 basic patterns On average, top 3 patterns cover 72% of incidents Lack of available entry – level education or roles
e-Leadership • As organizations rely more on ICT, they are demanding e-leaders who are both business and ICT savvy. • An e-leader motivates and guides multi-disciplinary professionals to use ICT to creatively exploit digital opportunities for business innovation and stakeholder value • Ability to exploit opportunities provided by ICT and new ways of conducting business • Skills: – Leadership – Business – IT – Entrepreneur – Imagination 21
Skills needs of the future Average World Unemployment 2013 100.0% 90.0% 80.0% 70.0% 60.0% Unemployed 50.0% 86.9% Employed 40.0% Most countries: 30.0% 20.0% labour shortage 10.0% by 2030 13.1% 0.0% Unemployed Employed 2013: 201.8 million unemployed 2014 another 4.2 million unemployed 22
Solutions? • Change in school curriculum – better understanding of IT careers • Ensure careers advisers don’t steer to conventions • Unconscious bias training • Promotion based on skills not time served • Role models at all levels • Given senior-level technical women are much more likely to have a partner with primary responsibility for the household/children (NetworkWorld): – Flexible working hours – Flexible working location – Support for childcare services – Job sharing – Training for return to work
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