Background
Despite its potential benefits, valuing diversity doesn’t come naturally
(Kirton, 2003; Galinsky et al., 2015). This policy comes in to aid the
prevention of future mistakes related to diversity such as sexual
harassment, poor handling and retaliation over sexual harassment
complaints, pay gaps, overarching inequal statistics, and gender
discrimination. The policy also aims to foster organizational strategic
goals by maximizing the attraction and retention of highly skilled
talent in an increasingly demanding environment.
The Information and Communication Technology sector (ICT) has been
characterized by different facets of gender inequality (Clayton, Hellen,
and Nielsen, 2009; Hall et al, 2019; Lewis, Lang, and McKay, 2007; Ruiz
Ben, 2007; Tans, 2019). Female professionals have been internationally
underrepresented despite the chronic global shortage in ICT talent (Ruiz
Ben, 2007; Clayton, Hellen and Nielsen, 2009; Kudakwashe, 2015).
Unfortunately, at Uber, only 33% of our workforce is female with that
percentage shrinking to 22% in leadership positions (Steinmetz and
Vella, 2017). It’s been noted that this type of demographic composition
may affect individual’s workplace experience of social identity and can
make them feel unwelcome (Ely, 1994).
Social identity as a cognitive social psychological concept has been
applied to organizations to illustrate the potential clashes between the
person’s position in the social space outside of work and inside of it
(Ely, 1994; Ashforth & Mael, 1989). Gender social identity and work
identity are distinct psychological constructs that have been shown to
be in conflict when the work is gender-specifically dominated such as
the case in our industry, where females perceive that conflict but not
males (Veldman, 2017). This results in lower team identification, more
burn-out, and perceived under-performance, however, with the right
support from male and female team members and leaders, these problems
can be mitigated (Veldman, 2017).
Social identity theory can also be used to understand the resulting
overall work-gender identity experienced by the staff such as the
identity of “female-technician”. This new central identity is often
threatened in gendered workplaces which partially explains the higher
turn-over rate in female science, technology, engineering and math
(STEM) fields (Hall et al., 2018). This threat is theorized to be one of
the main culprits behind organizations not reaping the benefits of
diversity in terms of innovation, decision quality and superior
information processing (van Knippenberg, De Dreu, and Homan, 2004). The
threat to social identity is not always salient by outward aggressive or
harassment behavior, it’s also been noted to exist in a subtle way in
day-to-day workplace conversations among employees of different
perceived gender identities with women at a disadvantage in STEM (Hall
et al., 2018). Moreover, it’s noted that in-group/out-group prejudice is
partially due to the need for positive evaluation of the self as part of
the in-group that is superior to the out-group (Tajfel and Turner,
2004), thus self-esteem and mental health care need to be central to the
conversation (Pettigrew and Tropp, 2006). Overall, the situation
requires a careful revision of the organizational culture and attitudes
rather than only focusing on obvious instances of outward harassment and
discrimination (Sharma, 2016).
The current state of affairs can be attributed to a multitude of factors
affecting the ICT sector. Research showed that profession-specific
gender-roles develop early in childhood and can evolve into negative
stereotypes directed towards persons who do not conform with these roles
(Clayton, Hellen and Nielsen, 2009). STEM in general and tech in
specific has been the subject of such stereotyping (assisted by the
media) with the stereotype of the socially isolated male software
developer being the norm, thusly females could shy away from tech to
avoid contradicting the social norm whereas, males can bare the grunt of
social isolation (Clayton, Hellen and Nielsen, 2009). The perceived
status of the occupation’s high salary range and high level of education
have also contributed to narrowing the participation of women in the
industry due to the clash with social norms related to female-gendered
professions and participation in society (Clayton, Hellen and Nielsen,
2009). The toll on female workers associated with the relationship
between their gender and profession manifested at times with lower
feelings of self-efficacy, isolation, sexual harassment, and
belittlement of their knowledge and competence especially with working
mothers and female senior staff. (Clayton, Hellen and Nielsen, 2009;
Multhaup and Williams, 2017; Lewis, Lang and McKay, 2007; Stamarski and
Hing, 2015). Other results like pay gap and promotion gap are also
present among male and female software engineers in the United States
(Dattero & Quan, 2005).
Assigning value to diversity is of great strategic business importance
to Uber due to its contribution to employee retention (WHO, 2001; Hall
and Parker, 1993). Uber has very little physical assets, contracts
drivers all over the world, and is often faced with volatile markets due
to the rapidly changing nature of the e-hailing business, thusly meaning
that people are literally Uber’s biggest asset (Jordan, 2017). Research
shows that a strong ICT company aspires to have a strong talent
attraction and retention capability as demand for software developers
continues to climb while diversity management is viewed to be a
potential factor in organizational attractiveness to new recruits
(Kudakwashe, 2015; Williams and Bauer, 1994). The US Bureau of Labor
Statistics projects a 21% increase in the demand for software
developers with no requirement for previous experience or on-the-job
training (Bureau of Labor Statistics, 2020). Governments have even
created special priority attraction schemes for talented software
developers (Cerna and Chou, 2013).
The policy takes a proactive transformative stance on managing
diversity, which means that no measures forcing equality of outcome
shall be maintained since systematic review showed that this type of
Affirmative Action style is slower in achieving results in the United
States following the Johnson act of 1965 and until recently (Kalev,
Dobbin and Kelly, 2006), neither will this policy only be enforced only
when conflict arises (Syed and Ozbligin, 2015; Kirton, 2003). The policy
will however favor the use of non-binding percentage goals (no reward or
punishment for achieving the goals) (Kalev, Dobbin and Kelly, 2006),
centralizing responsibility for diversity with the executives (Kalev,
Dobbin and Kelly, 2006), and the use of transparency in data (Grosser
and Moon, 2008), public objective criteria of appraisal (Kalev, Dobbin
and Kelly, 2006;WHO, 2001; Sharma, 2016; Stamarski and Hing, 2015),
inter-firm cooperation (WHO, 2001), and mentoring and training (European
Institute for Gender Equality, 2016; Jones, 2017; Sosik and Goshalk,
2000; Grant-kels, 2018). The objectives are split into short-term and
long-term objectives: