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: