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Addressing Gender Representation Gap in Finance: A Data-driven Case Study

This case study highlights the importance of data in people management and explores the issue of increasing the number of women in management positions at Finance Canada. It includes a literature review, diagnostic plan, and early findings from HR data. The study aims to validate themes such as implicit bias, caregiving responsibilities, lack of networks/mentors, and imposter syndrome within the department.

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Addressing Gender Representation Gap in Finance: A Data-driven Case Study

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  1. FIN Builds: A case study on the importance of data in people management Presentation to the Certificate Program in Leading People for Results November 16, 2018

  2. The Issue at Finance Canada: how to increase the number of women in management positions Yesterday … Tomorrow …

  3. Diagnostic: Literature Review and Process Literature review highlights several factors that contribute to the relatively lower representation of women in leadership positions: • General stereotyping and implicit bias. • Caregiving responsibilities in tension with professional expectations. • Lack of effective networks and mentors. • The imposter syndrome. How will we validate the relevance of these themes within the Department? • Candid discussions. • Detailed analysis of HR data. • Possible survey (to gain a broader set of data on more targeted questions, assess factors that are most significant to employees).

  4. Diagnostic Plan and Progress: Departmental HR Data Available HR data includes: Limitations to Data: • There are some limitations as to what HR data is able to demonstrate: • Lack of longitudinal data that is disaggregated by gender. • Data collection may not have focused on issues related to advancement – i.e.: have we been asking the right questions as to why women may choose not to advance at the same rates of men / or not be chosen for advancement at the same rates as men. • Small sample size of exit interviews. • Pilot project should be targeted at addressing findings. To the extent that there are data gaps, this may be challenging. • PSES results. • Parity levels at senior EC/EX levels. • Advancement: external vs internal hires, length of stay. • Parental leave / alternative work arrangements use by gender (to some extent, although informal arrangements difficult to track). • University Recruitment program statistics.

  5. Early Findings from HR Data Raw data: • Women are underrepresented in the EC and EX groups, yet are overrepresented in the AS and PE groups (72% and 88% respectively), jobs typically considered feminine. 2017-2018 PSES Results: • Women are less satisfied than men with resolution of interpersonal problems at work (62% agreement vs. 82% agreement). • Women are less satisfied with resolution of instances of discrimination at work (55% agreement vs. 65% agreement). 2017-2018 Exit Interviews: • Of those leaving Finance, 67% of women vs. 43% of men cited an equivalent position elsewhere in the federal government. • Women responded less favourably than men to 6/8 indicators around job satisfaction. • Women and men differed in their views around management creating a fair and equitable environment (women responded on average that they disagreed that management created a fair and equitable work place, whereas men agreed with that statement). • Women responded less favourably than men to all of the indicators around learning and career development, with regard to receiving adequate training and development opportunities, and whether the promotion system is fair and equitable.

  6. Takeaways • Evidence that there is a representation gap among men and women in senior positions, although more work needs to be undertaken to understand causes of this underrepresentation. • Hypothesis that strong formal policies against gender discrimination and harassment mean that some factors in the literature review are not as relevant at the Department • However, this may lead to potential hypotheses worth exploring: • How does the organizational culture at Finance impact gender representation; how does it compare to other relevant departments? • Can we substantiate and better understand the data that suggests women more than men leave Finance for equivalent positions elsewhere in the government? • To what extent to the Departmental networks and mentorships actually contribute to employee advancement? • How do we target data collection to the issue of advancement?

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