Dear Tech People - Product - Tableau

This is Part II of a two-part post. Part I outlines the process of presenting the data using Tableau and Part II delves into insights from the analysis.

This dashboard was done up for a #VizforSocialGood project.

Discussion:

- In the dataset provided, apart from the 100 top tech companies, the breakdown for American population (gender/ race on White/ Asian/ Black/ Latinx) and Google was also included as benchmarks. Only the gender proportion of the American population (0.5) was reflected in the eventual dashboard as the companies had "Other" within the race categories and hence the population breakdown wasn't comparable. In addition, I thought using Google as a benchmark might be contestable and hence decided against referencing any company to it.

- From the scatterplot, we can see that most companies are below the 0.5 line, where in general the 100 top tech companies have an imbalanced gender ratio. Also, there is no distinct trend between the number of employees and the company's gender ratio.

- The average proportion of females in different sectors varies greatly. It is especially low within the infrastructure sector at 0.2568 i.e. only one in four employees is a female. Companies in the e-commerce sector see a higher average proportion of females than males at 0.5552. It is worth looking into explanations behind the differences in sectors, such as whether practices or the work environment were more female-unfriendly, or job nature/ motivation in certain sectors appeals to females more, or (of course,) a mixture of both.

Sectors with at least 10 companies were analysed. In total, the 100 companies span 16 sectors.

Average proportion of females

100 top tech companies: 0.3739

Analytics sector: 0.3167

E-commerce sector: 0.5552

Financial sector: 0.3356

Infrastructure sector: 0.2568

Productivity sector: 0.3652

- For some companies with higher proportion of females, this does not translate into higher proportion of females in leadership/ technical roles. For example, Everlane has 0% females in leadership positions. On the other hand, Cruise Automation has an overall female proportion of 0.2343 within its employees but females make up 44.44% of leadership positions.

The average proportion of females in leadership positions for the 100 top tech companies is 0.2205 while that in technical roles is 0.2049.

Top 10 Companies by Overall (O)/ Leadership (L)/ Technical (T) Female proportions

BuzzFeed (O)(L)(T)

Clover Health (O)(L)(T)

Everlane (O)(T)

Glossier (O)(L)(T)

Houzz (O)(T)

Omada Health (O)

Rent the Runway (O)(L)(T)

StitchFix (O)(L)(T)

23andMe (L)

Cruise Automation (L)

Grail (L)(T)

Quora (L)

US Digital Services (L)

Chariot (T)

Funding Circle (T)

- Looking at the average proportion of females in Top/ Bottom 10 companies by certain race representation, it seems that there might be a correlation between race and gender openness. It is interesting to note that the disparity in female proportion is small between Top 10 and Bottom 10 companies by Asian representation i.e. "Most Asian" and "Least Asian" companies. (This observation can be further validated by a correlation test.)

Average female proportion in Top 10 companies based on X proportion within employees

White: 0.2961

Asian: 0.3292

Black: 0.4451

Latinx: 0.3978

Average female proportion in Bottom 10 companies based on X proportion within employees

White: 0.4175

Asian: 0.3432

Black: 0.2566

Latinx: 0.3123

Further analysis can include exploring the correlation between race distribution (eg. White/ Asian/ Black/ Latinx) and gender ratio in leadership positions and technical fields.

- While not easily available within the visualization, with the dataset, we can also perform other analysis such as comparing race distributions across sectors/ leadership and technical roles.

Alternatively, the interactive Tableau dashboard can be viewed here.

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