At Thought Machine, we calculate our gender pay gap based on UK Government guidance:
The gender pay gap is the difference between the average (mean or median) earnings of men and women across a workforce.
Companies that employ more than 250 people (like Thought Machine) are legally required to publish a snapshot of their gender pay gap each year, using data from the year prior. The following data is a snapshot of our gender pay gap position as of April 2022.
The data is not a measure of pay equality (it is a legal requirement for men and women performing equal work to receive equal pay). By looking at the data in aggregate, we see a picture of the overall differences in pay between men and women in the business. This data also reveals the kinds of roles held by men and women – and which gender is more or less represented in different salary bands.
It is an opportunity for us at Thought Machine to observe the disparity in pay between men and women across the business and ask ourselves the question as to why those differences exist.
We have collected and analysed data with regard to:
April 2022 hourly pay gap
As of April 2022, there was a mean (average) difference of 19.7% in the hourly pay received by men and women. This means that, on average, men are paid 19.7% more per hour than women in our company. We are focusing our efforts towards improving this, with a commitment to robust, proactive recruitment and D&I initiatives that will also aid us in this area.
A mean calculation takes all the available data points (i.e., every person’s hourly pay amount) and divides that number by the number of people in the set (i.e. the total number of employees counted). Data like this can sometimes be skewed by outliers – those who earn the highest and lowest amounts in the business – therefore, we also calculate the median difference.
The median difference picks the data point precisely in the middle of the complete list of everyone’s hourly pay – for men and women – and we calculate the percentage difference between those two numbers.
In our data set, the median difference shows that hourly pay was 18.2% higher for men than for women. This data reveals a bias towards men holding more senior positions and, therefore, higher-paid roles in the business. We are committed to re-establishing our talent and succession planning tools to ensure improved gender equity in recruitment and promotion at senior level and across all levels at Thought Machine.
April 2022 bonus pay gaps
Bonuses are not a standard feature of our compensation structure. However, we offer alternative reward incentives such as commission to our sales team and referral fees to anyone in the company who successfully refers a candidate who joins Thought Machine. Commission and referral fee data must be combined to calculate our bonus pay gap figures.
Percentage of employees who received bonus pay
As we have more men than women in the organisation, we expect to see men being those who more frequently receive our forms of bonus pay. This is heightened by the fact that the sales team was predominantly male.
We have calculated that 33% of bonus pay went towards men, while 8% went towards women.
Difference in bonus pay (commission and referral fees combined)
Our calculations show an 89% difference in bonus pay between men and women. This gap results from the commission paid on sales is larger than the amount paid for referrals – further compounded by the largely male representation in the sales team.
The median numbers – the numbers in the middle of the set – are zero. This is due to referral payments being at the middle of the set of bonus payment data – and referral fees are a fixed amount in the business.
While we continuously strive toward sourcing and recruiting more female members across the business, we are conscious of the disparity between those who receive commission pay and those who do not.
We have already initiated the steps to rectify the gender imbalance within the sales team. Looking at our recruitment data for the past calendar year, we can confirm that 13% of hires made into the sales team were women. Though progress is slow – we are working towards better representing women across the business at senior levels and within the commercial department.
April 2022 pay figures and quartiles
Our April 2022 pay and quartile data reveal the imbalance we have at the highest levels of the organisation. However, we intend to address this.
The upper quartile of our business, the highest-paid segment of Thought Machine, comprises 88.2% men and 11.8% women. In the upper-middle quartile, men make up 85% of this group and women 15%, a 2.5% increase from the previous year for women. One quartile below, in the lower middle quartile, women make up 21.5% of this segment, while men make up 78.5%. Women comprise 38.7% of this segment in the lower quartile, while men comprise 61.3%.
We have a way to go before we achieve the parity we expect. However, we have several initiatives running and others to be launched soon, which engage with female talent and which we believe have positively impacted Thought Machine’s gender balance since May 2022 (after this data was captured). These initiatives will help us become more visible to relevant female talent in the market and find new ways to hire diverse talent. We are also running several initiatives to better support the women currently working at the company.
Improved gender-balanced talent pipelines
We continue to find ways to improve and grow a diverse workforce and talent pipeline. We are sourcing more sponsorship roles with organisations which promote and champion diversity. These include She Can Code, which helps women enter, remain and excel in the tech industry. We are partnering with diverse educational establishments such as OxWEST (Oxford Women in Technology) – one of the largest student-led societies at the University of Oxford. We have also partnered with DocSoc, part of Imperial University, which runs multiple events throughout the year, including several hackathons. These partnerships give us direct access to diverse talent, an opportunity to promote working at Thought Machine and go beyond traditional recruitment pools and channels.
We set annual gender-balanced recruitment targets and ensure a gender-diverse interview panel where possible. We continue to use Textio (a tool for writing gender-neutral job descriptions and adverts) in our recruitment campaigns to eliminate loaded, biassed, and exclusive language in our hiring material.
We are making steady strides in this area. In 2020, our target was to ensure that of all of our new hires, women would account for at least 22%, which we achieved. Our 2021 recruitment target was 30% female hires, and we reached 36%. In 2022, we again achieved our recruitment target of 33% female hires. We are proud to have hired a number of senior women into the business – including new HR, client services, and learning and development leaders. We have also promoted a number of women into senior roles across divisions.
We consider our year-on-year improvement towards this a significant achievement, especially in the technology industry.
Diversity and inclusion
We are committed to building an engaged, diverse and inclusive culture. The following summarises some of the diversity and inclusion initiatives we have recently undertaken, in addition to those we continue to maintain:
We have been ambitious with our approach to diversity and inclusion so far in 2023: