Thought Machine’s Gender Pay Gap: A snapshot of April 2020

What is the gender pay gap?

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 2020.

The methodology

The data does not reveal individual salaries or any difference in salary paid for the same role (which is illegal under the Equality Act) – rather, 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 regards to:

  • Average hourly pay, for men and women
  • Bonus pay, for men and women
  • Proportion of men and women in different pay quartiles
The data

April 2020 hourly pay gap

Gender pay gap diagram

As of April 2020, there was a mean (average) difference of 20% in the hourly pay received by men and women. This means that, on average, men are paid 20% more per hour than women in our company. A discouraging figure, this is a reflection that the highest paying roles in Thought Machine are mostly held by men.

A mean calculation will take all the available data points (i.e. every individual person’s hourly pay amount) and divide 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 – so we also want to calculate the median difference.

The median difference picks the data point precisely in the middle of the full list of everyone’s hourly pay – for men and for women – and we calculate the percentage difference between those two numbers.

In our data set, the median difference shows that hourly pay was 14.6% higher for men than for women. This figure, while slightly more encouraging than the mean, reveals there is a bias towards men holding more senior positions, and therefore higher paid roles in the business. Our 14.6% figure is closer to the 2020 ONS calculation of 15.5% as the median pay gap in the technology sector.

April 2020 bonus pay gap

Bonuses are not a standard feature of the Thought Machine compensation structure, however we do offer commission to our Sales team and referral fees to anyone in the company who successfully refers a candidate who joins Thought Machine. Commission fee and referral fee data must be combined to calculate our bonus pay gap figures.

Percentage of employees who received bonus pay

As Thought Machine has more men in the organisation than women (and the Sales team are predominantly male), we expect to see men being those who more frequently receive bonus pay.

We have calculated that 10.1% of bonus pay went towards men, while 9.2% went towards women.

Difference in bonus pay

In our calculations, we see an 84.2% difference in bonus pay between men and women. This gap is due to the size of commission paid on sales, compared to the relatively low amount paid out for referrals.

The median numbers – the numbers in the middle of the set – show that men are earning 50% more in bonus pay than women in the business.

While we continuously strive towards 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 begun taking steps to rectify the gender imbalance within the Sales team. Looking at our recruiting data for the past calendar year, we are proud to say that 31% of hires made into the Sales team were women – compared to 0% for the calendar year before. Though progress is slow – we believe we are on the right track to have women better represented across the business – especially in the Commercial department.

April 2020 pay figures and quartiles


Our April 2020 pay and quartile data immediately reveals the strong imbalance we have at the highest levels of the organisation.

The upper quartile of our business, the highest-paid segment of Thought Machine, is composed of 89% men and 11% women. In the upper middle quartile, men make up 80.6% of this group and women 19.4%. One quartile below, in the lower middle quartile, women make up 24.7% of this segment, while men make up 75.3%. At the lower quartile, women make up 34.7% of this segment, while men make up 65.3%.

It is not uncommon in many businesses across the world that women are underrepresented in the most senior positions. This imbalance is seen across some of the biggest businesses in the world – and our data helps us to understand how much more work we have to do to redress the imbalance.

Another part of this is an industry-wide problem: a lack of women working in STEM. The 2017/18 UCAS data reveals the stark difference between men and women pursuing STEM studies:


Data shows that 81% of students pursuing Computer Sciences and Engineering/Technology subjects are male, while just 19% are female.

We continue to work with industry bodies and groups to fix this imbalance and encourage more women to pursue technical studies.

Meanwhile, internally at Thought Machine, our key priority remains to recruit, retain and promote women within the business.

Our commitments and initiatives

Improved gender pipelines

An integral part of building a well-balanced team is to have a well-balanced pipeline. In recruitment terms – that means having a long list of relevant and interested men and women who we can speak to and talk about job opportunities at Thought Machine.

If the pool isn’t well balanced – we end up with too many of one kind of person applying for roles – so we need to do everything we can to go out to the market and get different people interested in working at Thought Machine.

So – to improve our pipeline, and increase the chances of different kinds of people joining the company, we specifically partner with diversity groups at different universities (for example OxWEST or Edinburgh Hoppers) as well as inclusive job platforms, such as LGBTQ+ job friendly platform myGWork.

Employer branding

Employer branding is a wide, catch-all term which refers to the multiple ways we promote Thought Machine as a place to work.

The more effectively we advertise our company culture, our benefits, and our diversity – the greater our chances of attracting a wide pool of talent.

We’re strengthening our Glassdoor page, promoting our internal events, going out into schools and universities and advertising our company culture in new and exciting ways. It’s a long journey, but we think it will go a long way in demonstrating the value in working at Thought Machine for a wider group of people.

Family friendly benefits

We’re conscious that women in many workplaces regularly find themselves at a disadvantage, especially during and after parental leave. We want to make it easier for women (and men) to work at Thought Machine, and lighten some of the load if they become parents.

We offer a range of benefits to expectant and new parents – and offer a set of fair processes to ensure that parents are well looked after, supported and welcomed back into the company once they finish parental leave. These include: six months paid maternity leave, four weeks paid paternity leave, matched shared parental leave, world-class private healthcare for employees (and their families) and many forms of flexible working.

We are also looking into a partnership with a firm which specifically supports women who have taken career breaks and are looking to come back to work.

Gender neutral job descriptions

New research over the years supports the theory that job descriptions and material can inadvertently appeal to one gender or another. In most cases, the language in job descriptions has proven to target and attract men – while simultaneously deterring women, and other marginalised groups, from applying to a role.

With the huge tech gender imbalance in mind – we’ve taken a concerted effort to remove loaded, gender-biased language out of our job descriptions by using language insights platform Textio. With this in place, we expect to receive a more balanced set of applications and eventually a more balanced pool of employees.

Flexible working

The world is changing, and the workplace is, too. Working from home has now become a fixture in many modern companies –and we’re supporting our team as they adapt to a new normal of hybrid work.

Our policy, while still being refined, allows for a mixture of home and office working – supporting those who want, and need, to stay at home for a variety of reasons.

Collaborative working tools and processes makes this a viable option for us as a business, and smart scheduling ensures that teams are getting the crucial face-time they need with each other in the office.

University D&I partnerships

Many of Thought Machine’s talented employees are recent university graduates – and we continue to have great success by finding that talent direct from source.

To widen our talent pool, we work with specialist groups located in our target universities – giving them first-hand insights and experience of a career at Thought Machine.

Matt Wilkins signature

Signed – Matt Wilkins, Chief People Officer, Thought Machine

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