Promoting fair pay and transparency at Slimmer AI

Slimmer AI

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Industry: Artificial Intelligence

Country: Netherlands

Number of employees: 50+

Slimmer AI is on a mission to solve real problems alongside exceptional founders by using the latest AI technology. Boasting an accomplished team of engineers, the studio has co-built AI software products for exciting ventures like Sentinels, Biller and Uncover. We talked to People Lead, Elsa Berg, to find out how Figures has supported the company’s compensation structure.

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# The Challenge

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Just like HR departments all over Europe, conversations in the Slimmer AI offices often return to one topic: fair pay.

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“Everyone talks about fair, but what exactly is fair?” asks Elsa.

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“Our team members have different sources of information – they have former colleagues in similar roles, so they know about compensation packages at other companies. Sometimes we’d find ourselves disadvantaged as the employees appear to have better insights into what they should be paid.”

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As People Lead, she’s responsible for the entire employee experience – and that includes ensuring that everyone receives a fair and justifiable salary. 

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Slimmer AI occupies a respectable, but not sky-high, position on the compensation charts.

“We’re not somewhere you can go for the highest salary,” notes Elsa. “Companies where they throw a lot of money at people, where you also have very specific things to do, and not a lot of freedom… we call those Golden Cages, because you don’t have a lot of opportunity to develop, to grow, to diverge. That’s certainly not who we are.”

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The Objectives

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So, making sure that employees are fairly paid was one of Elsa’s main priorities. But she also wanted to improve awareness so that people know what to expect and how they can progress.

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“We aim to be transparent about pay. It’s important to educate your team to know what an increase in compensation entails.”

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To achieve this, two things were key: obtaining accurate data for benchmarking salaries, and sharing the compensation policy with team members.

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The Strategy

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Before signing up with Figures, Elsa would spend 30+ hours researching salaries to establish benchmarks.

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“It was always a combination of internet data reports and any other connections that we have – talking to a few other people leaders and recruiters – to understand how they pay.” This method wasn’t just time-consuming; it could be inaccurate, too. “I didn’t always feel confident in the resulting benchmarks,” adds Elsa. 

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A peer recommended Figures to Elsa, who was exploring options to improve their system.

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With reliable data for many roles, Figures offered the potential to save hours of work. “Now, a colleague can fill in the majority of the benchmarks for salary reviews in an hour or two and we know they are up-to-date,” says Elsa. 

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Figures would also provide evidence to support decisions on pay, which could be confidently shared with employees.

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To promote transparency, Elsa held compensation sessions as part of the company’s ‘Knowledge Café’.  She shared details about the HR policies at Slimmer AI: why pay is fair but not in the highest percentile on the market; how performance relates to pay; and what equations are used to calculate pay.

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“When we talk about compensation, what plays into that?  What are the influences impacting pay rates?  I’m really trying to explain more of the general mechanisms that play into determining compensation.”

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The Results

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#1 Figures’ data confirmed that salary bands were on target. 

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“I didn’t have any big surprises when I got the results of the data.  I was very happy and confident and it was good for me to see that the majority of the team was already within the benchmark and compensated fairly,” comments Elsa.

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The Company Dashboard proved to be a helpful tool, showing which salaries aren’t on target: “Being able to filter and sort by how far below or above the target people are – I think that is one of the other main features that I've been using in Figures.”

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#2 Figures’ data supports their bi-annual salary reviews.

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Elsa says that she now relies mainly on Figures’ data to establish salary bands.

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“We have a rhythm of reviewing salaries.  We do our main review at the end of the year and a general check at mid-year. Particularly for the mid-year review, Figures' data is relevant since we only review those that are really far from benchmark, have delivered significantly above expectations, or they’re due for their promotion.”

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“We were preparing for our salary review so I asked a colleague to just jump on Figures and, I think within an hour or two, she had filled in the majority of the benchmarking.”

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#3 Accurate levelling was made easier using Figures.

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Before joining Figures, benchmarking took up a lot of time. “Honestly, it was a really painstaking and long process trying to plough through all sorts of different sources and gathering the data,” says Elsa.

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Figures’ dashboard was easy to use after Elsa had integrated her employee data. “The mapping process helped me a lot with levelling; I had to map out the salary for each person and that was super interesting and insightful in recognizing small differences in levels we previously couldn't take into account.” 

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