Comp leaders are no strangers to utilizing data. It’s crucial to nearly every workflow they perform, from benchmarking to pricing bands to building competitive offers. Comp leaders also know that no data set is perfect. Combining multiple data sources is key to getting the best results—when done right.Â
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“Multiple data sources is always better. One set of data will have a perfect peer group, another set of data will have better data for a certain location or certain set of job families,” said Katie Rovelstad, New Verticals Lead at Pave. “Pulling together multiple sources is a way that you can create a clearer, more complete picture of the compensation universe relative to your company.”Â
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In Pave’s recent webinar, Katie spoke with JC Hoyos, Director, Global Total Rewards at ClickUp, who shared helpful insights on the ways he leverages offer data to achieve business goals. Offer data is based on accepted offers, and it can help comp leaders peer around the corner of compensation and understand where compensation is headed. Let’s dive into three ways to use multiple data sources to attract and retain talent.Â
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The comp philosophy at ClickUp consists of four key elements: the target pay percentile, the pay mix (the relative proportion of guaranteed pay, variable pay, and equity), the reference group or peer group, and the company’s core values (things like internal messaging around pay).
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JC leans on multiple market data sources to inform the first two elements, target percentiles and pay mix. Today, he uses survey data from Radford as the main baseline for all benchmarking, and builds his templates around those reports. In addition, he taps into Pave’s real-time market data as a supplemental data source.
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“I really anchor on that, especially for jobs that were either a little painful the previous year (or the previous month or currently), or that I just hear buzz that they’re becoming a little more prevalent or I need to pay special attention to,” JC said.Â
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JC explained that having validation from two data sources gives him more comfort and confidence that he’s building bands accurately relative to the market, which helps his talent acquisition teams stay competitive.
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Keeping up with the evolving labor market is a challenge for any comp leader. When Talent Acquisition and hiring managers come to JC with requests for higher offers, it isn’t always clear whether compensation is the missing link or if other factors are at play. That’s where multiple good data sources can make the difference.
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JC shared an example of a time when sales leaders at ClickUp were struggling to hire for certain key sales roles. He wanted to make sure the team had the talent they needed, but the candidates’ asking salaries weren’t aligning with the ranges he put together. Was this a hot job? Were the ranges too low?Â
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When JC looked at the survey data, he found that it aligned with the ranges he had in place for those sales roles.So he also checked real-time and offer data in Pave’s Offer Insights tool for the most up-to-date comp benchmarks. Pave data also validated that ClickUp’s pay rates were competitive. This gave JC confidence that the sales role wasn’t a hot job, but that perhaps sales leaders were going after candidates with experience levels that demanded higher comp.
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“It gave us a cohesive story,” JC said. “It’s not necessarily to say we are going to keep the ranges, but to go to the leaders and say if you want that [candidate] profile, this is what it’s going to cost you.”Â
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When the data tells the opposite story—that a certain job is in fact hot in the market—comp leaders will often need to make their case to the finance team. Sometimes, it can be fairly straightforward. For example, everyone is aware that Machine Learning is a hot job. Finance teams are expecting to hear that they need to release more budget for ML hires, and they just need to know what the cost will be.Â
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But what about when a hot job isn’t well known? As a comp leader, JC looks to the data for signals that a job is hot in order to paint a picture for Finance.Â
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One data-driven sign might be if the 50th percentile for a role makes a large jump. Another might be if current incumbents are already at the high end of the pay range for the role, or if recruiters are having to close new hires at the high end of the range. He may also look at whether certain skill sets or job titles are trending in candidate profiles or from hiring manager feedback. When he puts all those variables together: “Those to me are starting to indicate that there might be a hot job,” JC said.
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Offer data is a great data source to add to the mix here. For example, JC talked about using Offer Insights from Pave to explore in-function trends in marketing roles. At the time, he saw that Content Marketing comp was trending up 15%, while Product Marketing was down 6%. Combined with the other variables previously outlined, those offer data trends can help JC tell the story about Content Marketing as a hot job.
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“This data helps contextualize and encapsulate the story for Finance,” he said. “If they need to release that budget, it’s their call to make. But I can help them be more confident in that call.”Â
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More data helps you make better decisions, develop better communication with your Talent Acquisition and Finance teams, and stay ahead of trends. Combining the right data sources enables you to shore up your comp strategy and stay competitive in a fast-moving hiring market. To hear more on how JC does this at ClickUp, view the full webinar recording.
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When you’re ready to add real-time data to your data mix, including offer data, consider Pave. Our Premium Market Data now includes Offer Insights from 7500+ companies via our partnership with Greenhouse. Request a demo today!
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