How an Autodesk Recruiter Used Data to Reset Her Hiring Manager’s Expectations – and Make a Quick Hire

Jennifer Kopatz has had to deal with demanding hiring managers before. But earlier this year, when a long-time Autodesk hiring manager said he needed a senior software engineering manager with web development experience, a top-tier education — and 11 other must-haves — Jennifer said, Whoa buddy!

A senior recruiting manager at the design software maker Autodesk, Jennifer is one of two recruiters at the company who support the software development teams.

Jennifer knew that the last time her hiring manager had filled this role it had taken more than seven months, and she believed that the pool of engineers who met their requirements would be small and fruitless. But she also believed that she could put data in front of the hiring manager that would get him to think differently about what he needed.

To find that data, Jennifer turned to LinkedIn Talent Insights, an analytics product we recently launched to equip talent professionals with real-time, actionable data and insights to make better-informed decisions about their talent strategy.

A charter user of Talent Insights, Jennifer used the new product to reshape expectations, find a viable candidate quickly, and forge a better, more trusting relationship with her hiring manager. Here’s how you can too:

Show your team what the talent pool looks like

Jennifer knew that this hire would be difficult. The engineering team had already interviewed a number of internal candidates, including some from an Autodesk office that was closing in Switzerland. “And none of them panned out,” Jennifer says.

So Autodesk turned to the external pool of candidates, hoping to tap into the 7,000 software engineers Talent Insights identified in the Bay Area. But Jennifer’s hiring manager wanted a software engineer who was also a manager and had at least three years of tenure in his or her current title. And had the 11 all-important skills, which included web applications and development, Agile, Scrum, and cloud applications and development.

“So I pulled up all the buzzwords he wanted and the population was under 300 people,” she recalls. Using Talent Insights, Jennifer was able to show the hiring manager both how small the number of candidates was and how most of them were working at high-paying companies that they couldn’t compete with on salary. And that changed the conversation.

“It adjusted his mindset to know that there weren’t all these people out there,” Jennifer says. “You don’t know what you don’t know. But then it was right in front of him and that was really helpful.”

Now, Jennifer and her hiring manager were able to look at different scenarios — expanding the geography, changing the required years of experience, relaxing the requirements — in real time.

“Those are really good conversations to have,” she says. “In the past, you would have had to wait weeks to get some of these reports from other tools. To have this information instantaneously is amazing.”

Competitive intelligence can expand your pipeline

In addition to a long list of skills, her hiring manager also had insisted on someone from a “top-tier” school — MIT, UC-Berkeley, Stanford. Jennifer used Talent Insights to show that, in addition to hiring engineers from the big-name schools, Autodesk’s high-profile Bay Area competitors were bringing in senior software engineering managers from other engineering schools, both local and international.

“If our competitors are hiring people from different schools, maybe we should too,” Jennifer says. “If they’re hiring away from other companies, maybe we should start looking at those companies.”

As her colleague relented and converted some of his must-haves to nice-to-haves, the candidate pool became larger and larger.

In two weeks, Autodesk made an offer to a veteran software engineering manager.

Share real-time data with hiring managers as early as possible

“Hiring managers,” Jennifer says, “especially engineering managers, love data. And to be able to show data — not anecdotal data but real-time data — makes a big difference.”

“In the future,” she says, “I will probably bring this data to the second meeting with every hiring manager.”

The last time Jennifer’s hiring manager was filling this same position it took him 220 days to land a candidate. This time, he had an offer in front of a candidate two weeks after Jennifer’s data show-and-tell.

Data really is the new corporate superpower.

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