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Rapidly changing technologies, global skills shortages, unrealistic client expectations — staffing agencies have their work cut out for them these days. 

Just ask Andrew Kable, director of workforce solutions at Australian technical recruiting consultancy Interpro. Andrew and his colleagues were recently tasked with helping a client assemble a large team of engineers and other niche technical roles to deliver a systems integration project of unprecedented scale and complexity in an Australian context. 

On the surface, it was the kind of job that keeps recruiters up at night, requiring a wide variety of low-supply, high-demand skills, all while needing to balance costs. Add to that Australia’s engineering shortage and pretty soon those potential talent pools can start to look more like puddles. 

“You’ve got to be very thoughtful when you put a big project like this in the market,” Andrew says. “The constraints can be overwhelming.”

Overwhelming, yes. But not insurmountable.

To meet the challenge, Interpro turned to LinkedIn Talent Insights, a talent analytics tool, to identify how many people in the Australian workforce have the specialized skills needed for the project and in what combination. 

Armed with real-time data, Andrew’s team was able to help its client build a viable workforce plan that responded to everything from gaps in the talent pool to job descriptions that were not yet aligned with the latest market terminology — and they were able to do it at the outset of the program, without disrupting budgets and project timelines.

In the end, using Talent Insights and LinkedIn Recruiter together, Interpro met its hiring goal, sourcing some 200 workers across a variety of niche skill domains. “It wasn’t easy,” Andrew says, “but we were able to get the hiring managers in the right mindset from the beginning, and that’s always important.”

Rethinking team structure and role distribution 

Interpro’s biggest challenge out the gate was skill availability. Australia is a small, predominantly extractive economy. Companies looking to staff up on engineers and speciality technical roles are dealing with a very small pool. “Once you combine two or three skills,” Andrew says, “the top of the funnel can shrink very quickly. There may only be a handful of people in the country with the requisite qualifications, and they’re already employed and well compensated.” 

But what if you unbundle those skills? When evaluating the client’s job descriptions and team structure, Interpro identified opportunities to shift tasks and responsibilities between roles based on supply data insights. Given the scarcity of talent around cloud infrastructure in the Australian market, Andrew’s team learned that separating DevOps and Software Development positions significantly increased the pool of possible candidates and reduced costs. 

Another good reason to unbundle skills: You get a much more diverse pool. Andrew says that this is common in the emerging field of data science. “If you blend skills from the data engineering profession with a data science job description,” he says, “the female representation in the talent pool drops off dramatically.”

Reviewing candidate profiles

Once Interpro identified their top-of-the-funnel candidates, Andrew says, then the real work began. His team reviewed candidate profiles to make sure they had the right skills in the right context. “It’s essential to be able to contextualize skill data,” Andrew explains. “A skill doesn’t sit in a person. It sits between a person and their environment. You need to know how to interpret all of the variables to make the best recommendation to your client.”

The next step was outreach. Andrew’s team began contacting potential candidates to gauge their interest levels, and to test basic assumptions about work location, conditions, and salary expectations. To do this, they incorporated search results out of LinkedIn Talent Insights directly into LinkedIn Recruiter, which allowed them to use CRM tools for the campaign. 

But the real game changer, Andrew says, was being able to manually review raw candidate profiles in Recruiter, based on Talent Insights guidance. “A lot of talent intelligence tools gather data from anonymized profiles,” he says. “It’s a lot more powerful to look directly at the candidate’s skills in context by seeing their full LinkedIn presence.”

Making data-informed decision around salary

Identifying a potential team of hires is one thing; getting them all to sign on the dotted line is quite another. When it came time to start crunching the numbers, Andrew’s team noticed an immediate obstacle: The client’s salary structure was below the market in some key areas. 

“Often companies keep compensation data that’s not accurate,” Andrew says. “Salary is all about demand.” A classic example, he says, is that a software engineer with five years experience may be paid more than a software engineer with 15 years experience because the less-seasoned engineer came up working in the cloud, whereas the more experienced candidate may have a bunch of skills that are no longer in demand. “You need a higher level of granularity around skills and demand,” Andrew says, “to get your budgets right without affecting your timeline.”

The client’s talent acquisition team was able to present a strong business case to the finance team that certain salary bands should be revised upward. And, again, this was undertaken at the beginning of the project rather than after roles had been sitting open for months. 

In the end, Interpro helped its client meet their hiring goals and even shaved a month off a three-month hiring process for some of the more niche, low-supply roles positions. Could they have done it without using LinkedIn Talent Insights? 

“Maybe 10 years ago, when we lived in a slower-paced world,” Andrew says. “But today, when industries are rapidly evolving and skills are changing so quickly, you need to take a data-first approach to hiring.”

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