Why Using Outdated Salary Data Negatively Affects the Recruitment Process

October 12, 2020
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Author: Glenn Hunter

One of the most important tasks of an organization’s planning is setting up a compensation strategy that is not only competitive, but also supports a high level of employee engagement. Solid comp programs, after all, are a must for recruiting and retaining top performers.

Relying on old salary data puts your recruitment strategy at risk of not succeeding.

But whether the plan is devised by recruitment firms, internal talent acquisition teams or both working together, compensation in too many cases is based on outdated, unreliable data – or even on salary data from candidates who were previously placed in the identical role.

Relying on salary data from previously placed candidates or survey data sources fails to factor in a city’s unique employment conditions or the supply of candidates with the specific skills and experience needed to do the job. Economic performance by location and in-demand occupation can significantly shift salary demands. A blind spot in this area will inevitably delay and prolong the recruitment process, costing the recruitment firm and its client organization time and money.

A better way is offered by LaborIQ® by ThinkWhy, a cutting-edge software tool that bases its salary answers in real time on a location’s talent supply, employment conditions, company size and industry. LaborIQ ensures salary answers that are unbiased and above all speedy – every recruitment firm’s Holy Grail.

Salary Answers Using Validated, Real-time Data

Because compensation depends on a variety of factors that can change quickly, a salary level that was offered to a new employee even two months ago risks being out of sync with current job conditions. So, recruiters who determine their offers based on historical data could be suggesting salaries that no longer align with what competitors are currently offering. That can automatically stretch out the recruitment process and result in hiring managers losing top talent to their business rivals.

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In contrast to this method -- and to other compensation surveys that rely on crowdsourced or otherwise unverified data -- LaborIQ provides salary answers that have been validated against 80 million data points to ensure accuracy. Through a proprietary data science model called ATILA™, the tool filters salary solutions not only for the likes of industry, company size, experience and education, but it also factors in the difficulty of filling the role in a particular market. Is there a surplus of talent for the position in the city, or is there a shortage? Both will affect the salary offer.

With specific information in hand about a role’s true market value, recruiters can feel confident offering a higher salary to win over a much-coveted candidate. They can also deliver value for their clients by:

  • Updating old salary ranges. If the client hasn’t hired for a particular role in several years or performed annual salary reviews, they’ll now have current information.
  • Revamping an existing role. For positions now requiring more education, additional certifications or some other change, clients will gain visibility into salary adjustments that may be necessary to lure the best candidates.

Applying accurate job-market data will make it easier to attract and hold the attention of in-demand candidates. With offers based on validated, real-time data, job prospects will feel valued and be more inclined to seriously consider or accept the offered position. That’s the definition of a win-win-win for the recruitment firm, its client-organization and the candidate alike.

LaborIQ by ThinkWhy continuously monitors and forecasts labor data at all levels, measuring impact to cities, industries, occupations and business across the U.S.