Recruitment Analytics: Make Them Work For You
Is there anyone on the employment spectrum who isn’t affected by recruiting challenges? Not according to the numbers. While solving talent challenges for its clients and enabling exceptional resources to contribute to the commercial ecosystem at large, the talent advocacy team at Arthur Lawrence repeatedly observes some common patterns that make talent management frustrating: The perception/reality gap, facts and commitments that don’t fall through, and most of all—the time and effort wasted in finding the right match. The worst part? These issues are chronic rather than episodic.
What Are Recruiting Analytics?
Recruiting Analytics—putting it colloquially—is putting recruitment related data to business use. Although you’ll discover all kinds of software that builds on recruiting analytics, they all share a common purpose: To identify ways of bridging the talent/opportunity gap in the most efficient way, for all stakeholders involved.
Recruiting analytics are formed by aggregating datasets from recruitment experiences. So if you’ve just worked on one kind of recruitment and are looking to expand using your existing database, we wouldn’t recommend it. It will be skewed, and your results while presenting an accurate picture of past recruitment practices, won’t be helpful in assisting you with future recruitment decisions. Recruiting analytics are most effective when there’s a repository of rich, diverse and validated datasets on which to build those analytics. (In another post, we talk about the importance of data wrangling, and how not enough businesses do it). Another benefit of recruiting analytics built this way is that they’ll be highly intuitive. You won’t have to plow much to find the answer you’re looking for.
How Can They Help?
Recruiting analytics have an original solution to many of the hiring problems mentioned above. Because they are often architected over historical datasets, with many repetitive patterns emerging in the recruitment cycle, one of their most helpful outcomes are predictive analytics. Predictive analytics assist with much more than workforce planning and forecast. They flag questionable behavior in any stakeholder before it becomes problematic. So whether it’s candidate ghosting, or a client who habitually rejects final interviewees with no reason, these analytics hold a torch to behavior users are best warned about beforehand. Such analytics can educate decisions about talent sourcing by going beyond a first-level analysis: what is the time range in which a TA (Talent Advocate) can expect to place a specific profile? What long does it take to fill niche consulting roles? We encounter recruiters who believe “Placement is 90% luck.” With a recruiting analytics platform at work with you, that simply isn’t true. Even accounting for externalities, recruiting analytics can give you an accurate measure of the time a position will take to close. The lesson here: Invest resources accordingly.
More than time, it’s the cost associated with placement that’s another source of concern. Recruiting analytics are particularly helpful here, given that they can present drill-up analysis by:
– Cost Vs Time Ratio
– Similar roles in the industry and/or other industries
– Average user expenditure to fill the same role
– ROI per role
If you’re looking to fill short-term project-based roles, this analysis is invaluable. If such data is made public, jobseekers benefit by directing their own efforts better too. Why waste time on a specific position, when better returns are offered for the same position elsewhere? Likewise, if analytics suggest a considerable degree of ‘ghosting’ for a said position, potential jobseekers seriously seeking the job should present themselves accordingly: emphasizing commitment and their willingness to start immediately.
All Stakeholders Benefit
Transparency in the hiring decision requires you to make difficult, but quantifiably sound decisions. For instance, the belief that millennials are chronic job hoppers may apply to many industries. But what about the specific position and location you’re hiring for? What does the data say there? Err on the side of reason and caution when the numbers are on your side.
With the growing influence of the gig economy on traditional hiring practices, this is a very important benefit. It assists with fairer negotiations for both parties; transparency and flexible arrangements that result in win-win scenarios for all stakeholders. The figures from the analytics dashboard provide the groundwork needed to prepare such contracts.
Recruiting analytics help clients too. They attest to the credibility and soundness of the talent management system. The ratio of placements versus applicants isn’t always bad news, for instance. Often, it’s a reflection of the very thorough testing and validating methodology the talent management team has in its place.
Dashboards are a good starting place for managers to ask the right questions and uncover the real issues at hand. The benefit of an analytics solution is that the dashboards represent real-time data and are almost always easily exportable. (i.e. better than a slide deck if you’re hoping to make a collective decision).
For high-demand roles, there is added emphasis on employer branding. Even if it is a high-growth position, employer branding is key. If your organization has a positive history, analytics can become a powerful ‘brag point’ for your organization. They provide evidence of:
Career growth rate
Other success stories within that role
The best part is: Since analytics use aggregated data, with filters to anonymize records, this form of advertising is perfectly honest, and completely legal. You achieve transparency without compromising privacy.
Organizations sometimes prefer adding to the capabilities of recruitment analytics by adding performance-based elements to the mix. Drilldown analyses per employee or unique hiring scenario can prove to be helpful in complex or hostile conditions. In case there is legal recourse or union activity on the decision to discipline an employee, recruiting analytics provide a robust record of employee offences leading to that decision. Each incident has a time stamp and visual evidence. As we earlier mentioned, the richer the datasets backing the analytics, the more accurate the visual output will be.
Transparency in the recruitment lifecycle benefits all stakeholders: It keeps the talent team accountable, competitive, and professional, and empowers clients and jobseekers.