5 Recruiting Metrics Ebook

If You are Not the Talent Acquisition 1%

Jack Hill
Aug 08, 2017

one percent

Talent acquisition (TA) vendors and industry analysts alike are pushing the narrative of Artificial Intelligence (AI), Machine Learning and Natural Language Processing. It most likely will be the future of matching and selection but the market is still trying to figure out its place and how these new technologies interplay with human interaction and decision making. Even though the TA industry hasn’t yet fully accepted the practical implementation of these technologies it will most likely continue to dominate the “wishful” discourse of industry experts and will have a significant seat at the TA strategy table. Larger corporations with even larger budgets (what I like to call “The Talent Acquisition 1%”) will adopt some of the bleeding edge AI/Machine Learning tools without the demand to empirically justify those expenditures with believable ROI models. Until these tools have a decent track record of value the (non-1%) rest of the TA world will be slower to adopt.

robots

I have seen requisition loads rise and recruiter counts drop over the last five years, as companies and HR departments operate on leaner budgets. For many companies, there are too many openings to fill and too few recruiters to work those roles. TA departments need more technical and analytic support to drive the same level of excellence and service provided in years past. If you don’t have the budget to play with new AI and machine learning tools, a data driven approach to recruiting can help support your TA team and reduce the strain of high requisition counts without the promise of robots (bots) and algorithms to solve your pain.

The following are a few thoughts and ideas to help drive efficiencies if you are not “The Talent Acquisition 1%.”

Candidate Behavior

Make sure you investigate a web analytics tool to help your organization understand the behavior of potential applicants on your career portals. You should be able to pull funnel reports that will show your drop-off rates from screen to screen. This data should help you understand how adding questions and steps to your application process effects the drop-off rate of your potential applicants.

One of the ways to help your overleveraged TA team is to increase the amount of data you collect during the application process. Your ATS should be able to assist in front line screening and the more data you collect the more automation you can drive in your workflow. In addition, the more data you collect the better you will be able to leverage the search tool in your ATS (get away from keyword searches and use more fielded data sets) for future openings.

Although the trend in the market is for quicker and leaner application processes, you can’t help your recruiters with their volume of work unless you collect the right amount of data upfront. Parsing engines and social network application features can help drive the quick capture of information.

Constantly evaluating your candidate flow will help you find the right balance of data collection that can help drive automation in the evaluation process. (Google Analytics is a free tool that can help you accomplish this task, but there are other solutions on the market as well).

Google Analytics

Process Review

The most common issue I see in Talent Acquisition technology deployments is stale and outdated workflows. Most organizations deploy their technology and implement a process that maps to the current economic or corporate conditions at that moment in time. Flash forward 5 years and the same process and workflow is in place but the needs of the company and the demands of the labor market have changed.

It is imperative to set up internal process reviews at least once per year to respond to changing demands in the business. (I would suggest even more frequent reviews when – or if – time allows.) Your recruiting technology should provide you with robust reports to find bottlenecks and delays in the process that need your attention.

In tighter labor markets, you may want to look to a leaner process with fewer steps to help drive “speed-to-offer.” In less demanding labor markets, you may want to add steps to your process to facilitate more accurate decision making. A well-defined and market relevant process can help build efficiencies to assist your recruiters with higher requisition loads.

Workflow Automation

There are certain actions that a recruiter performs day-in and day-out. These are the simple but time-consuming administrative tasks around recruiting. There are many steps that can be fully automated through your recruitment technology (i.e. offer, scheduling, feedback). The fewer data entry and manual steps, the more efficiencies you will grant your busy team.

Background checks, compliance (e-Verify, etc.) and new hire exports (HRIS) are good examples of efficiencies you can find in your process associated with a robust integration strategy for your recruiting technology.

Proper Database Management and Communication

If your recruiters must re-invent the wheel every time they have an opening, you will dramatically increase time-to-fill. Many roles your teams are filling have responsibilities and skills that map directly to previously posted jobs. You most likely have a deep inventory of pre-interested candidates in your ATS database that you should always be leveraging first. One large healthcare customer I work with recently stated that 70% of their hires over the past year have been in their database for over 2 years.

Proper database management requires work and effort by the Talent Acquisition team. You must tag and group candidates you evaluate, but don’t hire, for future communication and consideration. You don’t need a fancy CRM system to send mass communications to these groups to keep them warm and interested. A good ATS should allow you to measure the number of hires from your “inventory” (database). We need to demand more of our technology to help you search and find relevant candidates in the database you spent so much time and money building.

Conclusion

Although the future of recruiting will most likely incorporate AI, machine learning and other exciting technologies it is an imperative to find strategies to help your over leveraged teams now with the technology you own. A more robust data driven approach to recruiting can help diffuse some of the pains associated with high requisition counts. The more you can automate and find efficiencies in your process the more time your recruiters will have to actually be recruiters. 

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