In our final installment of a four part series exploring the typical recruiting process gaps that organizations deal with when gathering candidate, recruiter and hiring manager feedback to optimize their recruiting process, we turn to scalability.
We’ve already looked at a big gap, lack of automation, which is closely tied to scalability. To review what we’ve covered in the previous articles, top-tier organizations, to their immense credit, have cobbled together processes which allow them to gather and analyze feedback from all constituents involved at each stage of the recruiting process (apply, phone screen, interview, offer, etc.).
And as we’ve explored, these programs are fraught with manual processes, they lack privacy/security/confidentiality, they result in disparate, disconnected experiential data and, finally, they lack the ability to scale beyond one-off projects or across large disparate target segments.
Recruiting Process Feedback Automation and Scalability
Pulling data from your ATS to a survey tool and then extracting and combining the resulting survey data for analysis within another system (and doing so for each stage of the hiring process) makes scaling that process virtually impossible.
First, the main mechanism for scaling this kind of manual recruiting process is increased generality. In other words, you most likely have to make surveys longer, more general and less frequent (combine two or more hiring stages) to expand the scope of the feedback and analysis beyond a small segment or pilot.
So if you are gathering interview feedback from candidates, for example, it’s highly improbable that you would be able to tie that feedback to specific hiring managers, locations or jobs. If you are exporting interview stage candidate data from the ATS to a survey program, then manually sending surveys and gathering that data into analytics that are solely focused on that specific survey, good luck getting granular with the who, what, when, where, why of the interview.
Good luck mapping key metrics from phone screen feedback to interview feedback. Or analyzing quality of hire by interview satisfaction to uncover clues as to how to increase the ratio of quality hires to failed hires. The location, hiring manager and job data are all back in the ATS. And all the stage based feedback resides in separate reports.
By the same token, if you are dropping survey links into an email workflow from the ATS interview follow up stage, you get the same type of generalized results. No ability to discover correlations between metrics from other stages (without extracting all survey data into yet another reporting tool). No ability to tie feedback to hiring manager, location, job, etc.
The best that can be gained from this kind of approach is tracking broad satisfaction scores and aggregate reporting of interview experiences like timeliness, preparedness, etc.
Global Recruiting and Scalability
The other impediment to your ability to gather recruiting feedback to optimize your hiring process is language and localization. Let’s say you are committed to a version of the less than automated feedback process described above and you have the manpower to make it work.
Now try to tailor your feedback program to other territories with slightly different recruiting processes and multiple languages and reality introduces a hard “no.”
With a fully automated feedback platform integrated with your ATS, every candidate that gets a survey is tagged with location, hiring manager, job requisition number, source – you name it. German candidates get localized surveys with localized questions in whichever language you specify because the feedback platform uses ATS data to trigger which survey goes to which candidate and when, based on a full profile of the candidate.
Without such a system, the level of manual processes to identify, extract and segment data to support the delivery of the right surveys to the right people grows exponentially. And again, dropping localized survey links into ATS workflow emails for the interview stage example described above, solves the data export problem but leads to the same problem of the resulting feedback analytics and metrics being disconnected from candidate, location, hiring manager, job, etc.
So if you are new to this subject, you may be thinking “I get it. Automated and integrated processes are more effective.” But I tackle this subject only because we at Survale see it every day. We talk with prospective clients that tell us they already gather and analyze feedback at each stage of the hiring process.
When we dig deeper, we discover just how manual, unsustainable and unreliable these processes and data are. Then we build ROI business cases to replace these processes with a purpose-built system.
And make no mistake, the end game here is not high candidate satisfaction scores. Experiential recruiting feedback holds the key to an optimized, constantly correcting hiring process. Just as customer service organizations have used transactional feedback to optimize customer service at each touch point, recruiting organizations are moving to using stage-based feedback to optimize performance at each touch point to improve hiring results throughout the hiring process. And ensure that hiring processes adapt as the organization and the talent market evolves. To read the entire series, click here.