— November 9, 2017
The logical way to think of hiring software is considering what product is going to best solve the pain points that your recruiting team has.
Unfortunately, a product-focused culture that mostly considers features and potential for customizations can miss the big picture.
It can create a sales-driven culture where sales reps click-through demo bullet points. When you hear 5-10 of these presentations, you can get confused.
But what are some different approaches to picking the right hiring software?
Here are 3 considerations that would benefit you to keep in mind.
1. The hiring manager adoption rate
This is crucial for two reasons:
- The actual hiring cycle process
If your company is investing in technology, metrics are going to be important.
In the talent acquisition world, we know some of the key metrics: quality of applicants, time to hire, and quality of hires.
Unfortunately, sometimes in organizations there’s a square peg/round hole problem between the hiring software and whatever systems and processes the hiring managers are using.
Hiring managers may see a new software as “the domain of HR,” and thus they won’t adopt it at high enough rates.
This is a problem. As Newton notes:
Hiring manager input is necessary to gather the most important metrics.
If the recruiting and HR users are the only ones using your system, it’s only logical that the system will capture metrics exclusively from administrative users.
This won’t yield helpful insights without significant data manipulation (you know, building spreadsheets by hand on Fridays).
Only when hiring managers are consistently using an ATS will you be able to get holistic recruiting performance metrics that will help you automatically generate reports and have the knowledge to pinpoint bottlenecks and areas for improvement.
Solving this problem is relatively easy.
When you get down to 2 to 3 potential vendors, look at the departments that hire the most internally. Have some hiring managers from those departments demo the software options you are considering.
It cannot just be a HR decision because it’s possible hiring managers won’t adopt the software. That’s going to cause issues in advancing candidates and gathering useful data.
2. Needs beyond the traditional ATS
Consider some of the terms we keep hearing at HR tech conferences and on recruiting blogs:
- Machine learning
Some tech like VR may never find a mainstream place in talent acquisition. But AI already has.
AI, which is closely tied to machine learning, has allowed the conventional ATS to go from “dumb” to “intelligent.”
A conventional ATS is “dumb.”
It stores candidate information but it doesn’t pull any connections between people. It’s very hard to access older candidates for newer positions for candidate re-engagement. It’s hard to work with passive candidates.
An “intelligent” ATS has AI functionality baked in.
The AI allows for more robust connections across your candidate database, including prior candidates who were shortlisted but didn’t make the final cut for role opportunities.
AI makes all facets of the hiring process easier, including screening resumes.
That might be the biggest advantage of AI tech at this stage, because it frees up time for human recruiters to focus on more relationship-building.
When you listen to vendors, consider what you need.
Is it a list of features, or is it an ability to be smart about your talent acquisition moving forward?
If it’s the latter, you need an “intelligent” ATS, with the ability to learn and build connections, as opposed to an older-school model that’s more a resume repository.
3. Paying attention to the outliers
For most roles, there are seemingly ideal candidates and AI software will help you identify them.
But sometimes an outlier, someone you’d never normally consider, might end up being great in the role. This could be for many possible reasons: connection with the team, connection with the manager, pr connection with the role.
You need to listen carefully to the pitches of sales teams and see if their hiring software can help you “pay attention to the outliers.”
To a large extent, identifying who’s the correct outlier is going to come from AI and machine learning.
As the system learns about the role and other data (e.g., department attrition, salaries, promotions), it can help identify people who might be great fits for new roles even if the hiring manager says, “No, this will never work.”
With business models constantly shifting and cost-cutting measures very much at play in companies, the cost of a bad hire is worse than ever. You can’t afford to get this wrong.
That means you need the right hiring software.
But you can’t just evaluate it in terms of a bullet point list of features.
You need to think more about how exactly the software will transform what you do and how you can influence overall strategy instead of just the talent silo.
You’ll need to think a bit differently about your real hiring needs.