How Data, ML, and AI is Reshaping Staffing Agencies Recruiting Strategies

Imagine walking into a recruitment agency a decade ago. Stacks of resumes, folders, and colorful sticky notes on every recruiter’s desk would be normal. Fast forward to 2023, and you probably would have difficulty getting any paper documents at all.

Reason: Cutting-edge online staffing solutions.

The recruitment industry has undergone a massive transformation in recent years with the advent of data science, Machine Learning, and Artificial Intelligence. Over 85% of recruiters credit AI recruitment tools to speed up their recruitment process. A majority of them (58%) found AI helpful in candidate sourcing, while 56% considered it advantageous in screening candidates^[1]. So, staffing solutions not just accelerate the entire recruitment process but also help define and refine hiring strategy.

Suggested Reading on Staffing Agency Tools: Top AI tools for staffing agencies in 2023

In this guide, we will explore the impact of data regulations and machine learning on staffing agencies’ recruitment strategies. We will also delve into how AI hiring tools have turned out to be a comprehensive solution for staffing agencies. In the end, we’ll answer some FAQs pertaining to data-driven hiring.

The impact of data-driven hiring

Data-driven hiring is the process of using quantitative and qualitative data to make an informed hiring decision. It involves analyzing metrics such as applicant source, time-to-hire, and candidate quality to optimize the hiring process and make informed decisions about candidate fit.

Your talent acquisition decisions can’t just rest on instincts alone. Your gut feeling is important, but not everything. When talent is concerned — whether it’s retention or acquisition — relevant research and data need to be present, paired with your recruiting instinct, to make the right call. Data-driven hiring decisions, especially in the midst of a pandemic, are the only type of decisions that can get us through.

Take talent recruitment, for instance. Traditionally, it lacks the strategy, efficiency, and information needed to bring the ideal candidates to the surface. To this point, recruiters have relied on standard Boolean search strategies that scour multiple channels to find candidates. Instead, they could use HR metrics and analytics to tailor their approaches and meet the right candidates in the right places.

A polished and fleshed-out HR data strategy is the only way to capitalize on this information and garner the kind of talent acquisition and retention results HR leadership covets. To achieve that vision, HR leaders need to understand the difference between HR metrics and analytics and the critical role each element plays. Here’s a breakdown of the two terms:

HR metrics

The purpose of HR metrics is to put a numerical spin on the effectiveness and efficiency of one (or several) HR policies. HR metrics can put that shift into the proper perspective if a noticeable change occurs.

Let’s say, for example, that employee retention dipped from 7.5% to 5% over a year at a given company. Those data points tell the story of a 12-month trend, while the 50% decrease is a metric that the company’s leaders can apply to their HR data strategy and employee engagement strategy.

HR analytics

While HR metrics offer a no-frills look at differences in data points, HR analytics looks at how employees affect business outcomes. The purpose of HR analytics (or people analytics, as it’s sometimes called) is to explain why something occurs and what that impact is numerical.
Returning to those retention numbers, HR analytics could be useful in establishing context. HR analytics can attach reasoning to why employees or candidates do the things they do, enabling HR leaders to act accordingly.

HR metrics and analytics allow companies to make talent decisions in good faith and with proper context. Familiarize yourself with the kinds of figures specific to each term to arrive at the conclusions needed to make the best decisions for prospective and current employees.

It’s clear that data is important in driving informed hiring strategies for staffing agencies, but given how skeptical the online users and governing authorities are of data theft, it’s also crucial to account for the effect of data regulations on your staffing solutions.

But don’t forget the effects of data regulation

Like anything of value, data’s true worth is only realized when it’s adequately protected.

According to an Insight222 study, privacy and ethics concerns threaten 81% of people’s analytics projects^[2]. Laws like GDPR are designed to address these privacy concerns, and governments are making sure they’re enforced. For instance, those who fail to comply with GDPR can be fined as much as 20 million dollars or 4% of their yearly global turnover^[3] — whichever is more.

For HR departments, hiring managers, and staffing agencies, the greater emphasis on privacy and consent with regard to personal data means a lot more red tape for the candidate engagement process. The trick for recruiters to harness data-driven hiring will be navigating current data regulations while preparing for future ones.

Consent has always been necessary before a company can hold employee data. What GDPR now mandates is that consent be “specific, informed, and unambiguous”^[4] as well as revokable. Essentially, this means the current way of doing things is likely obsolete.

GDPR isn’t the endgame of data regulation — it’s the first step toward a more protected and compliant future. Here are a few GDPR HR implications^[5] that recruiters should expect to encounter going forward:

Candidate data will no longer be free

In our current environment, data is easy to access for free. People are beginning to wake up to this fact and are putting a real value on their personal information.
As GDPR broadens the definition of personal data, the value people put on their information will only become more critical. For recruiters, this likely means they will have to consider each candidate’s data an asset they must pay for before hiring managers will be able to see it.

Access to third-party data will change

HR tech vendors currently pay to access third-party data. But now that Europe-based platforms must comply with GDPR, many of those partnerships could change or dissolve altogether.

For the most part, GDPR’s impact on HR will force vendors to take new approaches to third-party data collection. This also means that recruiters and hiring managers must ensure vendors have a backup plan.

New avenues for lawsuits

GDPR HR compliance is going to be a common subject of lawsuits in the future. Whether it’s a failure to get permission before contacting a candidate or an instance of someone viewing personal data through an unsecured browser, there are plenty of ways companies can get sued for violating these laws.

HR providers have already run into trouble with data breaches, such as PageUp in 2018^[6]. As more global companies comply with GDPR, the frequency of these data breaches will only increase.

With that, it’d be incorrect to think of data regulation as a hurdle in data-driven hiring. Rather it helps make information more private and keeps people’s information safe – what we all should strive for in fair hiring practices.

That’s one reason automated, or AI-led systems, are attractive: They can handle a lot of the red tape for you, ensuring you stay compliant while making the process as easy as possible. We’ll come to it later in this guide.

The impact of Machine Learning on hiring

Machine learning (ML) basically enables a tool to learn and make predictions based on patterns in data. It is a subset of artificial intelligence.

Staffing agencies can benefit from an ML-powered staffing solution as it can help streamline recruitment processes, identify high-performing employees, and predict employee turnover. These hiring tools can also analyze resumes, shortlist candidates, and recommend suitable job roles while bypassing hiring bias.

Improving Job Matches for Candidates

There are staffing solutions that have been using assisted machine learning to help improve job matches for candidates. This works by manually rating job search results against popular search terms. So, for example, if a candidate were to search ‘substitute teachers’ and the results included jobs for ‘substitute nurses’, this would receive a one-star rating out of five.

Once this stage is completed, this information is fed into the ‘machine’, which goes on to identify patterns for good and bad jobs. The logic is then applied to all jobs on the site to ensure that candidates are presented with only the most relevant search results.

This approach to machine learning is helping to improve matches for candidates while also pushing employers’ jobs in front of the right people. Ultimately, this will ensure companies receive more applications from the most relevant candidates.

Analyzing the Success of Job Adverts

Your job advertisement is one of the most important parts of your hiring process. After all, it’s the first insight a candidate has into your company, so it’s crucial to get it right. The good news is that this is an area where machine learning plays a key role.

Of course, AI and machine learning can never take away the entire task of writing your job adverts; this still requires a human touch. However, it can help to analyze your postings and tell you why some adverts work and others don’t. This might be down to language patterns, tone of voice, and even any gender-specific wordings that might be putting off applicants.

It then uses this information to make suggestions on what you should (and shouldn’t) include in future posts. For organizations that are struggling to recruit, this can provide valuable insights that make a real difference to your hiring process; so it’s definitely something to explore.

Screening Resumes and Assessing For Cultural Fit

Another key area where machine learning impacts hiring is, of course, throughout the screening process. Time and money are precious, and both can be lost if your screening process isn’t as efficient as possible. The good news is that technology is making it easier to screen resumes and assess candidates for cultural fit.

While screening candidates’ skills against a job description is nothing new, the fact that these tools are now able to assess how well a candidate will fit into the company culture is particularly impressive. After all, as it becomes harder to source top talent, companies are increasingly hiring on potential rather than experience. So, assessing how well they’ll fit into your business and what they can bring to the table can be extremely beneficial.

Another key benefit of using machine learning in staffing solutions in this way is that it can help to remove human bias throughout the screening process. Whether we mean to or not, we’re all guilty of judging a book by its cover; anything we can do to prevent this can help.

Suggested Reading on DEI Hiring: Blueprint to drive DEI hiring in the workplace

Managing Relations with Candidates

Candidate experience is always going to be an important part of the hiring process. As mentioned above, it’s harder than ever to recruit right now, so companies must focus on candidate engagement.

This covers each stage of the user journey. From answering candidate questions at the application stage, to staying in contact pre and post-interview; keeping candidates happy and informed should be a priority.

One of the trends we’re noticing in this area is the rise in chatbots. Many organizations are using these to help interact with candidates; for example, by providing more information about a job or even scheduling in an interview. Again, this can save massive amounts of time when recruiting, ultimately positively impacting your hiring efforts.

Suggested Reading on Candidate Engagement: Why candidate engagement is critical

However, it’s important to note that each area of your recruiting strategies handled by a staffing tool, should be closely monitored to avoid any form of bias. Indeed, some organizations have hit the headlines for all the wrong reasons when it comes to using faulty hiring tools in their hiring process; and you don’t want to be one of them.

The impact of tech on hiring

According to a G2 study^[7], 68% of recruiters believe their jobs will become more efficient in the next five years thanks to technology. While on the other hand, a general sentiment among candidates is that tech tends to remove the human touch from human resources.

The problem isn’t that recruiters relied too heavily on technology or prioritized efficiency over person-to-person connections. Instead, the issue is that recruiters are just now figuring out how to tap into the benefits of those advanced tools without losing the art of their profession.

Recruiting is as much art as science — and the art happens on both sides of the equation. Ideally, innovative recruiting solutions should optimize the hiring process while supporting recruiters in the higher-value tasks of engaging with talent.

Here’s how recruiting technology can help hirers optimize the hiring process without sacrificing the personal touch:

Empowering recruiters — not replacing them

About 94% of recruiters surveyed by G2 say innovative recruiting solutions simplify their jobs. A solid hiring tool should work with recruiters and provide them the necessary People Intelligence to find qualified, capable candidates.

Cuts in recruiting teams have been made based on unrealistic promises from tech vendors. Rather than use technology to reduce staff roles, leverage tech to empower team members to do their best work. Choose tech products that give people more time to spend nurturing talent. You’ll see the benefits when you start attracting and placing top performers.

Enables hiring standardization

Standardization isn’t a four-letter word. Standardizing job descriptions and applications can make it easier for hirers to use tech in an assistive capacity.

For instance, hirers can rely on an automated system to scan a vast pool of diverse applicants in seconds. The standardization ensures the system won’t miss anyone, and the recruiters can take over once the pool of candidates is whittled down.

With the broad and specific ways in which data, ML, and the latest tech, in general, stand to disrupt our perceptions of staffing solutions, staffing agencies’ options are overwhelming. Too many tools that don’t complement one another only add to the confusion and slow the process down. Clunky, disconnected tech interfaces ruin any chance of recruiters getting the information they need smoothly.

That’s why it makes sense to invest in tech that enables hiring personnel to integrate their point solutions effortlessly and streamline workflows. And this is where the AI recruitment tool comes in.

Thus, AI Hiring Tool becomes the one-stop staffing agency solution

It’s one thing for staffing agencies to see AI coming our way in HR. Another thing is implementing the staffing solutions that harness it to improve sourcing and hiring success.

AI isn’t just on the horizon — it’s already part of some very forward-thinking recruiting and hiring programs. Given the tight job market, AI is a way to give organizations a tangible edge on the competition. It facilitates a far more accurate way to see a far greater range and depth of talent — which means it’s easier to find better candidates — and more of them. And AI enables hiring teams to make and maintain radically better connections with talent, garner a far better sense of fit over a whole spectrum of criteria, and, frankly, be more human than we’ve been in a long time.

Finds Talent

Imagine a scenario at your staffing agency where your ambitious recruiting team has been tasked with sourcing 250 new hires for a growing company. These are positions from entry-level to senior management, covering a whole range of functions. Tough task, especially when the budget is low and timelines are tight.

Using an AI-powered hiring campaign can save the day by automatically sourcing hordes of resumes of geographically segmented and promising candidates. Meanwhile, the team can also search within their existing talent pool with the ATS system integration – enabled by the same AI hiring tool!

In addition to the basic filters, the boolean search feature in AI hiring software brings the convenience of traditional candidate sourcing.

Makes Connections

Since AI tools do the heavy lifting of staffing agencies, the recruiting team has ample time to start sorting through the resumes of qualified candidates and reach out.

They can tailor their approaches to what they already know about these candidates — collected via AI — to make these vital first connections, using hiring events, social and mobile messages, and personalized emails. Put together prospective talent pools for each level of hire, and start digging into resumes to see if they’re coming up short or sourcing sufficiently. Here, again, the ATS integration comes in handy.

Since the whole team would be working on the same platform with access to the same information, they can quickly set up automated tasks for AI to complete that will help them pinpoint ideal candidates for each position, and they can start reaching out to candidates who stand out.

Tends to the Talent

Even before they start screening for skills, competencies, and experience, there are already conversations going on between prospective candidates and the hiring team. It’s not the hiring people doing the talking: there’s no phone tag or cumbersome emails. Instead, the candidates are engaging with a sophisticated virtual assistant.

Yes, AI-powered chatbots are also asking for seats at staffing agencies.

Candidates who show interest can do a pre-screening quickly with a chatbot, asking questions and getting a clearer picture of the position. Each conversation offers dynamic, responsive messaging and produces data on the candidate that the virtual assistant can share with the recruitment team.

In the time it might take to reach out and have one initial conversation with one candidate, countless exchanges have already taken place, and candidates are already engaged in the application process. A whole pool of candidates is entering the talent pipeline, already having a positive experience and interested in finding out what comes next.

Many of these candidates are digital natives, well used to interacting with chatbots, and at ease with the process — and to them, the process implies that the employer is appealingly forward-thinking in its approach to business and people. Now candidates can start having real-time conversations with the recruiting team, who already know a great deal about each candidate before they talk — and can tailor their conversations based on what they know.

Ensures cultural fit

With hundreds of positions to fill, there’s little time to spend on potentially poor hires. But AI can create predictive analytics on who may make the grade and be a great fit. A whole array of criteria is used to create screenings and pinpoint promising matches. The HR team can rely on the data to help narrow down the best candidates for each position and find candidates that fit other positions they may not have applied for.

In each case, the hiring team can take time to get to know each candidate, whether in conversation or formal interviews, as the human recruiters are freed up from repetitive and tedious administrative tasks now being executed by the AI software.

Keeps the Hiring Process Going

A study on LinkedIn^[8] found that key hiring trends include different kinds of interviews and conversations, adding more of a human side to the classic mano-a-mano. That may include online skills assessments — which may be built around the data AI has gathered already on candidates.

There are VR options for “trying out” the position in the virtual workplace, job “auditions,” video interviews, and far more casual interviews that set both interviewer and candidate at ease and allow for more meaningful and spontaneous conversations. Data intelligence has enabled recruiters to use their emotional intelligence.

Every interaction adds to the data gathered on each candidate and improves the recruiter’s understanding of that candidate’s relative strength and fit with regard to the company.

The benefits of AI recruitment tools are clear. They provide a comprehensive solution to the challenges of modern staffing. They can sift through vast amounts of data, identify the best candidates, and build strong relationships with them. They can also automate many more tedious and time-consuming tasks, freeing recruiters to focus on higher-level tasks. All this enables recruiters to spend more time with each candidate, establishing connections and relationships. The result is a whole crop of promising new hires who can help the organization continue its growth.

Key Takeaways

As the use of data, machine learning, and tech evolves further, a comprehensive staffing solution like an AI hiring tool is set to level the playing field of talent management. Staffing agencies that embrace these tools will be well-positioned to stay competitive. Else, those who do, will sit at the edge.

However, it is important to remember that AI tools should not replace human recruiters entirely. Instead, they should be seen as a powerful tool to augment their skills and expertise. By combining the power of AI with the human touch, staffing agencies can deliver a truly exceptional hiring experience for candidates and clients alike.

So, if you’re a staffing agency looking to stay ahead of the curve, there’s no reason to shy away from AI’s capability. Try out the demo today to see how it can benefit your business.

FAQs

What is a data-driven approach to hiring?

A data-driven approach to hiring involves leveraging data to inform and improve recruitment practices.

How do you use data to make hiring decisions?

Data can be used to identify top-performing employees, assess job fit, and predict candidate success.

How using a data-driven approach to hiring can enhance selection in companies?

Data-driven hiring can increase the accuracy and efficiency of recruitment, reduce bias, and improve candidate experience.

What is machine learning in recruitment?

Machine learning in recruitment involves using algorithms to analyze and learn from large datasets to improve hiring outcomes.

What is the use of AI and ML in recruitment?

AI and ML can streamline recruitment workflows, improve job matching, and reduce manual tasks for recruiters.

What are the benefits of using AI in hiring?

AI can help recruiters identify top candidates, automate repetitive tasks, and enhance candidate engagement.

What is a staffing solution?

Staffing solutions are comprehensive staffing software that provides end-to-end recruiting and hiring functionality.

Is going through a staffing agency worth it?

Staffing agencies offer many benefits, such as cost savings, reduced hiring time, and access to a broader talent pool.

What tools are recruiters using?

Recruiters use tools such as applicant tracking systems, sourcing tools, and video interviewing software to improve recruitment.

What is staffing agency software?

Staffing agency software is a specialized software designed to streamline staffing agency operations, including recruitment, scheduling, and payroll.

Resources

[1] https://businessolution.org/ai-in-recruitment-statistics/

[2] https://www.linkedin.com/pulse/rise-people-analytics-its-impact-hr-future-work-david-green/

[3] https://www.forbes.com/sites/bernardmarr/2018/04/27/what-does-gdpr-really-mean-for-hr-teams/#1d96a26030e0

[4] https://www.globalsign.com/en/blog/6-ways-gdpr-affects-hr/

[5] https://www.people-doc.com/hr-and-the-gdpr-everything-you-need-to-know-for-hr-compliance

[6] https://www.corporatecomplianceinsights.com/gdpr-fallout-employee-data/

[7] https://www.g2.com/articles/recruitment-statistics

[8] https://business.linkedin.com/talent-solutions/blog/trends-and-research/2018/4-trends-shaping-the-future-of-hiring