The Growing Use of 2 New Recruiting Automation Tools

The Growing Use of 2 New Recruiting Automation Tools

The Growing Use of 2 New Recruiting Automation Tools

July 27, 2023

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Key Takeaways

  1. AI and Data-Driven Recruiting are two related recruiting automation concepts in talent acquisition and recruitment
  2. ATS is any piece of software that automatically scans and assesses resumes during the initial stages of the hiring process
  3. Data-driven recruitment is any hiring strategy that utilizes data sources to help find a qualified candidate
Summary

 

 

Current statistics show that a majority of companies already incorporate AI into their recruitment strategy in some form or another, with the number rising rapidly each year, but how much do we really understand the processes involved? While it can speed up hiring, what can companies do to ensure these recruiting automation tools are incorporated and used in the best ways possible?

In this article, we look at two of the biggest ways to incorporate recruiting automation into a hiring strategy and hiring processes and compare the pros and cons of these approaches. Finally, we’ll give you some top tips from one of our recruitment experts on improving your hiring using technology and how to keep the “human” in your Human Resources department even when using AI or data to boost your efficiency.

 

Understanding Recruiting Automation with AI and Big Data-Driven Recruiting

 

Recruiting Automation and Data-Driven Recruiting are two related concepts in talent acquisition and recruitment.

 

Recruiting Automation

 

This is the use of technology and software to automate various aspects of the recruitment process. It may traditionally involve using multiple tools and systems to streamline and optimize recruiting tasks, increase efficiency, save time, and reduce manual effort. However, some companies now offer HR systems that integrate every stage of the recruitment process into a single platform.

Some common examples of recruiting automation include automated job postings, resume screening using AI algorithms, automated replies, and AI-assisted scheduling.

Recruiting automation can help HR professionals and recruiters focus on more strategic and high-value tasks, such as candidate engagement, building relationships, and evaluating cultural fit. By automating repetitive and administrative tasks, you can improve your overall recruitment speed and effectiveness.

 

Data-Driven Recruiting

 

This involves using data and analytics to drive decisions in the recruitment process. It emphasizes collecting, analyzing, and interpreting relevant data to make informed decisions about candidates. It relies on gathering data from various sources, such as applicant tracking systems, candidate assessments, social media profiles, and performance metrics.

Data-driven recruiting enables you to gain valuable insights into your recruitment processes and outcomes, and by analyzing the resulting data, recruiters can identify trends, patterns, and correlations. These patterns can help to optimize your later recruitment strategies, improve candidate quality, and enhance overall talent acquisition efforts.

Overall, recruiting automation and data-driven recruiting can be complementary approaches that streamline and optimize the recruitment process through technology. By combining these approaches, you can make recruitment efforts more efficient, effective, and data-informed.

 

 

AI in Recruiting: The Pros and Cons of an Automated Applicant Tracking Systems (ATS)

 

Hiring and tracking applicants is more complex than ever before, thanks to the global reach of recruitment platforms. Hiring managers and recruiters must often now evaluate hundreds of candidates from around the world to find the proverbial needle in a haystack.

So, for a quicker process, recruiters and hiring managers can now turn to recruiting automation software and digital tools, including Applicant Tracking Systems (ATS), to improve almost every aspect of the recruiting process.

ATS is any piece of software that automatically scans and assesses resumes during the initial stages of the hiring process. More and more, this means using systems with elements of recruiting automation to help with the storage and sorting process. This type of system quantifies mass amounts of data and allows you to remove unqualified or unrealistic candidates quickly.

 

The Pros of Using AI through an ATS      

 

ATS software allows you to automate various tasks of the hiring process that can save you a lot of time, and free up your recruiting personnel for other high-value tasks. By posting to multiple job boards, tracking candidate applications, and automating interview setup and feedback, you can increase overall screening speed and quality through standardization.

According to INS Global’s own recruitment team, simply arranging interviews can be one of the lengthiest parts of the process. However, with even a small element of recruiting automation, this can be significantly shortened.

An ATS can also track the performance of your recruitment team through recruitment metrics. This helps you to optimize your recruitment process in the long term. An essential part of this may be using an ATS to measure the efficiency of different job boards in providing suitable candidates. With some job boards including expensive paid posting options, knowing you are getting your money’s worth is essential.

Not only does an ATS create more efficient workflows, but it can also improve the quality of your shortlisted candidates. First, you can cast a wider net by posting on job boards with standardized messaging to attract more candidates. Second, automated filtering highlights the candidates that tick the most boxes. Finally, you gather more insightful information that can be adapted to your specific needs, so your recruiters make a well-informed decision.

The best candidates on the market likely find themselves with many opportunities, and it’s highly probable that recruiters are reaching out to them already. If you have a streamlined hiring process using recruiting automation to speed up repetitive steps, a candidate is likelier to stick through it. If your hiring process is long and complicated, they may just move on to the next potential employer.

Ultimately, the entire process is strengthened and improved from an early stage.

 

The Cons of Using AI to Manage an ATS

 

While it might seem like an AI-driven ATS could reduce bias, in fact, the opposite is also possible. Using the wrong combination of keywords or allowing AI programs to learn using faulty data sets, algorithms may favor certain candidates above others based on discriminatory criteria.

You have to be careful when setting your recruiting automation software filters to recognize common keywords around roles and responsibilities. Even small mistakes here could mean that you end up filtering out good candidates with atypical experience or lacking specific variations of keywords. Careful consideration of your filters ensures you aren’t unknowingly removing good candidates.

Finally, when automating responses to candidates, your messaging may feel less personalized and can come off as robotic. It can take time to find a good communication template that can be sent en masse yet feel personalized.

 

Big Data in Applicant Tracking Systems (ATS): The Pros and Cons of Big Data in ATS Management

 

Data-driven recruitment is any hiring strategy that utilizes data sources to help find a qualified candidate. Traditional hiring methods may rely heavily on intuition and gut feelings when selecting a person for a role. However, recruiting automation with data-driven analytics means much of the guesswork is removed as recruiters can use data to help make effective hiring decisions.

When done consistently and methodically, data analysis in recruitment can help sort out better candidates and improve hiring plans for a company in the long term.

 

The Pros of Big Data in ATS

 

With a recruitment process that manually sorts resumes and holds seemingly endless interviews, many hiring decisions are based on subjective concepts or internal biases. Additionally, many people will put on their best faces simply to receive an offer, making objective decisions difficult. Data-driven recruiting automation minimizes risky hiring decisions based primarily on the candidate’s likeability factor and shifts the hiring decisions to the company’s needs.

When your company needs to fill a role, the obvious goal is to find the best candidate to boost your company’s short- and long-term performance. Traditional hiring methods may make this harder because it is hard to gauge how well a person would perform once in the role.

Data-driven recruitment considers an applicant’s experience more over the long term, so you have a better chance of making a more analytical and insightful choice. It also builds data pipelines over time, improving your choices in the future.

Streamlining the hiring process by removing unnecessary steps can lead to a much more affordable hiring process by cutting out time and quickly shortlisting the best-qualified candidates from the pool.

 

The Cons of Big Data in ATS       

 

Most ATSs offer the same applicant experience: fill out a form, attach a resume, attach a cover letter, and wait. In most cases, this is the only touchpoint the applicant ever has with an organization, as there is rarely any feedback, and the application may simply end without notification.

Understandably, most employers don’t have the time to give applicants specific feedback. However, creating a negative company image is easy if the application process does not feel human. While this can be said of both AI and a data-driven recruiting process, too much reliance on big data analytics can quickly make you overlook someone based on data points when their human experience is important.

A big disadvantage of big data is that most ATSs start by trying to turn people into numbers. This could be things like the date they applied, the number of failed knock-out responses, or the job ID.

A hiring team then sorts through these data points and may add notes. The problem is that this may still leave the final decision to a combination of luck and instinct.

Even if your hiring team has properly reviewed all of the resumes in detail at this stage in the application process, they may still misunderstand the candidate pool (or market if you are looking abroad) well enough to make good decisions. They may lack basic information on the other ‘dimensions’ of applicants, such as personality, cultural preference, and aptitude for skills required in the role.

 

 

AI vs. Big Data in Recruiting Automation

 

 

Aspect AI in ATS Big Data in ATS
Data Processing Pros: Pros:
1. Efficient candidate matching 1. Comprehensive candidate insights
2. Faster resume screening 2. Enhanced candidate search capabilities
3. Automated interview scheduling 3. Identifying hiring patterns and trends
4. Reduces human bias in decision-making 4. Better predictive analytics
Cons: Cons:
1. Potential bias in AI algorithms 1. Privacy concerns with large data collection
2. Difficulty in explaining AI decisions 2. Data quality issues over time
Candidate Experience Pros: Pros:
1. Personalized communication 1. Tailored recommendations
2. Quick response times 2. Improved candidate engagement
3. Automated status updates 3. Streamlined application process
Cons: Cons:
1. Lack of human touch in interactions 1. Potential for impersonal interactions
2. Technical glitches or errors 2. Overreliance on algorithms
Costs Pros: Pros:
1. Long-term cost savings 1. Efficient resource utilization
2. Reduces manual HR staff time 2. Potential cost reduction through optimization
Cons: Cons:
1. High initial investment 1. Costly infrastructure and maintenance
2. Costly to train and retrain AI models 2. Expenses associated with data management

 

 

3 Ways to Better Integrate Recruiting Automation into Your Global Recruitment Process: Advice from an INS Global Recruitment Expert

 

Standard questionnaires

 

From the moment candidates apply, they can be asked to answer 8 to 10 questions that help your team filter them. A short and simple questionnaire at the beginning of the process can be the best way to sort candidates based on your needs quickly.

By automating the system, you can also automatically contact unsuitable candidates to provide quick feedback and request their permission to keep their details on record for future opportunities.

 

Use Chatbots for Consistent Candidate Contact

 

Chatbots can be integrated into your global recruitment strategy to provide immediate engagement with candidates, answer frequently asked questions, and collect basic information. Chatbots also enable round-the-clock availability, ensuring that candidates receive timely responses and assistance, regardless of their time zones. Using chatbots, you can provide candidates with a seamless and efficient experience and ensure consistent communication throughout the process.

 

Work Closely with Your Recruiters to Customize the Recruiting Automation Tools According to Your Specific Needs

 

Tailor the algorithms, models, and features to match the specific requirements of your global recruitment strategy. This customization allows you to adapt the AI tools to your organizational culture, industry, and candidate profiles.

Using template storage models like collection forms or technical assessments per position to organize candidate information allows you to quickly store and use information during the recruitment process and as part of a good talent pool.

Even if questionnaires or templates are not sent automated, they can help your team save time. Every document can be integrated into the ATS as long as parameters are set early.

 

The Best Data and AI Recruitment Tools Right Now

 

These recruiting automation platforms use AI to help you find and qualify candidates based on skills, experience, and other factors. The right tool can screen candidates, assess them based on their skills, personality and other factors, and help you make more informed decisions.

 

Zoho Recruit

 

This cloud-based candidate tracking system supplies companies with complete recruiting automation solutions. Its AI recruiting automation software also uses chatbots to communicate with candidates in real time.

 

TurboHire

 

It is an intelligent recruitment platform based on deep data processing that can create personalized interviews, automated test assignment recommendations, Chabot evaluations, and candidate rankings.

 

Toptal

 

This platform contains data on professionals specializing in machine learning, end-to-end development, blockchain, design, AI, financial and project management from around the world that companies can hire in up to three weeks.

 

recruiting automation

 

Why INS Global’s Tech-Driven Approach Can Boost Your Global Hiring Strategy

 

International recruiting is difficult for businesses of all shapes and sizes. It takes a lot of time and funds, resources that might not always be available. To ensure that you hire the best local people in your target market while maintaining strict regulatory compliance, you have to think outside the box.

As with anything that uses AI, recruiting automation integration will also be better than a total replacement of the human element. Finding the right way to integrate recruiting automation tools and approaches means having the right expertise and experience, and INS Global can help you.

INS Global provides market-leading recruitment outsourcing solutions to meet all your demands, so you will always receive the best recruitment services while consistently ensuring that your recruitment complies with local regulatory needs.

We help companies meet their recruitment and expansion goals in more than 100 countries worldwide and offer experience and specialized knowledge at every stage, from writing a job description to onboarding and beyond.

Contact one of our global recruitment professionals today to learn how we can assist you and start recruiting immediately.

 

 

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