4 Innovative Strategies For High Volume Hiring

McDonald’s made headlines recently in their high volume hiring of 250,000 employees for the summer. Job seekers can apply on McDonald’s Snapchat career page via 10-second Snaplications.

McDonald's high volume hiring using Snapchat

This is just one example of how companies are responding to the growing challenge of attracting, hiring and retaining talent for high-demand, high-turnover roles in today’s tighter labour market.

If large, established companies like McDonald’s are innovating their application process and candidate experience, it’s clear we all need to step up.

Here are 4 innovative strategies to optimize your high volume hiring. First, a brief introduction.

High volume hiring

High volume hiring is the practice of hiring for a large number of open positions in a given time frame. This can range from hundreds to thousands of positions a year.

Common in industries such as retail and hospitality, the need for a large volume of new employees can be due to seasonal hiring, new store openings, or rapid growth in the organization.

Jobvite reports that while the average job posting attracts less than 50 applicants, the average high volume hiring attracts more than 250 applicants.

high volume hiring attracts more than 250 applicants

This means the main challenge for high volume hiring is the time spent screening and shortlisting candidates. Keeping your high volume hiring process short and sweet – for both candidates and recruiters – is the name of the game.

Strategy #1: Create a “candidate-first” job application process

Indeed found 42% of job seekers found lengthy applications the most frustrating part of the application process.

So while McDonald’s Snaplications may seem silly at first glance, they’re being very smart by creating a super speedy (and mobile) application process.

Best practices for a “candidate-first” job application for high volume hiring include:

  1. Be where your candidates already are: Whether that’s Snapchat, Reddit, or LinkedIn.
  2. Make sure your application is mobile-optimized: According to Indeed, 65% of job seekers use their mobile devices to look for jobs. The ability to apply on mobile is especially important for hourly workers who might not have access to a desktop computer. Being mobile-optimized includes a job application site that’s both mobile-friendly (no more pinching the screen!) and allows job seekers to upload their resume using their phone.
  3. Keep it short: If possible, reduce candidate friction by creating a 1-click application process. If that doesn’t work for you, keep your qualification questions to a minimum (e.g., five and less), enable social profile apply, and pre-populate text boxes as much as possible.

Strategy #2: Speed up your sourcing with talent rediscovery

Talent rediscovery is the practice of mining your existing resume database to find previous candidates for open reqs.

A CareerBuilder survey found that one of the biggest complaints employers have about their recruiters is the failure to look at candidates in their own database. This complaint is a bit unfair when you consider that a typical ATS just wasn’t designed to have this type of internal search functionality.

Although your ATS may allow you to use keywords and Boolean strings to search through existing resumes, the results are usually limited and error-prone. This makes it difficult or even impossible to match previous applicants to an open req, unless you’re using a dedicated talent rediscovery tool.

This type of technology works by you entering a job description of a current req and the talent rediscovery algorithm will automatically screen every resume in your ATS to find the most qualified matches.

Strategy #3: Use technology to automate resume screening

On average, 75% of the resumes a typical high volume job posting receives are considered unqualified.

When you’re hiring for thousands of open positions a year, this adds up to hundreds of wasted hours skimming through unqualified resumes. While screening hundreds of resumes can be mind-numbing for human recruiters, it’s exactly the type of pattern matching AI was designed for.

Software that use AI to screen resumes analyzes the resumes of existing employees to learn the qualifications of a job and then ranks and grades new candidates who fit the criteria (e.g., from A to D).

Using AI for high volume hiring makes sense because AI requires a lot of data to be accurate. By automating manual resume screening, organizations such as retailers have reduced their time to hire by 75%.

In his Forbes article on how AI is being used in retail, Bryan Pearson of LoyaltyOne notes reducing time to hire gives high volume retailers a better chance of winning the best talent.

Strategy #4: Use recruiting metrics to find shortcuts

High volume hiring is a problem of scale so you need to be sure you’re optimizing your time and spend where you can.

Recruiting metrics are essential for understanding where process improvements are needed and justifying investments into specific recruiting functions.

Some recruiting metrics you can use to find shortcuts in your high volume hiring include:

  1. Track source of hire to optimize advertising spend: Silkroad’s data finds the most common source of hire are job boards and aggregators, which account for 31% of hires. Get granular by assessing which job boards and aggregators lead to more hires and invest more money into them while dropping underperforming sources.
  2. Track conversion rates to eliminate unnecessary steps: LinkedIn’s interview process for customer success representatives used to include three interviews. The first interview was a phone screen with a recruiter who rated candidates on a scale of 1-3. When their data showed 90% of candidates who scored a 3 in their phone screen made it to the final interview round, they eliminated the second interview for these candidates.
  3. Create multipliers where possible: Efficiency is crucial for high volume hiring. Multipliers during the recruiting process include asking candidates to apply with their friends and conducting in-person interviews in groups.
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Ji-A Min

Ji-A Min

Head Data Scientist at Ideal
Ji-A Min is the Head Data Scientist at Ideal. With a Master’s in Industrial-Organizational Psychology, Ji-A promotes best practices in data-based recruitment. She writes about research and trends in talent acquisition, recruitment tech, and people analytics.
Ji-A Min

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