How to Optimize the Front-Line Employment Value Chain
Even as recently as six or seven years ago, most hiring for in-store, consumer-facing roles happened when companies placed ads in a local newspaper and candidates sent in resumes through the mail. That began to change as use of the Internet gained traction.
Today, as we celebrate the 25th anniversary of the World Wide Web and online platforms have matured — with nearly 200 million smartphones active in the US — the recruiting and hiring process continues to evolve, particularly for front-line employment.
The key question then becomes: how can all us work together to optimize the front-line employment value chain?
In addressing that question, there is no doubt that we collectively benefit from the scope, functionality, and growth of online talent platform retailers. The biggest impact of these tools stems from their ability to better match individuals and local-level work opportunities. The catalyst of this movement is a skills shortage for front-line roles, and the result is improved access to a broader and more diverse pool of candidates and worker employment opportunities using sophisticated search capabilities.
Bringing Data to Hiring: How Does it Work?
New startups and mid-market firms are developing software-as-a-service solutions that transition the entire hiring process online, powered by sophisticated algorithms. Hireology.com is one great example. Through the use of software, HR departments can now employ analytics-based hiring to optimize each step of the employment value chain from application sourcing, candidate screening, performing background checks, recording interviews, and even sending candidates series of tests and evaluations regarding competence, work ethic, social intelligence and wage expectations.
The goal here is to ameliorate human biases in each stage of the hiring process, which often leads to dismissing qualified candidates. Now, with advanced technology, many companies are working to find solutions on how to hire front-line workers through analytics as employers increasingly harness a data-driven approach to selecting candidates that fit the role.
How This Benefits the Front-Line Consumer-Facing Industry
When using data and analytics to aid in hiring for entry-level positions, the “automation” differs from when screening for more skilled and experienced candidates. Automation in hiring for retail, quick serve restaurants, healthcare, construction and manufacturing, and customer service positions is more focused on assessing soft skills and personality through testing, instead of traditional skill matching and experience.
Due to the high turnover rate of workers in these types of industries, finding candidates who have the right attitude, character, and work ethic are the most important factor for new hires, and could decrease turnover rates. This new approach could also work in favor of candidates with little to no employment history, since it focuses on soft skills and cultural fit, as opposed to hard skills they may be lacking. This is good news for entry-level position seekers because it makes skills the more relevant dimension of selection as compared to prior in-role employment experience.
The result is now allowing workers and employers alike to conduct more efficient and detailed searches and make more informed choices, reducing the risk of a bad match for parties on both sides. Moreover, greater specialization of search allows for smarter calibration of the type of employment from full-time to contingent or even contract work.
A Move Towards Greater Information Sharing
By taking a skills-driven approach to hiring, especially for entry-level positions, corporations can better match localized supply and demand. As corporations begin to collect and track data on what a successful entry-level front-line employee looks like on the local level, this information will need to be shared throughout all levels of a company, and across consumer-facing industries in order to create the “perfect candidate” profile. This type of information includes distributing centralized data as relating to employee success and what makes a good candidate for specific roles. Sharing data throughout a company and across industries can help to get a comprehensive understanding of the talent that’s needed, and the types of candidates that best fit certain roles.
Empowering Both Companies and Candidates
Online talent platforms can transform the way individuals navigate the world of work and empower companies to select better candidates. Their applications offer distinctive value for front-line service roles like quick services and hospitality. In these sectors, we will see increasing local level labor force participation and reduced unemployment, and in the process improved store-level productivity and profits.
These dynamics will fundamentally change the way employers approach talent sourcing and candidate evaluations over the next decade. This shift, no doubt, will have profound implications for both employers and candidates alike and, in the process, help to optimize the front-line employment value chain.
Resources: (1) Can an Algorithm Hire Better than a Human? (2) We Can Now Automate Hiring. Is that Good? (3) Will Computer-Automated Hiring Ever Become the Norm? (4) Increasing Employment Opportunities for Disadvantaged Adults
