Before online job applications were a reality, job seekers had to fill out physical forms to answer work history, assessment of skills and more. Job seekers and hiring managers alike surely loved to do away with paper trails that the internet made obsolete, but it still took some time before applications became more user friendly. The paper application with dozens of fields to fill out remained largely the same, only it could then be done on a computer, said Kurt Heikkinen, president and CEO of Montage, a hiring software company based in Delafield, Wisconsin. It would often take 30 minutes or more to fill out an application, and many job searchers would drop out of the process.
“The expectations of the modern candidate have really changed the need for organizations to alter what they ask for and where in the process they ask for that information,” Heikkinen said. “Candidates have more power and control than ever before.” Therefore, the application process must be fast, easy and transparent, or potential talent will take their services elsewhere.
Now, employers are finding that they can simplify applications to save time and effort for all parties involved. One way to do this is to collect information as needed, capturing enough data up front so the employer has an initial snapshot of the candidate to then make a decision to further engage in the interview process, Heikkinen said. These data points include the minimum job requirements and availability, motivations and interest in the role and potentially other areas not directly in the employer’s application but found elsewhere online: LinkedIn profiles, coding challenges, thought leadership and blogs, Heikkinen said.
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One reason for the change in strategy is to reduce candidate frustration. If one question knocks the applicant out of the process, why should they answer dozens of other questions? Instead, the data gathered should be a series of natural interactions that appear to be logical, transparent and progressive for the candidate, Heikkinen said.
“Recruiting organizations are notorious for front-loading data collection,” said Sahil Sahni, co-founder of AllyO, an AI recruiter startup based in Sunnyvale, California. He shared that he’s seen job applications that ask for a Social Security number up front, ask 290 questions or request 10 years of employment history. “None of that needs to be front-loaded,” he said. Instead, the application process should ask for the minimum amount of data to push on to the next step of the process. “People will only stay engaged when you maintain a very optimal give-take ratio,” Sahni said. If the application asks too much of people up front, they will drop off; instead, companies should ask for what’s needed to keep engagement high and the process smooth.
Collection of data in the hiring process can provide business leaders with visibility into their process. For example, if a hiring manager requested that candidates have five years of experience, but a large portion of applicants have four years and thus miss out on the opportunity, then the data can help the manager adjust their ask and increase the volume of candidates, Sahni said.
Recruiting and HR functions should be looped into operational decision-making more than traditionally, Sahni said. “Everything, if you think about it at large from a business goal standpoint, translates into hiring needs, either in terms of retaining existing employees or in terms of hiring new talent,” he said. By having these teams talk across silos with other departments about their hiring needs, all can be more aligned when trying to attract top talent. Teams should communicate to understand how to find the right person for the job.
Data can also provide visibility into the areas of hiring that are not optimized, such as where advertising dollars are spent, reducing frequency of applicants dropping out of the process and more, Sahni said. The ability of HR leaders to have that data is extremely valuable. “It allows them to have the armor and talking points that allows them to capture more value within the business,” he said.
But what to do after collecting the data? Sahni said that keeping data is a good idea, as long as it can be used constructively, such as for finding indicators of success or re-engaging with past candidates. Storage of data is not much of an issue with modern technology, but it certainly should be deleted upon request, he said. “In every case, the data should be protected with the best measures.”
Lauren Dixon is a senior editor at Talent Economy. To comment, email firstname.lastname@example.org.Filed under: Talent EconomyTagged with: acquisition, AI, data, Hiring, recruiting, talent