I am always struck by how many companies fail to track their readily available data. This data offers cost-saving, productivity-enhancing, and revenue-generating information for the picking. If only someone would look.
While today’s applicant tracking systems and AI powered chatbots can track and harvest much of the data I speak of, HR departments without the most up-to-date platforms, can still harvest their data using Excel sheets and simple data sets.
Data justified a new, faster recruiting model.
One company I worked with was hopelessly behind in their recruiting. Their recruiting model suffered from uninformed neglect and resulted in needless cost and inefficiency to the business. They used one recruiter and administrator and an army of third-party search firms to find engineers, clinical researchers, and regulatory affairs specialists. Every department paid for the cost of their job posting ads and third-party search firm fees.
I began collecting data on the time-to-fill open job requisitions by the department. It showed that some departments were taking more than 120 days on average to fill a job requisition. (A few were at six months!) The departments with the longest time-to-fill were the departments that would make or break the development of a new game-changing product for the business. Each month of staffing shortages pushed out by two months the day the product would be available for sale.
I next gathered the cost being spent on recruiting by each department, including job ads and third-party search firm fees. I also included the current number of job openings by department and added to this number the number of replacements that would be needed due to turnover.
With this data, I was able to pitch top management that with the investment of three recruiters and by centralizing the purchasing of ads in HR, we could purchase ads at higher volume and save costs, use third-part search only for executive searches, and hire faster, at less cost per hire, and reduce turnover. I promised them a 25 percent reduction in costs-per-hire and a 50 percent reduction in time-to-fill, and a 25 percent reduction in turnover as a result of better screening.
They approved my proposal in ten minutes. In six months, we achieved our goals. At the business level, the organization was able to stop pushing out the release date of its new products due to staffing shortages.
All of this was achieved without big data analysis powered by artificial intelligence. My weapon of choice was simple, easy-to-read excel sheets, mimicking the format used by our Finance team, so everyone could quickly read the data and understand the advantages.
Today’s AI makes data literacy easier and provides better employee experiences to build an employer brand and reduce unconscious bias.
I am all about being an HR and recruiting leader of the times. I advocate using the same digital tools marketing departments have been using to build customer brand, find and attract new customers, and capture valuable data. These are the tools of the day: chatbots, big data sets analyzed by artificial intelligence, and block chain. These tools are available to HR in today’s contemporary applicant tracking systems, job applicant hunting and candidate matching software, and chatbots.
Using these tools is not difficult. HR does not have to use Excel as in my example above. Besides, these digital tools can find and attract more job applicants, communicate with them instantaneously and thereby builds employer brand by not having applicants felt left in the dark. The AI in these tools can gather valuable data on your best recruiting sources (such as LinkedIn or Indeed posts), the best universities for recruiting, and your best tracking metrics, such as time-to-fill.
In an era when our awareness of unconsciousness bias in screening and hiring decisions has been significantly raised, these tools empower HR leaders. These tools help them see if women, veterans, or people of color are being disproportionately rejected in various stages of the recruiting process, such as the initial basic qualifications screen, recruiter screen, manager screen, and the ultimate hiring decision. This judgement is hard to make on hunches or by casual observations of trends. However, armed with an extensive data set and AI that can identify the trends, the departments or hiring managers who disproportionately reject women or people of color can be identified, allowing HR leaders and executives to investigate.
Whether using little tech or big tech, the case for HR and recruiting leaders’ data literacy is overwhelming. Not only does it improve recruiting and HR, but it also enhances the business’s ability to generate profitable growth with smart investments, leaner processes, faster hiring, and lower turnover. Besides, the HR leader who can use HR tools and analytics to drive business growth gets a seat at the table.
I invite you to join the JobSync’s Recruiting Roundtable discussion on the case for HR data literacy this Thursday, August 27 at 8:00 AM PT. Piyanka Jain and I will lead the discussion. I will raffle off to attendees’ copies of my book, “Hack Recruiting: The Best of Empirical Research, Method and Process, and Digitization.” Register here.
Victor Assad is the CEO of Victor Assad Strategic Human Resources Consulting, managing partner of InnovationOne, and Sales Advisor to MeBeBot. He works with companies to transform HR, implement remote work, recruit executives, and develop extraordinary leaders, teams, and innovation cultures. He is the author of the highly acclaimed book, Hack Recruiting: the Best of Empirical Research, Method and Process, and Digitization. Subscribe to his weekly blogs at www.VictorHRConsultant.com.