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Data-Based Decision Making

Rebecca Miller

Human Resource Development in Education

Dr. Graham


Importance of Data-Based Decision Making in the Recruitment Process

In modern society, it is hard not to hear about data-driven decision-making. The term alone has recently become something of a buzzword in business, and for an excellent reason. Data permits business owners to leverage the endless digital insights that are currently available at their fingertips and embrace the power of data-driven business intelligence to make more informed decisions that are better for the evolution and growth of the business (Webb & Norton, 2013). Today, data-driven business decisions are very much significant than ever before. And while sometimes it is best to go with an individual’s gut, most of an organizations’ decisions need to be based on metrics, facts, and figures that tie in with your aims and objectives. This will provide the firm with something solid to back up its management aims and business operations. With that, we know that the importance of data in the recruitment process need not be ignored. Traditional recruiting relied on intuition, guesswork, and lack more than data, which proved to be time-consuming to analyze and amass (Webb & Norton, 2013). Hiring teams and recruiters could only assume that their methods of hiring were effective. Today, with a wealth of analytics and software tools available in the market, any organization can create a data-driven recruiting process.

Data-driven recruiting utilizes tangible stats and facts to inform their hiring decisions, from selecting candidates to creating hiring plans (Webb & Norton, 2013). An organization’s recruiting team that uses data is more likely to be effective and efficient, improve their hiring process and even reduce the costs. As stated earlier, the hiring process until just recently had mainly been based on guesswork. With candidates, you could never really be sure if they were going to do a good job. Gut feeling and manual resume screening can only take you so far after all. So it should not be a surprise that up to 75 percent of all hires are bad hires. This unscientific approach brings about a lot of other losses. The hiring can, for instance, be overpriced, failing to meet the candidate’s expectations, and long. With an ancient recruitment process, an organization will interview many unqualified candidates wasting both the organization’s resources and time.

With a data-driven recruitment approach, however, a firm may make the whole process more efficient, significantly more manageable, and in the end, cost-effective. Below are some of the benefits of data-driven recruiting; First and foremost, data-driven recruitment eliminates gut-feeling decision making. We all know that any decision in business based on a gut feeling rather than rational and logical decision-making has a chance to backfire. While most candidates appear charming, it doesn’t mean they will perform well in an organization. So instead of making recruiting decisions based on candidates, likeability, and a resume, the hiring team may try utilizing data-driven recruitment (Kowalski & Lasley, 2010). Secondly, data-driven recruitment improves the quality of hires as the chances of making the right hires are high. It also decreases the time to hire, reduces the cost per hire, improves candidate experience, removes all kinds of bias from the hiring process, and finally improves forecasting.



Kowalski, T., & Lasley, T. J. (2010). Handbook of data-based decision making in education. Routledge.

Webb, L. D., & Norton, M. S. (2013). Human resources administration: Personnel issues and needs in education (6thed.). Upper 

Saddle River, NJ: Merrill.