How Big Data Has Changed the Headhunting Game

Big data is both a science and a practical application based on the concept of harvesting as much data as is humanly possible and then figuring out how to use it. In its earliest days, big data was taking in exponentially more than it was putting out. But the tide is changing. We can see the progress it has made by observing its influence on the headhunting game.

Headhunting is a term used in the HR sector to describe actively recruiting job candidates who might not otherwise be looking to switch jobs. Tech industry recruiters have been doing it for years. Headhunting is big in the healthcare sector as well, especially since the onset of the COVID pandemic. Staffing shortages made worse by the pandemic have forced recruiters to pull out all the stops in search of candidates.

Big data plays a crucial role in their efforts, according to healthcare marketing company iMedical Data. As part of the Healthcare Staffing Innovations family of online properties, iMedical Data has access to high-quality, first-party data that is vetted through healthcare organizations and pharmaceutical companies. Headhunters rely on their database of healthcare providers to do what they do.

Success Is in the Details

Big data’s greatest weakness is also the key to its success, at least when utilized properly. The weakness in question is volume. Big data’s model revolves around harvesting data indiscriminately. It then has to be analyzed and sorted through to determine what is valuable and what is not. Doing so can be a formidable task.

Using iMedical Data as an example, they glean data from a variety of healthcare job boards. All their data is provided by visitors who actively opt into data sharing. From all the harvested data, iMedical Data is able to provide specialized datasets pertaining to doctors, nurses, therapists, etc.

They have enough data to meet the needs of most headhunters. But headhunters do not necessarily want all the data they offer. Headhunters want specific datasets pertaining to specific kinds of candidates. iMedical Data can furnish those datasets because they have so much data to work with.

In short, success is in the details. You harvest as much data as you can and then comb through it to find the details you need for your particular application.

Targeted Recruiting Equals Better Results

From the headhunters perspective, big data’s value lies in being able to conduct targeted searches. If a headhunter knows exactly the types of candidates a client prefers, they can base their search exclusively on those unique characteristics the client is after. They do not waste time researching candidates the client is unlikely to hire.

What would clients be looking for? It could be anything. The hospital might insist on hiring only advanced practice nurses with so many years’ experience in a given specialty. The more specific the requirement, the more valuable high-quality data becomes. Narrowing down all the advanced practice nurses to just those who have the required years of service allows the headhunter to put their resources to use in the best possible way.

Thank the Internet

It turns out that we have the internet to thank for all of this. Think about it. Data is useless if it cannot be shared easily. If nothing else, the internet facilitates easy data sharing by connecting the entire world through a series of global networks. The internet has made data harvesting an enterprise we never even considered 50 years ago.

Headhunting is alive and well today, especially in the healthcare industry. And thanks to big data, it is a lot more productive in the modern era.

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