HR analytics help teams better understand the movements and motivations of their workforce through the…
Much like the grain silo on a farm, the data silo houses a lot of information in one location. But unlike the farm silo, where you don’t want your wheat mixed with your barley, information-sharing between “silos” can be truly beneficial to an organization. Often unintentionally siloed, information-sharing between departments or team members can provide vital insights and create efficiencies when an organization centralizes its data.
Defining The Problem
The data silo problem in healthcare has different meanings to different people. If you’re a researcher in healthcare, it means large organizations across the public and private sectors don’t pool research to get a more comprehensive view of medical health issues. If you’re a patient, it means having to fill out forms for every place you go, from the hospital to the rehabilitation center to your doctor’s office, because healthcare service providers may use different systems.
The industry is segmented and complex, and the tendency to silo information presents an issue for healthcare recruiting as well. For recruiters, the data silo problem can pertain to recruitment data that serves its purpose for any single step in the recruitment process. Sometimes hiring information is recorded across multiple data systems or by different team members and it remains decentralized. Of course the talent acquisition team will share the necessary information to get to the next step in the process, but a lot of the resources needed to create meaningful strategies down the road remain untapped. When your recruitment data is all over the place, it makes it difficult to analyze—and this means that one of your most valuable resources in recruitment (the data) remains underutilized.
An Example In Action
Consider the applicant tracking system, which conveniently stores applicant data and ultimately helps narrow the field of applicants by screening resumes. While its focus may be to score applicant data for a specific job, the data could have broader implications. Which sourcing strategy proved to be the most effective and efficient to get the best applicants? Which applicants for one job make quality candidates for a new opening? The data points in the hiring process can even connect further by tracing new hire turnover back to its source. Wouldn’t it be nice to predict a candidate’s staying power and quality of hire before they start?
Join Your Silos To Find Success
In order to create meaningful insights in your hiring process, you need to pool these information silos together. This is a pressing issue for healthcare recruiters. Your industry is siloed in general, and you're also facing a rising talent shortage. Programmatic platforms like Pandologic’s PandoIQ can centralize your recruitment data into a reporting dashboard. While the technology uses historical data and machine learning to optimize the recruitment process (and does so automatically), it can also provide hiring managers an aggregate view of your hiring needs. It can distribute your spending across all job campaigns in order to prioritize hard-to-fill positions, while continuing to optimize the process for every open position based on your budget.
Centralizing the information between campaigns for different open positions, no matter how many recruiters work on each, no matter how many vacancies there are, can really optimize your budget by automating the budget allocation.
Make Your Process As Streamlined As Possible
By pooling data, a programmatic platform is also better able to make predictions—the more data, the better. The more factors that can be analyzed together, the more strategic and comprehensive your hiring strategy will be. While a hiring manager may know intuitively to prioritize a hospital administrator vacancy, the data on turnover rates in the ER nursing staff may also indicate that this area of the hospital and its staffing needs extra special attention.
The main benefit of a programmatic platform is the time you save and the cost-efficiencies. With a centralized data system, you can see the broader landscape and make smarter decisions.