BLOG: Data Driven Workforce

Jennifer Hanniman

Jennifer Hanniman

Recent Posts by Jennifer Hanniman:

4 Ways to Better Hiring Results With Analytics (Part 4)

We’ve shared with you the first 3 steps to getting more out of your Candidate data by tying your analytics to hiring results and diving into the data. (See Parts 1, 2, 3 here if you're getting caught up.) Today I want to share with you the final step - Step 4 - Refine The Results.

Once you review and share the initial results, you will likely want to further refine the analytic views to tailor to your needs. 

 

4 Ways to Better Hiring Results With Analytics (Part 3)

In the last two blog posts I shared the first step in getting more out of your candidate data by tying your analytics to hiring results (Part 1, Part 2). Today I want to share with you Step 3 - Dive Into the Data.

If you are cringing when we mention data, take a quick step back to understand what data is actually needed in order to do the analytics. To be able to use candidate analytics, the focus needs to be on collecting the data required to analyze the stages and segments that are important to your business. If cleanup is required, focus on the key segments first and gradually move to the next step.

There are three types of data required to be able to analyze the volume and conversion rates in your candidate pipeline: candidate pipeline process data, requisition data, and candidate data.

4 Ways to Better Hiring Results With Analytics (Part 2)

Last blog post I talked about the importance of tying your analytics to hiring results - and in this post I want to dive a little deeper into this area.

Step 2: It’s all about the stage...

4 Ways to Better Hiring Results With Analytics (Part 1)

It can be a challenge to clearly understand where to invest to improve how you attract, progress and hire quality candidates. While there’s a ton of data available it isn’t always the right level to inform decisions. A deeper look at your candidate data can tell you where to focus your attention and investment to deliver timely, predictable, high-quality hires to the business. 

Analytics can help. But how can you get started when your team already seems maxed out with their daily activities and you cringe just thinking of the state of some of your data?