In anticipation of HR Technology Conference and sessions of Women in HRTechnology, we recently sat down with John Pensom, our CEO and Co-founder, to quickly talk about the state of Diversity and Inclusion in the workplace, and how data and analytics will help organizations measure up.
John Pensom, on 23.8.2018
For the past 3 years, most HR Tech vendors have claimed reporting and analytics are actually "embedded" in the newer releases of their transactional solutions.
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.
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.
