Source | www.concur.com | Stela Lupshor
People analytics is a hot business topic and rightfully so. Organizations need to leverage the plethora of data that’s generated today to glean patterns about untapped talent potential, ways to positively impact productivity, and opportunities for growth and innovation.
Analytics practitioners often focus only on top-level data sources (sales quotas, expenses, performance ratings, etc.). However, there are new types of data and ways to analyze them that can provide insights to help keep your employees happy and productive. Organizations that don’t examine patterns about the largest part of their balance sheet – their people – will be left behind in retaining and developing employees, influencing business outcomes, and potentially surviving in the long run.
As a relatively young field, there are many misconceptions about people analytics. Here are three of the biggest myths and what you need to know as your organization dives into the data:
Myth #1: People analytics involves just one kind of analytics
While people analytics can be performed through many frameworks, there are three general categories of analytics work.
- The foundational analytics gives your organization a consistent language to understand workforce dynamics and detect early signs of issues to investigate. This foundation should have the following elements at its core:
- A “golden copy” of high-quality workforce data, which includes historical trends to help you answer “What has happened or is happening now?”
- Standard measurements and definitions based on that data (headcount, turnover, hiring, movement, diversity, etc.) that enable business leaders to understand, in a consistent and repeatable way, how well they are managing the workforce. These measurements can help you identify trends that normally would be difficult to spot, like attrition spikes or certain positions that take longer to fill.
- Easy-to-navigate visualizations that users, with the appropriate access levels, can access across the organization.
- Advanced analytics is data collected during the workforce lifecycle that have an impact on important outcomes. It leverages and augments foundational data with more sophisticated types of data and analyses to address questions like “Why has a certain outcome happened and what can we do differently to improve it?” and “What new insights can we make available across the organization?”