People Analytics Series: Introduction (Part 1 of 4)
The introduction of analytics into Human Resources is not a new concept and has been gaining popularity over the last decade or so. A recent article by McKinsey & Company outlines how advanced analytics is transforming the HR landscape.
For this article, people analytics means using data about people to develop insights in order to make data-driven decisions within a business. An example of this would be looking into employee demographics, qualitative feedback, and attrition trends to determine if a one-size-fits-all benefits plan is optimal.
Before one dives into preparing for any people data-related project, it is important to first think about where your organization is currently, where it wants to be (and how to close the gap) with regards to how resources are currently being used. To assist with this, below are tiers in helping to understand analytics maturity within an organization:
LEVEL 1: Descriptive (What happened?)
The first tier is essentially the ability to read reports generated by people systems.
LEVEL 2: Diagnostic (Why did this happen?)
This level is typically reached when one is able to not only read reports but find causal factors between multiple sets of data.
LEVEL 3: Predictive (What would happen if?)
Level 3 is where the approach becomes more proactive (as opposed to reactive). At this point, an analyst would be able to determine likelihood of what would happen (or not happen) based on causal factors identified.
LEVEL 4: Prescriptive (What should we do?)
At this level, algorithms within a system would analyze and forecast what actions should be taken.
Understanding where one’s organization is situated on this people analytics journey will be instrumental in gathering and utilizing the tools available before one begins.
Continue reading the series on data analytics to learn how to prepare when taking a data driven approach:
If you have any questions, please reach out to Kiwi Partners’ HR Services team.