Data Analytics: Considerations to Corner Effective HR Actualization
The road from data-aspiration to data actualization comes with its share of pitfalls and potential problems. As noted in A Buyer's Guide to Data-Driven HR," to tackle data-driven HR there are few components you need to get right: You need to be able to gather and manage the right data, understand what it means in the context of your most important business goals, and then use it to improve processes and make better, data-driven decisions." But how do firms make the jump from data analytics to effective actualization?
Here are three considerations to help jump start the process in your organization.
1. Manage Maturity
For many corporations, the idea of leveraging big data comes with a "silver bullet" mentality — big spend should equal big results. The problem? Raw data alone never tells the whole story. Massive amounts of information provide the foundation — key comparisons, correlations and connections — but aren't enough in isolation. So organizations should "start with a business goal, and then work backwards to find out exactly what kinds of data you need to improve your decision-making ability," according to A Buyer's Guide to Data-Driven HR cited above.
It's, therefore, critical to first evaluate existing analytics maturity: Is this your first big data solution, or are you hoping to enhance an existing model? Is corporate culture already data-driven or is an HR shift necessary to embrace this new resource? By managing maturity before investing in data analytics, HR professionals can determine the ideal support outcome.
2. Understand the Possible
The next step to empower data actualization? Understand what's possible as your organization matures. Entry-level processes allow you to easily capture and report data, while more advanced implementations let HR experts identify emerging issues — such as retention, compensation or employee performance — then make predictions about likely outcomes and prescribe immediate action. But as noted in A Buyer's Guide to Data-Driven HR, "once you work out what you need to do, you need to work out where the data is. Integrating all the data from multiple internal systems and making it visible is a major challenge." You need to make sure you not only understand what you can do, but also have a strategy in place to fill the gaps when you find them.
3. Plan Well
But how do you get from point A to point B with HR analytics data? Careful planning. Identify the data you need to answer crucial questions, integrate information from non-HCM sources, and utilize benchmarking to provide actionable industry insight. Once you do that, you can then start to prioritize your objectives and find the right analytics solution for your organization with advanced actualization tools that integrate analytics into core HCM workflows to help you deliver actionable results.
So are you ready to move beyond data collection and embrace big data actualization to improve your HR decision-making?
Download A Buyer's Guide to Data-Driven HR, to see some of the ways organizations are winning with data-driven HR.