Have you ever noticed that organizations are increasingly using the terms “big data,” “analytics” and (to a somewhat lesser but still notable degree) “business intelligence” (BI) interchangeably?
But they aren’t quite the same thing. Here’s how respected, authoritative sources define the three:
“high-volume, high-velocity and/or high-variety information (asset) that (demands) cost-effective, innovative forms of information processing that enable enhanced insight, decision making and process automation,” according to Gartner.
I like this one too, from the McKinsey Global Institute: “Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze. This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data.”
“the scientific process of transforming data into insight for making better decisions,” according to the Institute for Operations Research and the Management Sciences (INFORMS), the world’s largest organization for professionals in the field of operations research, management science and analytics.
“simplifies information discovery and analysis, making it possible for decision-makers at all levels of an organization to more easily access, understand, analyze, collaborate and act on information, anytime and anywhere,” according to Microsoft.
I’m particularly intrigued with the last definition. It dates back to 2008, but it’s relevant today – especially when applied to what we call “people analytics,” a.k.a., the combining of big data, analytics and business intelligence to improve recruitment, onboarding, training/development, engagement, retention, succession and other human resources (HR) practices. Ultimately, you use people analytics to drive toward a better-performing workforce.
The best people analytics tools allow HR leaders and their teams to maximize the possibilities of existing data. It doesn’t necessarily have to be big data. But it often is, and this reality should only grow more prevalent as we collect more and more data, from more and more resources. By applying BI principles which foster the simplification of information discovery and analysis, effective solutions empower organizations to easily and instantly derive the most value from talent-management data. The tools are so intuitive and user-friendly that you don’t have to be a data scientist to make sense of them. As Microsoft described, decision-makers and staffers at all levels readily access, understand, collaborate and act upon the information.
This proves critical because tech proficiency among HR professionals runs the range. Even if certain team members are IT savvy, it’s not a prerequisite. If the tools intimidate them, they won’t use them – and that’s a waste of your organization’s money and time. Strip away the intimidation, however, and these professionals find that they can vastly augment workflow processes, perhaps through one insight. People analytics might reveal, for example, a previously unknown redundancy or bottleneck that can be removed, saving literally thousands of dollars by expediting time-to-hire or improving onboarding practices.
To extend the concepts of BI here, we must also avoid focusing solely upon the technologies. Always remember that this is about solving business problems. And, should HR teams truly take full advantage of the technologies, they can explore endless ways to apply people analytics to an endless number of business problems, such as low morale, inadequate training, high attrition, pending retirements, succession gaps, etc.
Despite all the talk, people analytics is still in its infancy. There is a world of opportunity ahead. We will see, as organizations move forward, they will hire and retain better employees, leading to tangible and immediate ROI. What’s better: Your HR teams won’t need a degree in data science to accomplish all of this.