HR analytics, talent analytics, people analytics, and workforce analytics have become a confusing jumble of concepts. They can have different meanings depending on context, but we frequently use them interchangeably.
To make matters worse, the term “analytics” often becomes conflated with reporting and business intelligence. Software vendors package reports and dashboards in their applications and call it analytics. Business intelligence vendors wrap their entire suite of offerings into “analytics,” using it as an all-inclusive term.
Embedded analytics is powering a new hype cycle, with competition driving a rush to bring reporting and analytics directly into business applications, enabling better decision-making. A new model for delivering actionable information to business users is rendering IT-driven, centrally provisioned, highly governed and scalable system-of-record reporting obsolete. The future belongs to self-service data preparation and data discovery, where users can employ plain-language search tools to find the answers they need to seize opportunities at today’s speed of business.[1]
Words matter. They can shine light on a concept or obscure it. When the future of a project or strategic initiative depends on shared understanding, lack of clarity has consequences. We want to spend a few minutes to develop a framework for bringing your team together by promoting clarity of meaning.
When researchers and data professionals refer to analytics, they are describing statistical and predictive
modeling—much different from the reports people use every day to manage everyday business operations. They focus on predictions and connecting data and business outcomes. Reporting information in dashboards is not analytics, it is operational or management reporting. Predictive analytics is also much different from the simple analysis we use to correlate information from various sources to understand what is happening now or occurred in the past.[2]
Little of the work data teams do is predictive analytics. At the strategic level, few things matter, but they matter a lot. Answering the big questions that determine the direction of the business is worth the investment in sophisticated statistical modeling. Most data work is reporting on processes and events (Figure 1). We don’t mean to say reporting is not important. It is essential, but requires fewer resources.
Human capital management software vendors include “analytics” in their marketing, but few offer true analytics in their reporting functions. Data preparation tools are usually not part of the package. We can expect those things to change quickly. Gartner, Inc’s strategic planning assumptions for analytics point to a radical shift in the way business software vendors deliver data to end users.
According to Gartner, by 2018
To make sense of the way we use terms for analytics in HR, we reviewed the way vendors and practitioners use the terms and applied our experience and understanding to the differences among them. In many contexts, the differences do not matter, but when they do matter, a lack of understanding can lead a project team astray.
Use these suggestions as a starting point for creating the lexicon that works for you. Clarification of terms will help your planning and project teams form operational definitions that foster common understanding.
References:
1. Parenteau, Josh. " Critical Capabilities for Business Intelligence and Analytics Platforms." Gartner, Inc. March 10, 2016.
2. Reilly, Peter. "What do we mean by 'HR analytics'?" November 28, 2016.
3. Parenteau, Josh, et.al. "Magic Quadrant for Business Intelligence and Analytics Platforms." February 04, 2016.
Phenom eCloud is a comprehensive technology solutions provider committed to empowering businesses to overcome challenges, enhance their workforce capabilities, and achieve superior outcomes.