Human Resources has a long history and has undergone massive shifts and changes throughout its lifetime. There are many misconceptions floating around, and many people have outdated perspectives regarding the nature of HR as it exists today.

HR analytics, while increasingly accepted as highly impactful and important, are even more widely misunderstood and not always fully embraced as an essential aspect of HR.

But failing to understand the essentiality of data-driven HR would be a grave mistake, and HR analytics shouldn’t be ignored by anyone who wants to compete moving forward. This practice is directly related to information about the heart & soul of an organization or company — its people — and can be highly influential when done correctly.

The global market for this field is expected to grow from $1.9 billion in 2019 to $3.6 billion by 2024, pushing leaders and HR departments to develop an accurate understanding of HR analytics and use those insights to advance and enhance their systems and procedures in this industry.

Let’s go through eight commonly accepted beliefs about HR analytics and discuss why these myths are untrue.

Myth 1: Complex approaches and techniques are always superior to simple ones.

Many believe that the more complicated and technical HR analytics systems or methods are, the better.

This couldn’t be further from the truth. Data-driven HR is about making the inundation of information as easy to understand as possible. If you overcomplicate this process, it’s hard to make sense of findings, pinpoint the most essential information, and incorporate it in valuable ways. It can also be costly and eat up tons of time and energy.

Technically sophisticated processes can be useful, but only if they lead you towards outcomes that deepen your understanding of the workforce in relation to your business.

Great data-driven analytics integrates various approaches, strategically enmeshing complex techniques (when advantageous) with tried-and-true methods to produce insights that can aid decision-making and help you improve business practices and achieve greater success.

Myth 2: HR analytics can be “done” or “finished” and can provide “permanent” information or solutions, where it is all about the destination rather than the journey.

A narrative suggesting that HR analytics is a program with an expiration date exists in the world of enterprise. Some assume that once you find useful information about your workforce, you can incorporate that into your HR programs and then “be done with it.”

But in reality, HR analytics is an ongoing, dynamic, and never-ending practice that draws its utility from its longevity. A “one and done” approach is a silly approach, as the workforce, the global market, and the field of HR are ever-changing.

Data-driven HR is truly about ceaselessly learning about your employees and your organization to continuously make long-term, sustainable, and endlessly evolving changes that enhance procedures and increase your business’s chance for success.

Myth 3: HR analytics are only essential and/or useful for large companies.

While this belief is understandable, it’s far from accurate. Although large companies may need HR analytics to a higher degree (as their workforce is larger, more complex, and more difficult to understand), small organizations should certainly prioritize this facet of HR.

SMBs who cultivate their HR analytics programs enjoy the same benefits as large companies who do the same, ranging from identifying harder-to-notice trends in performance to optimizing employee wellbeing and subsequently attracting high-caliber hires.

Myth 4: HR analytics will become obsolete and have little to offer in the AI-driven future of business.

Just as people think that “the robots”— or automated systems driven by predictive and intelligence-based software— will overtake most jobs in fields such as HR, some maintain that as AI gains traction and is integrated more deeply into the world of business, HR analytics will be phased out by automated programs.

The reality, however, is that HR as a whole and the analysis of HR data will become more deeply informed by & integrated with AI software.

According to Oracle, 47% of companies will incorporate AI-based solutions into their HR systems by 2022, while solutions like these already used by more than 17% of businesses.

AI doesn’t stand alone. It must be integrated in a thoughtful and calculated way based on the specific needs, goals, and characteristics of each unique HR team/business to serve as a useful tool. Determining where, when, and how to use AI requires robust HR analytics practices, and AI can’t be successful within the realm of HR without data-driven HR.

Myth 5: Every pattern in HR data is representative of a causal relationship.

A common misconception in mathematics, data analysis, and many other realms is that correlation = causation. As any good mathematician knows, it’s important to remember that not every pattern of inputs/outputs represents a cause/effect relationship.

Take care when making your analytics conclusions, and always test and verify seemingly causal chains to avoid errors in decision-making.

Myth 6: HR analytics frameworks are necessarily expensive, hard to set up, and require a data scientist.

While this field can prompt large monetary investments and complex approaches, HR analytics systems aren’t inherently costly, inaccessible, or difficult to build. And while many companies can benefit from hiring a full-time data scientist or an expert team, there are other routes to developing a successful data-driven approach to HR.

As leaders and HR professionals, you can opt for implementing affordable yet powerful software that streamlines your analytics practices and provide useful data for HR teams, hiring consultants for specific projects or initiatives rather than as full-time employees, or adopting a simplistic and straightforward approach that prioritizes a few growth areas when building your framework.

Using all the tools, technologies, and resources at your disposal, you can avoid making a crazy high investment and set up or build upon your HR analytics system more easily.

Myth 7: More data is always better.

This is one of the most widespread myths about HR and one of the most damaging. HR data is only useful if we can, well, use it. And an excess of information makes findings harder to see, more difficult to extrapolate, and much more challenging to leverage and incorporate.

Too much HR data can be impossible to manage and paralyze HR teams or data scientists. Having access to the right data— the data which can help you improve your business— is what matters, and what’s right for your organization will depend on a range of company-specific factors and global trends.

Myth 8: HR analytics exists in isolation from “other” aspects of a business and is really only relevant to the HR department.

HR and HR analytics don’t exist in a vacuum. These fields deal with the workforce, a clearly integral part of any company, and outcomes resulting from HR analytics practices can inform business-wide decisions, processes, and achievement rates.

Data-driven HR is highly relevant across any organization, and when done well, it can optimize results within any department.


As is true within any discipline, it’s important to fully understand the realities regarding commonly held conceptions and beliefs surrounding the nature of HR and its associated practices, implications, and impacts.

Don’t just accept what you hear as truth; always do your research, listen to verified experts, and challenge ideas before adopting them as beliefs that guide your decisions.

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