People Analytics: What is the Human Resource? - dummies

People Analytics: What is the Human Resource?

By Mike West

At a high level, people analytics consists simply of applying evidence to management decisions about people. More specifically people analytics lives at the intersection of statistics, behavioral science, technology systems, and the people strategy.

People strategy means making deliberate choices among differing options for how to manage a group of people.

The figure illustrates how people analytics joins together these four broad concepts (statistics, science, systems, and strategy) to create something new that didn’t exist before.

analytics concepts
People analytics is what happens when human resources professionals realize the power that a good dataset gives them.

Many forward-thinking companies are already realizing the benefits of evidence-based decision making in human resources. To identify what other people think people analytics is, I rounded up 100 job descriptions related to people analytics from job boards. To summarize, I created a word cloud from the words in those job descriptions; it appears in this figure.

analytics word cloud
Creating a word cloud is a kind of data analysis to identify and visualize trends in vocabulary.

If you’re not already familiar with word clouds, this is how they work: The more frequently a word appears in the text that you’re analyzing, the bigger and darker that word looks in the word cloud. You can tell from the figure that data, analytics, human resources (HR), and business must be central concepts to people analytics.

These 100 job descriptions are from Human Resources department that are ahead of the pack in using hard data and analysis as decision-making tools. The insights data is providing these companies gives them an advantage over companies that do not yet know how to do these things. A vast majority of companies do not yet have people analytics and most people do not even know what people analytics is. That being the case, you, by learning about people analytics, will be in a great position to differentiate yourself among your peers (and your company among its competitors).

People analytics solves business problems by asking questions

Like all business analysis disciplines, people analytics offers businesses ways to answer questions that:

  • Produce new insight. One of the great contributions people analytics can make to you is to reveal some of the perilous things you don’t know and don’t even know you should know but in fact should know.
  • Solve problems. Data can also help you devise solutions to known problems.
  • Evaluate the effectiveness of solutions and improve going forward. You also can use data to evaluate the effectiveness of solutions on a small scale so you can make sure the solutions will actually work before implementing them more broadly. Experiments can provide a dataset that allows testing ideas in ways that prevent costly mistakes (facilitating improvement) before rolling out ideas more broadly.

People analytics uses people data in business analysis

People are the face, heart, and hands of your company. All companies depend on people in every aspect of their business because people

  • Empathize with customers wants, pains, and problems
  • Create and improve products and services
  • Design, manage, and execute the strategies, systems, and processes that help everyone work together toward a productive enterprise

Considering how important people are to the performance of each company, it’s amazing that more companies don’t study employee data for insight into their businesses. Your company probably hires experts with advanced skills to analyze your finances, equipment, and workflows, so why isn’t anyone studying the people who use these things?

Part of the reason is that, until recently, the pool of available employee data was pretty shallow. When companies had only physical file folders full of employee data stored in the file cabinet, the opportunities for deep, meaningful analysis were few. Over the past couple of decades, though, the amount of electronic data that companies keep (intentionally and unintentionally) about their employees has quietly been building.

Today, your company probably has a flood of electronic employee data, whether you realize it or not. You’ll find some of this data in obvious places, but you might not have thought about the data available from some of the sources I list here:

  • Employee resource planning systems (ERP)
  • Human resources information systems (HRIS)
  • Payroll systems
  • Applicant tracking systems (ATS)
  • Learning management systems (LMS)
  • Performance management systems
  • Market pay benchmark surveys
  • Employee surveys
  • Email and calendar system data
  • Corporate intranet (internal websites) traffic data
  • Job boards
  • Social network comments
  • Government Census and Department of Labor data

The good news is that businesses do seem to know that their employees are their greatest asset. What businesses don’t seem to know is how to analyze data about their employees to improve their business outcomes. In the chapters in this book, I demonstrate how you can do just that.

People analytics applies statistics to people management

All managers think they’re above average at making decisions, but at least half of them are wrong! I’ve just demonstrated the wide variety of data that human resources managers have available to them, but they need the right tools and methodologies to interpret and make decisions based on that data. If you misinterpret your data, the option that seems right can turn into a disaster for your company.

That’s where statistics come in. You might think of statistics in terms of the procedures a statistician uses, like t-tests and regressions, but analyzing data with statistics isn’t just a mechanical operation. My favorite book on statistics, The Nature of Statistics, by Allen Wallis and Harry Roberts, defines statistics as “a body of methods for making wise decisions in the face of uncertainty.” The field of statistics offers the tools, but you need to wisely apply those tools to produce useful insight from data.

People analytics combines people strategy, science, statistics, and systems

As a relatively new field, people analytics feels a lot like what I imagine the Wild West of American folklore must have felt like: There aren’t a lot of rules, and everyone’s making their own way to some unclear new opportunity.

If you asked a group of people analysts to describe their work, the answers you’d hear would likely be quite different from each other and depend a lot on the background of the individual person. Here are some examples of how the categorically different types of people you find working in the field of people analytics think categorically differently about what they do.

  • Human resources: Someone with this background might describe people analytics as “the decision science of HR” or “the datafication of HR.” Put a different way, as customer analytics is to sales, people analytics is to human resources. The focus of a person with a human resources or management strategy background is likely on the implications of data on how the company manages people or human resources conducts its work, with less emphasis on the nuances of how the data was produced.
  • Behavioral science: A person who comes from a scientific background is likely to describe people analytics as simply a new term referring to the near century old practice among university professors and graduate student research to study people in the workplace in fields as wide ranging as: psychology, sociology, anthropology, and economics. This crowd carries the all-important distinction of three letters behind their name, (PhD) or two letters before their name (Dr.). The focus of the doctors is on the application of science to human behavior to produce new learning, less so on the day-to-day processes to efficiently collect, store, and use the data. Scientists are best at identifying new data that should be collected and developing a reliable and valid means to collect that data, but probably not best at how to do that efficiently.
  • Statistics or data science: These folks might describe people analytics as using statistical methods and machine learning algorithms to infer insights about the people aspects of businesses from data. Their focus is on mathematics and technical processes to produce insight from an existing dataset, with less emphasis on the determination of what data should be collected or how to apply the findings from data to produce change.
  • Information technology: Someone in this camp probably would focus on those systems that would make reporting and analysis more efficient to produce. Their focus is typically more on the overall data architecture and systems than the analysis itself. From an information technology standpoint, people analytics is nothing more than the application of reporting (sometimes referred to as business intelligence) to the specific domain of human resources, as opposed to something new and different.

The answer, of course, is that people analytics is all of these things, and a dozen things in between. You can apply the tools of people analytics to many purposes. Just like in the Wild West, rugged individualism is a common characteristic among people analysts, but we still stand to gain a lot by listening to and learning from each other.