Perspective

Using Data for Human Resource Management

How to Stop Losing Good People to Hidden Figures

Jose Antonio Sison

1 November 2018

How do we encourage higher productivity?

What makes for a valuable employee?

What makes our valuable employees leave?

The problems at the heart of human resource management remain constant across time, and today’s HR professionals are busy answering yesterday’s questions. Every time a promising answer arrives, economic, cultural, or generational variables change to wipe the board clean.

Still, we persist in finding new solutions and developing better tools to manage our employees and provide them with every advantage in aligning with our business’ goals.

Or, at least, we should be.

A failure to innovate makes it harder for businesses to thrive. Circumstances may change and people may be the trickiest subject to master, but nothing kills growth quite like a refusal to get with the times.

This is especially true in the field of HR. Recent waves of technological progress have added great complexity to the average employee’s life and values, and technology provides a great advantage when sorting it all out—but only to the willing.

People Analytics

Just as the name suggests, big data has grown to encompass a wide range of applications. People analytics, defined by Google re:Work as the use of “a data-driven approach to inform your people practices, programs and processes,” is one of these applications.

Consider the oldest HR problem in the book: how do I encourage higher productivity?

If you were to ask a random person on the street, they might give an intuitive answer: start by finding out what motivates your employees and then work from there. Call each member of your organization over for a quick interview, and make changes based on the ideas they give you.

The direction of the kind stranger’s advice is a form of people analytics. You gather qualitative data about your employees, analyze the data, and use what you learn to make smarter business decisions. The approach of interviewing your staff members one by one may be a bit low-tech compared to what we’re capable of today, but you can see the core of the idea in action.

With people analytics, you can spot the variables that make for top performers, high-power teams, and flight risks. You can find out what your employees are thinking and feeling, as well as which of those thoughts and emotions make for the best investments. You can master your organization’s internal processes before taking it in a new, more efficient direction.

Data Engineering in HR

People analytics is a technique, but it’s one that relies on a particular frame of mind. In theory, you can pull up a spreadsheet and start running analysis on whatever data you have available. It’s possible, but unless you’re thinking from the perspective of a data engineer, the results aren’t likely to hold significant value.

There’s more to people analytics than analytics. To make the most out of HR’s latest and greatest innovation, you need to consider the following:

  1. How do we collect data, and where from?
  2. How do we store and organize data?
  3. How do we make sense of the data?
  4. How do we act based on what we’ve learned?

There are four parts to what we at Cirrolytix call the data value chain: a process by which raw data is harvested and refined into the kind of information that can save industries. Think of it as a factory line for data-driven decision making.

A data analyst is involved in the third step, or data consumption. This means that even the most skilled analyst is nothing without a proper infrastructure for gathering data.

A data engineer’s perspective is concerned with the whole enchilada. It leaves no stone unturned, and helping businesses wield data from the moment they start to collect it.

HR Analyst

When you realize everyone is taking their sick leaves on the same days every year


Hidden Figures, Clear Risk

HR professionals who’ve tapped into people analytics and other big data techniques have spotted factors they never imagined would have an effect on their KPIs. There’s a large risk in letting these factors go unnoticed; if you weren’t aware, employee turnover in the Philippines has recently hit a five-year high.

To show you what tapping into people analytics looks like, let’s refer to the Harvard Business Review’s study on the kinds of behavior that employees exhibit before quitting. HBR referred to hundreds of data points and determined that lowered productivity, relatively poorer teamwork, and drops in motivation are signs that an employee is soon to leave.

The discovery is great news for any HR manager who knows how to act on it, but therein lies the problem: how does a company with ranks upon ranks of employees monitor behavior with the necessary level of precision?

The answer would be to build a sound infrastructure for collecting and analyzing data. Tap into expert knowledge and quantify those highly subjective variables (create scores for motivation, for example, or track teamwork to the decimal). Data science allows HR professionals to shine a light on the hidden figures that can make or break their years of effort.

Moving Forward

Like it or not, there are lines of influence that run through every business. Invisible to the untrained eye, these variables warn of fortune and disaster long before the point of no return.

For most Filipino businesses, today’s problems were solved yesterday by data specialists and the tools they’ve developed. Those who plan to dominate tomorrow have to get the ball rolling and engage with emerging technology.

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If you’re interested in facing the demands of today’s market head-on, sign up for our Masterclass series on business analytics. We’ll equip you with the tools you need to make data-driven decisions and spot the hidden figures that flow through the professional world.

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Jose Antonio Sison
Anton is a digital marketing consultant and content strategist. He helps businesses craft messages that sell to audiences on the internet, armed with the expert perspective of someone who spends far too much time there himself.


 
 

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