How Can Data Analytics Improve the Measurement of Employees’ Performance?

A report from Deloitte shows that in recent years, the need for people analytics has reached high points of over 70 percent. More companies rank people analytics as a “high priority” in the organization. However, the same report lays down a frightening truth: Less than 10 percent of those organizations actually have usable data. So, are we not asking the right questions? Do we even know what to look for? This isn’t yet another post on complicated algorithms; after all, you’re not here to learn data science.

This post is about answering one question: how can data analytics improve the measurement of employees’ performance? It’s not going to be easy— assessing your human capital is always easier said than done—but I’ve got your back.

But before we dig any further, it’s important to make sure that we’re on the right page. There are a lot of buzz words out there, but data-driven management is by no means a new concept. Since the concept of “the cloud” came up, companies started moving their workforce to it. Big item metrics like acquisition (e.g. cost per filling, training ROI) led companies to also ask questions about revenue, retention, and, more importantly, the question we’re here to talk about: how to track performance.

Data-Driven Management

Great instinct has always been number one in every good manager’s toolkit. Knowing how and when to use that gut feeling was faster than relying on a computer to make decisions—if you’re asking the right questions, that is.

So how does that gut feeling mesh with people analytics?

Today, we’re going to work at bridging two really opposite concepts: great instinct and data-driven leadership. At the end of this post, you’ll realize how much better it is to shoot for objective metrics and people analytics than to rely on subjective evaluations.

In this era of quantification, business intelligence is here to help you understand what to look for. It also helps you pursue data-driven leadership. Bigger result sets, tailored indicators, and enterprise computing are now readily available and provide never before seen help to HR managers. Things have changed.

People analytics are not a replacement for soft skills. Having these discussions company-wide actually increases brainstorming, which is a proven creativity catalyst. Team-building and keeping morale high should always be at the heart of every HR initiative, and the strategies we outline aren’t the exception. Plus, more data involves more people, which brings different perspectives and insights to keep in mind.

Getting Into Specifics

Opening up a browser and looking for indicators and variables to measure will result in an endless list of metrics. While these metrics can all help to push your company forward, it may feel like there’s too many of them.

At this point, it’s fairly easy to think about tracking everything, but that would turn your analytics into a Big Brother scenario. Don’t get me wrong, you definitely could do that, but don’t fall prey to the trap of management by spreadsheet! After all, who likes being micromanaged?

We now understand the need for metrics, and we know we can easily get them. Also, we know what to look for and what not to do, so what’s next? We’ll find things to measure—something to prove we’re maximizing efficiency.

Enter KPIs.


KPIs are actionable metrics that a company can use to keep everything under control. They help link business strategy with individual performance. Projects, customers, or anything else in the organization can be tracked. But we’re here to talk about one specific aspect of KPIs: employees’ performance.

One thing to keep in mind before we continue: Not everything is a KPI. Just because you can measure it, doesn’t mean that you should track it. We only care about a metric if it aligns with the company strategy.

So, what exactly can we measure? Here are two main categories:

  • Employees’ outcome quality
  • Employees’ outcome quantity

These two metrics can be used to summarize workforce productivity and employee efficiency.

Only your company can determine which specific metrics (and how much of them) are needed. Your metrics should follow your business logic and align with the company strategy. No two companies are the same. Remember when I mentioned brainstorming?

Having the right HR metrics is an ongoing collaborative effort. More than that, these strategies will keep the HR department relevant. Ask yourself questions like:

  • How does this metric align with the company values?
  • What is our strategy to improve?

The answers to these questions steer metrics in the right direction and drive a positive impact on the bottom line, thus making the 21st-century HR department perform at its most efficient.

One thing to keep in mind: These metrics are created to tell you what happens within your organization. It’s only through careful analysis that you can get to the why.

Data Quality

Beyond quantity, how good your data is will make or break your strategy. Your information can only be as good as the intelligence you gather. There’s a great book on organization effectiveness that summarizes the information gathering process quite well for us:

  • Consistent
  • Accurate
  • Reliable
  • Efficient

Embracing consistent data means that the lifespan of the gathering has been steady over time. Accuracy talks about the data’s preciseness; ideally, few to no errors are accepted while gathering it. The data should also be reliable, as your HR department has to depend on that data. And all of the above efforts should remain efficient; the cost of gathering the data must be minimal.

How Do People Analytics Help?

I thought you’d never ask! One very important thing to get traction in your data-driven HR effort is to always make a business case out of it.

There are plenty of business case studies out there of companies that used analytics to measure and increase performance. Let’s go over a few:

The Algorithm That Tells the Boss Who Might Quit

Back in 2015, Credit Suisse was rather concerned about employee turnover rates. They used a specific set of metrics to predict whether an employee will choose to stay with the bank.

Just to give you an idea of how much turnover means for a company, a mere one percent reduction would save the company between $75 million and $100 million per year. It took Credit Suisse a three-year strategy (consistent data, remember?) to gather the information they needed.

People Analytics at Nielsen

On that same note, Nielsen faced a similar issue. They were dealing with attrition, and to remedy the situation, they gathered the data. Within the first few months, they were able to come up with a model that aligned with their business strategy (defining the KPIs). By doing this, they debunked myths and ensured the right people would stay with the company.

Examples of success don’t stop at analyzing turnover. They also apply to hiring, performance, and engagement.

Sounds Fancy, Is It for Me?

Thinking that all of this only applies to big companies is wrong. Your company has readily available tools out there tailored to your needs. Some of them might include Zoho People, ADP, Oracle HR, Bamboo HR, or others.

However, buying additional software isn’t mandatory. Most HR departments will have all of the information they need already. The trick is knowing what to look for and how to extract the data.

But as we’ve learned, it’s only after asking the right questions and following the proper strategy that you’ll reach your objective. Here’s a simple to-do list to get you going:

  1. Create a business strategy.
  2. Collaborate to create an HR strategy.
  3. Ask the right questions.
  4. Define metrics to answer those questions.

Data analytics are no longer just something nice to have—they are a must for your company.

Are you ready to tackle the challenge? Be sure to let me know.

This post was written by Guillermo Salazar. Guillermo is a solutions architect with over 10 years of experience across a number of different industries. While his experience is based mostly in the web environment, he’s recently started to expand his horizons to data science and cybersecurity.

Other Reading:

RAG (Red, Amber, Green) status is a widely used tool in data analytics because it provides a quick, visual representation of the state of a particular metric or KPI relative to a target or benchmark. It simplifies complex information by providing an easy-to-understand summary, aids decision-making by highlighting areas that require attention, facilitates communication by using a color-coded system, and enables tracking over time. As such, RAG status is an invaluable tool in data analytics. Read more on RAG status in technology here.