To the uninitiated, the world of analytics can seem daunting; an impenetrable maze unless you have a HR background or expertise through people and culture courses. Truth is, when you find a way in, it’s a path your company should pursue.
Especially people analytics. The strategies born from implementing people analytics deliver proven results, but only if you properly understand how to implement and utilise them. Let’s unpack exactly how your company can do this.
People analytics: a definition
People analytics is collecting and analysing data to understand better how your employees perform. Done well, it follows this sequence: insight gained, decision made, strategy implemented, improved business outcome enjoyed.
People analytics is a common and powerful tool for HR departments; that said, its reach isn’t limited to human resource matters. Your marketing, finance, and customer service departments can all benefit from people analytics.
Types of people analytics
Like other types of analytics, different approaches exist that offer different insights. Each approach has value; combined, even more so. Here are the four types of people analytics:
1. Descriptive
Descriptive analytics focuses on one question: what happened? It addresses your company’s past actions by analysing historical data. What it doesn’t address? Your company’s future.
A study by the HR Research Institute found that 83% of businesses rely on this type of people analytics, a concerning statistic given its limited scope.
2. Diagnostic
If descriptive analytics is the news bulletin, diagnostic analytics is the critical interrogation of that bulletin. It asks why, aiming to explain how trends, correlations, and anomalies in the data offer certain insights.
3. Predictive
As the name suggests, predictive analytics aims to forecast the future by analysing your company’s past and present data. It uses the insights gained from this analysis to create estimation models to predict what might happen.
Another concerning statistic from the HR Research Institute’s study found that only 20% of businesses used predictive analytics.
4. Prescriptive
On its own, data is static; it needs action to give it life. Prescriptive analytics does this by turning an academic activity into something practical and beneficial. It offers potential challenges, scenarios, and outcomes and recommends how to handle them. For this reason, it’s arguably the most important type of analytics.
Notice the sequence? It reflects the logical steps of a detective presented with a challenging case. Again, each type has value; it’s when you combine them that they properly unlock your data’s potential.
3 benefits of using people analytics
The benefits of implementing people analytics are as countless as the data points that inform them. Rather than unpack them all, let’s look at the benefits more broadly.
1. Optimises efficiency
Collecting and analysing data on your company’s operations lets you identify areas where you can get better. For example, you might discover a step in your production line has become redundant; removing it increases operational efficiency.
2. Improves safety
Replace redundant with unsafe. Quality data highlights gaps in your company’s safety policies and lets you address them promptly.
3. Saves money
The culmination of implementing sound strategies based on quality data is that it leads to financial savings. When you make your company safer and more efficient, you reduce unnecessary costs. Reason enough to embrace people analytics.
How to implement people analytics in your business
Define your problem
While routine data collection is a practice worth implementing, it helps to understand exactly why you want to collect the data. Understanding the why lets you narrow your focus and only collect the data you need. Refining your intent will lead you to actionable answers to your problems sooner.
Ensure alignment
Alignment is key with people analytics. Collecting and analysing data takes time and effort; if the activity runs against broader company goals it can lead to friction within departments. Align your people analytics to your bigger-picture goals and you’ll gain the most from implementing it.
Start with a sample
There’s a reason data analysts exist; it’s a skill you master with practice. If this is your first attempt at utilising people analytics—or any analytics, for that matter—start with a sample data set. Like training before your first footy match, it gives you a chance to hone your skills before your actions have consequences.
Poor insights, poor results: what to avoid with people analytics
Data lives by one rule: you get out what you put in. No amount of manipulation can change this; at best, it will set your schedule back.
Biased data
In simple terms, biased data is incomplete or inaccurate data. The reason you want to avoid it is equally simple: biased data fails to paint an entire picture. And without an entire picture, you risk your decisions and strategies failing to account for certain details.
Biased data becomes more complex when you consider the source of the bias. Imagine a scale. At one end, you have administrative bias, like poor data collection and entry. At the other end, you have social, economic, and political biases. Both ends of the scale give you poor data. The difference is the administrative end can be easily fixed; the social, economic, and political end, not so much.
A timely example of biased data happened at Amazon, where it was discovered that their automated recruitment software discriminated against women applying for technical roles.
Focusing on quantity over quality
Data’s greatest strength is its reach. You can collect data on anything. And everything. The flip side to this limitless pool? Your efforts focus more on quantity and less on quality. On the surface, collecting oceans of data might seem like a step in the right direction. It can be, but only if you’re collecting the right data. Data for data’s sake is not a strategy; it’s time and energy better spent elsewhere.
Collecting the right data starts with asking the right questions. A supermarket operations manager looking to reduce the costs associated with malfunctioning refrigerators must ask: how many different ways can a refrigerator malfunction? The right question points you toward the right data.
Forgetting the bigger picture
Data is seductive; once you learn how to wield it to your company’s advantage, it’s easy to get carried away with what you can learn. Just make sure you step back and consider your company’s overall goals and objectives.
Start by maintaining honest and transparent communication with everyone involved in your company’s data project. Being told to collect data without context could eventually have a negative effect on the collector; it’s the type of uncertain task that could have them questioning their future with your company.
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In the end, data is evidence. And evidence, when interrogated properly, should always answer the questions you ask of it. People analytics is no different. It presents your company’s data less as vast amounts of information and more as a roadmap toward better performance.
