People Analytics: A Definition & Breakdown Of Trends
What, exactly, is people analytics (sometimes also referred to as human capital or workforce analytics)? At Perceptyx, our definition of people analytics is this:
People analytics is the process of connecting the dots between people data and important business outcomes. (Tweet this!)
Ultimately, it’s about figuring out how to maximize the value people bring to an organization. To do that, we must first understand how to measure and analyze a variety of people data, such as employees’ perceptions. Data is always better than a hunch or intuition, and people analytics gives us a way to cut through the noise and the biases we all bring to the table. Then, we communicate the value of having that information to leaders, who enact changes that will allow all employees to perform to their maximum capacity. Essentially, the work we do in people analytics allows leaders to see what matters most to employees and make smarter decisions to act upon it.
In this article, we’ll look at the developments and trends in people analytics that are bringing us closer to realizing the goal of maximizing human capital.
It’s an interesting time right now in HR. The HR landscape is changing, and advanced HR analytics is one of the most strategic activities HR can engage in to win a permanent seat at the table. Finance is no longer the only department that has concrete numbers to buttress plans and strategy.
On the other hand, most people who have been in the HR field for some time didn’t choose their career path because they love numbers. This poses some challenges. While HR professionals are experts on people, they aren’t necessarily experts on numbers or analytics. This mismatch between skills and the direction HR is heading has created some interesting trends across the industry.
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People Analytics Trend #1: The Team Of Teams Approach
As organizations and HR professionals scramble to develop their people analytics strategy, it’s clear that, the way most teams are currently structured, they aren’t prepared to handle in-depth analytics. And while it may sound like building a team internally in HR is the right move, the cost of entry is incredibly high, both in terms of the people costs and technology costs. Not to mention it takes months to successfully onboard a team, build relationships, and start providing real, concrete value. Another potential approach is to “borrow” expertise from other departments—such as finance and operations—to get the work done. The problem with this approach is that team members insourced from other departments will be more concerned with their primary responsibilities, forcing your people analytics projects to take a backseat.
Currently, most organizations favor a “team of teams” approach to building their practice. This approach relies on outside partners who are experienced in seeing problems and overcoming obstacles. It minimizes the cost of entry, and provides a ready-made team of individuals who are already grounded in people analytics strategy. Using this approach, external player-coaches can help HR get up to speed more quickly and build their own practice over time.
This approach is powerful because it combines internal expertise on the business with external expertise on data science and consulting. Without convergence, a data pattern may be of interest to an analyst but not to an HR leader, who may deem it inactionable.
The team of teams approach also gives HR quantitative horsepower. A diverse set of people collaborate to move forward with initiatives that hit the mark for the business. With that, there’s an opportunity to move HR from being viewed as a cost center to being seen as a strategic partner; quantification of people analytics insights and results clearly demonstrates HR’s value to leaders. In addition, there are always opportunities for external partners to work on the whiteboard issues every CHRO has but doesn’t have the time or resources to address. An external partner that works with HR rather than competing with the internal team will boost leaders’ perception of HR as a strategic asset.
It’s also important for HR and their analytics partner to work with other groups outside of HR. For example, when attempting to determine the costs of attrition, instead of spitballing a number, HR should work with the finance department to develop a concrete number on the direct and indirect costs of turnover in the organization. This quantifies the return on investment for people analytics. Plus, the close collaboration with finance lends the HR team more credibility than they would have had simply by working on their own.
What is common in HR analytics is that, too often, organizations want to tackle the biggest, messiest problems first—which is a recipe for failure. The complexities of addressing big issues such as workplace culture makes these types of issues a poor starting point for the initial launch of a people analytics practice; failure to produce results can hurt HR’s standing with leadership for the future.
Attempting to tackle the big problems first is not a good plan for gaining traction. The better approach is to start out working on smaller issues to rack up some wins and build a reputation as a strategic partner who delivers for the business. If the team has already compiled a record of small, quick wins, their reputation is less tarnished by a later failure on a bigger, more complex issue.
The most important thing in the team of teams approach is to choose your partner carefully. Many external partners only catch the fish, or try selling a new reel; they do not invest in teaching the organization the practice. People analytics providers who focus on making their clients heroes with the data—and teach them along the way how to build and maintain their analytics practice—make the most effective partners.
People Analytics Trend #2: Progress Towards Maturity
Human capital analytics continues to mature in terms of the depth of insight teams can provide. Many teams start in the descriptive, diagnostic stages, trying to understand past events. It’s a rearview mirror view, where the team looks at what happened and tries to understand why it happened.
The next stage is predictive people analytics. In this stage, the team can look at what happened in the past and the data points that predict, for example, voluntary turnover of top performers. Understanding there is a pattern between certain survey responses and subsequent attrition gives the team the ability to predict the who, when, and why of turnover. Many organizations have reached the predictive stage in their people analytics practice.
The final stage, the pinnacle of achievement that all organizations hope to reach, is the prescriptive stage. In this stage, the team has the benefit of predictive analytics to know what to look for as red flags, and the experience to know what kinds of actions will work to head off problems. Few organizations have reached the prescriptive stage.
The knowledge team members have accrued in the previous stages of maturity becomes clear in the prescriptive stage, because here, the questions are not about who or why, but what can be done to produce a desired outcome. What actions can be taken to solve or minimize the problem? Some people analytics platforms are sophisticated enough to provide alerts to users about problems that lie ahead; the system may be scanning employee data and sending nudges to managers before potential issues grow into problems.
At the same time that platforms are becoming more sophisticated, what users are asking for is simplicity—a solution that is both simple to use and scalable. Right now, simplicity often competes with depth of analysis. The analytics team that can crack the nut in terms of creating something that is simple for leaders to understand and scalable across even large organizations—but still provides depth in both predictive and prescriptive analytics—is the team that will win at the end of the day. Very few providers are creating people analytics solutions that can check all of those boxes today. All phases of the analytics maturity model are important, and with each progression comes more complexity, but greater value. Nevertheless, I find it best to crawl, walk, and then run, before you implement prescriptive analytics (running with scissors).
One route to making analytics work approachable is for HR to think about visualizing the data so leaders get the story and have an “Aha!” moment about why it matters and why they should care about the metric. If a picture is worth a thousand words, an interactive data visualization is worth a million words. In terms of analysis, it means going from the macro level of explaining what’s going on at the enterprise level and driving down to the micro level, so managers will also care, understand, and act on insights. We all have a visceral reaction to being told what to do; the best visualizations allow users to interact and discover in a guided way to form their own conclusions and potential paths to monitoring and improving performance.
People Analytics Trend #3: Integration Of Artificial Intelligence (AI)
It is sometimes said that we are in a time that is data rich, but analytics poor, with 90% of data being created in just the last year. We have a huge volume and variety of data with incredible velocity, which affords ever more complicated analyses. The use of AI in HR analytics makes these complex analyses more approachable than ever before.
The issue is that with some complicated techniques, we lose the ability to explain; AI becomes the “black box” of people analytics. Many people still have a fear of algorithms and are more comfortable relying on intuition or judgement. When confronted with complicated algorithms using deep learning and neural networks, which are more difficult to explain and understand, that fear can be exacerbated and get in the way of driving change. There is a role for AI in people analytics, but the easier it is to explain or the more it can be hidden behind a user-friendly people analytics dashboard, the more comfortable people will be with it.
Because many of the biggest issues organizations seek to solve are best addressed at the manager level, an approach of showing managers which levers to pull is going to have the biggest impact. Managers typically don’t want to be told what to do; they want to discover it on their own. After building a people analytics model, it’s interesting to allow managers to play with the inputs in a dashboard and discover that if they do X, here’s what will change in Y. It’s almost like leaving a trail of breadcrumbs for managers so they come to realizations themselves; this hands-on approach is far more powerful for incentivizing managers to enact change than just being told what to do—and it can help to eliminate any fear or bias against algorithms.
This approach also helps to address issues of scale. In an enterprise organization with thousands of managers, it’s nearly impossible to disseminate information one-on-one with all of them to hit the mark. It’s important to make the platform or system so approachable that managers can easily discover insights about their teams for themselves.
People Analytics Trend #4: Designing For All Stakeholders
A people analytics platform and practice has to meet the needs of everyone in the organization—employees who interact with the system when completing surveys, managers who supervise those employees and implement actions, HR administrators, and executive teams.
Our approach at Perceptyx has been to think of all the personas interacting with the system, and leverage design thinking to build insight tools and technology that “ticks all the boxes” for all of those people. This translates into providing depth of analytics in terms of descriptive and diagnostic power, combined with flexibility to allow users to navigate the tools and look at their own areas of interest. Giving them the tools and allowing them to explore to gain familiarity is the most important recipe for action planning that’s simple, scalable, and repeatable.
The external consulting role is the other side of designing a practice that works for all stakeholders. What’s most important is having a great understanding of the business and what the organization is trying to accomplish strategically. Too often there is a tendency to jump to solutions without first understanding the problem. As Albert Einstein said, “If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and five minutes thinking about solutions.” That quote speaks directly to people analytics practice, and where external consultants can provide tremendous value by asking great questions and not immediately jumping to solutions that, in all likelihood, miss the bullseye.
The value a good external partner brings is in understanding the problem at the beginning, providing efficiency and expertise in execution, and implementing and continuously monitoring changes within the system. They provide a third-party perspective from a source who has seen it before, has experience in what has worked and what hasn’t, and from that experience, has an idea of what might work in a particular situation. The external people analytics partner is there to guide the organization in the right direction to reach its goals—and to even help push it when needed.
Seeing The Way Forward
The Perceptyx platform combines simplicity of use with depth of analysis—and has the flexibility to address the needs of all stakeholders. Combined with support from our operational and analytics experts, our platform can help you keep your finger on the pulse of your employees’ perceptions, and identify meaningful actions to drive sustainable improvements. Get in touch to see how we can help your organization build a people analytics solution tailored to your strategic goals.