HR Answers: Getting Started With People Analytics

Although there is a lot of buzz about the growing use of analytics within HR, many organizations large and small still grapple with the best way to get started on their analytics journey. Concerns about data access, data quality, analytical tools and more often get in the way of building a baseline capability in people analytics.

Based on research that we’ve conducted at Cornell’s Center for Advanced Human Resource Studies, several common barriers stall progress in making more data-informed decisions about how and where to invest in talent. At the same time, we are seeing organizations take initial steps to gain buy-in for people analytics investments and build on this progress over time. So, if you would like to bring more analytics into your talent decisions, how should you get started? Here are five tips:

1. Identify an important people-driver of a key business outcome. Most people analytics groups gain considerable momentum when they are “pulled” into a business problem or opportunity (versus “pushing” data or metrics out to the business—which may or may not be relevant to a business problem.) For example, a credit union with multiple branches may see that member satisfaction scores (a business driver) vary considerably across branches. This is a prime opportunity for HR to step in with data that could explain why some branches tend to outperform others. Do the branches vary on key talent dimensions (e.g., manager experience, turnover, engagement)? Talking to business leaders about their main concerns opens opportunities to collect relevant people data that helps solve business problems.
2. Worry less about tools and systems. A common refrain in conversations about people analytics is “We don’t have the right tools and systems.” While many organizations indeed lack sophisticated tools and technology for collecting people data, this shouldn’t get in the way of taking initial steps to become more data-driven. Even relatively “simple” data, analyzed in Excel or other basic (but widely-available) software can provide insights that would otherwise go undetected. As one example, imagine using a third-party skills assessment as part of the hiring process—shouldn’t we check to see whether high scorers on the assessment actually end up performing better? It’s an important question that doesn’t require much in the way of data or sophisticated tools or analysis.
3. Borrow from other parts of the business. The field of people analytics follows from a longer history of using analytics in other business functions such as finance and marketing. Oftentimes we find that organizations already have systems and tools that provide some form of business intelligence to inform decisions. Building on this existing infrastructure provides a starting point for understanding the data, systems and tools that might be leveraged for talent-related purposes. Another benefit is that HR can learn from internal data experts and begin to speak a common language.
4. Differentiate between metrics and analytics. HR has a much longer history of tracking metrics and is only starting to embark on true analytics projects. Metrics such as time-to-fill positions, cost per hire, training completion rates and the like are helpful for showing what happened in the past, but they are less useful for forward-looking decision-making. Metrics also tend to stand alone on dashboards and people reports without much context as to why they are moving in a given direction. Analytics, on the other hand, involves linking different data sources to better understand underlying causes and potentially forecast future conditions. For example, some companies have used analytics to forecast the future size and shape of the organization based on historical trends around hiring, promotions and attrition, allowing them to develop more informed staffing plans for long-term growth. Metrics can be helpful to a point, but look for ways to bring more analytics into the conversation.
5. Start small and build a data-driven case for change. A common mistake when getting started in people analytics is trying to do too much too fast. In the early stages of such initiatives, many organizations are not ready for advanced analytics and complex tools—in fact, these efforts can backfire, especially when they cannot be explained in simple terms. A better strategy is to identify a small and manageable (yet business-relevant) problem or opportunity, collect some relevant data that informs the situation and develop a case for making a change. For example, one large organization estimated the cost of turnover for its call center staff and used the alarmingly high figures to convince business leaders overhaul their approach to staffing and managing the call centers.

Getting started with people analytics is a challenge, especially for the HR function, which historically has not been equipped to manage from a foundation of data and evidence. However, given the growing availability of people data and the need for today’s HR professionals to bring analytical acumen to decision-making, many organizations are investing in ways to grow this capability. Think “business first,” and look for small but impactful ways to introduce people analytics to your organization.

John Hausknecht is a professor of human resource studies at Cornell University’s ILR School. He teaches and writes about HR analytics with a particular emphasis on employee turnover.