How to Leverage People Analytics to Improve the Bottom Line
By Mary Anderson, VP, Shared Services, ManpowerGroup Solutions RPO
Like many HR practitioners, you’ve likely been reading about people analytics and know that many companies are investing serious resources to develop their analytics capabilities. You might be wondering how you can possibly get where you need to be because your company, like many others, struggles to get meaningful data– both quickly and accurately.
According to research firm Bersin by Deloitte, more than 50 percent of companies are operating at the lowest level of maturity in terms of people analytics. In comparison, a mere 4 percent of companies have reached level 4 (the highest level of maturity) in their people analytics, which is defined by predictive capabilities.
The question you might be asking yourself is: How do you get to the next level of people analytics when the level you’re currently at is so challenging? In the era of Big Data, the temptation might be to tackle everything at once. Instead, I would suggest breaking your approach down into smaller, more manageable chunks to build experience, confidence and credibility as you go. Here are three things you can do build a people analytics ROI for your organization and significantly improve your chances of success:
1. Focus on the Pain: Do you know the true pain points of your business? If not, that is the place to start. People analytics can only help your organization improve if you analyze the right data. Choosing the right data to analyze is the first step toward maturity and is not strictly an HR exercise. The most meaningful people analytics have a connection to data in all areas of the business. A recent article by McKinsey on people analytics provides an example that focuses on where to cast your recruiting net for the most success. But in order to look at all of the key elements that factor back into their recruitment strategy, the profiled organization pulled in 30 different data points spanning all areas of the business–including overall business performance metrics.
Looking at HR data points alone doesn’t allow you to draw meaningful conclusions beyond the HR arena. The data to be analyzed should reflect the very real challenges faced by the business. Those challenges may include leadership readiness, attrition of top performers and diversity initiatives, which are often the domain of HR and talent leaders. However, it could also include challenges from other areas of the business, such as sales performance, operational performance, compliance risks, cross-function collaboration and more.
"As people analytics takes a bigger role in an organization’s strategic roadmap, it is critical to bring data science professionals onto the HR team "
When you think about all the possible kinds of data to include, it can feel overwhelming. To get a seat at the table it is important to understand the key data intersects for your business, and to expand your approach beyond HR data to bring a broader viewpoint of people analytics to the organization based on your organization’s top two or three pain points.
2. Focus on Data Quality: When thinking about data quality, it all has to start with your systems. While some companies have made great strides in implementing a single integrated cloud-based HR system that allows one window into all HR data and analytics, there are still quite a few that are somewhere along the spectrum. No matter where your organization is, you can take action on your people analytics strategies now. However, it does mean that an increased priority has to be placed on the quality of data you get from each of the systems and how you bring it together to gain meaningful insights.
Creating a clear governance process for data collection and a system of rigorous validation before bringing your data into a centralized database is critical. Without this, you risk developing strategies and actions based on unreliable data. In addition, it jeopardizes your seat at the table as an informed and strategic business partner. Let’s face it–we have all had an experience where someone has provided us data that isn’t quite right. After many conversations and additional research, the issue is discovered and corrected. But from that point on, we doubt the data when it is presented, and it is very hard to walk back from that.
While it will take additional time and typically involves IT support to build the up-front data quality framework, it is worth the investment to ensure you are delivering clean data as a basis for your analysis and recommendations.
3. Focus on the Right People to Build People Analytics: Traditional HR professionals don’t always have the aptitude for or interest in data analytics–and that’s okay. But you cannot expect to be successful unless you have the right players on your team driving the right activities forward.
As people analytics takes a bigger role in an organization’s strategic roadmap, it is critical to bring data science professionals onto the HR team. The key to these professionals is finding a mix of statisticians and analysts who can correctly identify and explain trends, as well as those with a business consulting mindset who can bring those trends back to the company’s executive leadership with real recommendations on how to take action on the conclusions. Providing analytics without a clear business application has very little chance of long-term success or value.
While it may be a challenge to get a seat at the table to discuss the importance of people analytics and your company’s business strategy as an HR leader, it is achievable. The key to moving the needle is ensuring you are looking at the right data for your organization; that the data is clean and accurate; and that you have the right talent on your team to use that data to consult with executive leadership on driving business transformation. This will result in further analytics investments as an organization because, as Deloitte says in their recent People Analytics in HR article: when HR has the opportunity to show the value and ROI that investment in analytics can bring, it will result in a willingness to invest further and spur acceleration in people analytics capabilities.