Did you ever cut an onion while cooking? If you did, I bet it made your eyes tear. The well-known burning sensation in the eyes is simply a reaction to the sulfur that spread in the air when you destroy the onion’s cells. But what if you peel the layers of the onion one by one? There will be less damage to the onion’s cells, and therefore, fewer tears in your eyes.
The hierarchical definition of People Analytics
People Analytics is just like an onion. This domain of expertise has many practical layers. Its hierarchical definition includes at least five perspectives: C-level and business perspective, HR processes, data in HCM and other HR-tech platforms, data science methods, and the daily activities of the People analyst. If you try to cut through the entire hierarchical structure of this multidisciplinary profession, it will be so hard to grasp, that it will make you cry. Well, at least metaphorically. However, if you explore the layers of this definition one by one, you’ll get a thorough understanding that eventually will enable you to impact your organization – Tearless guaranteed!
The variety of roles that are involved in any People Analytics project within the organization contributes to the complexity of this practice. Notice that in effect, each layer in the structure of People Analytics definition is influencing and being influenced by the nature of the layer on its top and bottom. For example, the data stored in HR-tech platform influences but is also influenced by the HR processes that generate it. This complexity implies challenges in People Analytics activities.
The language of business
A crucial part of your challenge in People Analytics is the effort to establish communication between different professionals. In the hierarchy illustrated in the People Analytics definition, you have a C-level perspective above HR processes and data science beneath. Therefore, you must ensure communication between two kinds of professionals: executives and data experts. I consider this communication as an important layer to peel, in the onion metaphor.
The People Analytics journey enables HR managers to become more strategic because they speak the language of the business. Obviously, they must do so, since People Analytics is all about impacting the business by the right questions and insights derived from people’s data. However, they can support decision making, only if the people who are in charge of data science projects can communicate effectively with business leaders.
The role of the People Analytics leader is considered sometimes as a translator, the enabler of this communication. The People Analytics leader must make sure that the data scientists understand the business needs in workforce-related analysis, come up with the right business questions to analyze and return with the best storytelling with data. The People Analytics leader must also make sure that the owners of HR operations, who may be in charge of BI in the domain of workforce, understand the needs of data consumers among the executives.
Demystify People Analytics
On the other hand, you have executives. They need support too, on their journey to the data-driven organization. Perhaps they need you, the People Analytics Leader, to demystify this domain for them. Business leaders may be familiar with quantitative methods in other domains, e.g., Marketing, Finance, and Operations. But how deep is their understanding of statistical models and algorithms in the field of the workforce? Do they really know how to interpret the insights derived from the shiny tools and methods of People Analytics to the right decisions about people, careers, and employee experience? They surely can benefit from learning some new terms, to avoid the inconvenience experience involved in misunderstanding concepts, methods, and technologies.
Democratizing data is a process, not an outcome
Enabling the communication between the data professionals and the data customers is actually a part of the process of democratizing data in your organization – a significant part of preparing a vital portion of your workforce for the future. Though democratizing data is relevant to all parts of the business, the domain of workforce apparently lags. Implementing tools for telling stories with data within the HR department is important, but it is certainly not enough. The gap in communication must be close too. Closing the gap will enable the process of getting the business question right, ensuring data integrity and transparency, iterating to find the best algorithms, and getting people to use the insights in their decision making.
Therefore, the HR leaders, who are also responsible for learning, must lead simultaneously, toward data literacy among the management and toward understanding the business among the data pros. People Analytics is not about software or cloud services. It is a mindset that should become common throughout the entire organization. Closing the communication gap between executives and data pros is an important part of educating the workforce, and it may save a lot of burdens, just like peeling the onion’s layers, one by one.