Three reasons to adopt ‘people analytics’

Human resources (HR) functions are under pressure like never before to provide actionable insights and analysis from data across the enterprise. The problem is human resources functions have tended to under-invest in systems that facilitate and make this kind of analysis more accessible to HR and the managers they support. Many executives lack even basic reporting into their organizational health from a people perspective.

Reporting is necessary but not sufficient for HR and managers to make better choices. Beyond mere gathering and presenting backward-looking information about workers, the gold standard is so-called “people analytics.” People analytics refers to a practice of connecting HR data to business outcomes in a way that allows for proactive, purposeful, forward-looking action.

In many ways, having the data infrastructure in place to support basic reporting tools is a necessary first step, particularly for medium and large organizations to get to people analytics. Having the ability to report on metrics like turnover, overtime pay and time to fill is a precursor to more value-added activities such as predicting what reduces turnover, overtime pay and time to fill. The path to get there involves deeper analysis and better, quicker decisions. Following are three reasons to adopt people analytics:

1. Flexibility and reliability. Even in organizations that do not fully realize the value of having readily-accessible, high-quality HR data, the need exists. In that kind of environment, one might find teams of business analysts who pull data from myriad sources and “systems of truth.” Those analysts must then translate data from one system in a way that makes it compatible with data outputted from other systems. Along the way, we see a fragmented, makeshift set of systems that lack compatibility both in terms of user experience and security.

The end result of the business analysts’ work in this kind of case is often unreliable because it requires a level of touch and manipulation that is prone to errors, even when the work behind the scenes is performed by capable people. Equally as important, however, is the idea that the output is inflexible. For example, if a business leader needs the turnover data to exclude retirees, the business analyst needs to narrow the dataset accordingly and re-send the results. If the urgency of that request is high, the analyst cannot always make the deadline. So, in addition to being somewhat unreliable, the data is also inflexible in many ways since it requires a human intervention.

To the degree possible, HR systems strive to remove the human element from the data analysis equation to streamline the process of achieving insights and to make it more reliable. That is possible because the HR system itself is the source of the data. Rather than having to ask a business analyst to cut the data a different way, an HR system with sufficient capabilities will allow a user to perform that action with a higher level of efficiency and accuracy. It also makes it more likely that executive-level users will utilize the information.

People analytics refers to a practice of connecting HR data to business outcomes in a way that allows for proactive, purposeful, forward-looking action. 

2. Integration with other systems. Most organizations already pay for integrations for their HR business processes. For example, an integration involving an HR system and background check vendor is common where a new hire process kicks off a background check process. But beyond the tactical administration of HR programs, data integration is also very important. Data integration refers to the aggregation of human resources information from multiple platforms, as opposed to a business process in one system kicking off a business process in another system.

In the previous scenario, where a user is pulling information from different sources and aggregating it into something meaningful, the “integrator” is a human person. And there are limitations to having human persons serving as data preparers. Employees or contractors are expensive, error-prone and subject to time constraints. A better use for people in a business context is as interpreters of data, rather than preparers. Ideally, the “integrator” is a software program that has the ability to pull together information from many different sources to become a single source of truth.

When an HR function gets to the point where it is able to automate the integration of data between HR, payroll, finance, purchasing, IT and other systems all into one, people analytics is given a chance to develop into an actual practice within the organization. For example, instead of thinking about performance of sales people as a purely “HR issue,” we can look into financial data for their assigned sales territory and see how their sales have varied throughout the year and in response to pricing changes due to raw material costs (from the purchasing system). Putting everything together means we have a more complete picture of what is actually happening.

3. Self-service analytics. The third reason HR software will help an organization adopt people analytics is because of the potential for self-service analytics. Another issue with having a person integrating HR data for the purposes of creating insights is that it puts a middle-man between the user and the data. “User empowerment” is a concept that refers to allowing users of a system or software to conduct their own analysis. So, rather than relying on the business analyst to exclude or include certain data in a dashboard or report card, the manager or HR user can do it themselves.

Of course, user empowerment assumes that the user is capable of and willing to perform certain kinds of analyses themselves, which varies based on the individual. However, assuming that a particular person wants to have that control over data manipulation herself, the easy answer is to provide that level of control. As HR software becomes more and more advanced and user-friendly, we will start to see “data discovery” become a huge value proposition for businesses; that is, users will be able to navigate through information and interactively build their own reports.

Effective self-service analytics is only made possible when the human intervention commonly needed to prepare HR data is removed and replaced with software integrations with systems that house “ancillary data,” which refers to data that is not expressly HR-related. For example, the territory sales data, procurement/pricing data and shop floor output data all come from different sources but, when brought together, can produce meaningful insights. Giving users the tools and ability to make sense of it, without having to spend time bringing it together, will allow the organization to explore relationships between variables in ways never before possible.

To conclude, in today’s technology environment data is everywhere. Interpreting it is the hard part. When we look at HR strategy, being “data-driven” is a top priority in relatively large organizations, despite under-investment in HR software and technology. The first step in becoming data-driven and focused on people analytics is getting to a flexible, reliable, single-source of truth. The second step is making sure all primary and secondary data sources are brought together through software integrations. The third step is to empower users by giving them appropriate security access to interpret and derive conclusions from this data. Without flexible, reliable, integrated and accessible information produced by a functional HR system, people analytics will remain an aspiration for those organizations unwilling to make that investment.