Creating A Five-Star Consumer-Like Experience With People Analytics

Dr. Christian Liebig

As new generations enter the workforce, they expect HR processes to be designed just like the services they use in private life. Employees are no longer tolerant of a poor user experience at work. We must acknowledge that employees expect and deserve a “consumerized” experience at work, what is created to a large extent through HR services.

Beyond the employee perspective, there is a business reason: Jacob Morgan recently outlined that companies investing in employee experiences outperform those that don’t.

To create these consumer experiences with our HR services, we must insert analytics in every aspect of HR and use our data to its full potential. This way, we can gauge data at every touchpoint along any HR service. We gain insights from what drives satisfaction or dissatisfaction at a specific moment, which matters.

With these insights, we are able to create new programs or improve existing ones that are designed for a 5-star consumer experience.

Real-time data helps make better decisions in HR

Real-time data enables us to integrate technology into everyday decision-making. By using data analytics, we create transparency for key performance indicators, such as talent acquisition volume, attrition of top performers, or women in management. It also helps us understand employees’ behaviors and needs. This allows us to react quickly to changing situations and design more customized, user-friendly HR programs.

Digital boardrooms and customized reporting help us form a  data-driven culture at every level of the organization. Insights from data and analyses provided in such tools have the power to make better decisions for both perspectives: to boost HR  consumer experiences and to help us run HR like a business.

Disruptive technologies change the way we think and perform HR

Further opportunities arise when people analytics is combined with other disruptive technologies, like machine learning or blockchain. Not so long ago, we pushed many aspects of HR work to the end customers and called it “self-service.”

This was the wrong approach. People don’t care if they have to perform a task that is not relevant to them but needed by the HR department. But what if:

  • A machine learning algorithm was routing HR tickets in a clever way or answering the first-tier questions right away? This could save a lot of time for the consumer to interact with HR as they don’t have to first learn the concept of the tickets and components before submitting a query.
  • An app recommended the appropriate learning courses depending on the individual situation? People wouldn’t need to browse thousands of learning offerings to find the right ones. They could start learning right away. As Jason Averbook points out in his book, The Ultimate Guide to a Digital Workforce Experience, we need to remove the term “self-service” from our vocabulary.
  • The standard self-service options don’t meet the needs of employees any longer.

People analytics helps personalize moments that matter for a 5-star consumer experience. By inserting people analytics into any touchpoint along the employee journey, we can personalize those moments that matter. This helps HR meet the expectations of a consumerized experience at work. In addition, HR is better able to measure, manage, and predict the impact of their operations.

For more on this topic, see “HR Customer Experience: Setting The Scene For Success.”

Dr. Christian Liebig

About Dr. Christian Liebig

Dr. Christian Liebig is Head of People Insights with SAP SE. In his role, he focuses on creating superior talent experiences by bringing together our innovative HR strategy and data science on combined “X” (experiences) and “O” (operational) people data. Prior to this, Christian led in his role as the senior manager of HR strategy, planning, and analytics. Christian studied Industrial and Organizational Psychology at the Universities Mannheim / Germany, Saarbruecken / Germany, and Amsterdam / Netherlands. He holds a doctorate in Economics from the University of Mannheim.