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HR Data as a basis for decision-making in daily business

“Data are just summaries of thousands of stories – tell a view of those stories to help make the data meaningful.” - People Analytics, or HR Data, comprises the application of data and analysis techniques for enhancing and optimizing HR processes and decisions. Burgeoning data volumes related to progressing digitalization, as well as increased decision-making in HR departments requiring measurable key figures, are lending this issue growing importance in the market. Data aid us in making strategic decisions and utilizing our company’s potential. The risk of misinterpreting results always accompanies data utilization, however. Inadequate expertise regarding the collected data often leads to wrong decisions.  A survey of executives, published in the Harvard Business Review, underscores how present this danger is in companies. 47% of those surveyed believe that HR specialists lack analytic skills.

All the more important then, when introducing People Analytics, to also train staff in analytical skills and to make clear that data can support decision-making only if analyzed and interpreted correctly. 

What exactly does the term “People Analytics” mean?

People Analytics examines past and present data while also looking at causal relationships, for the purpose of confirming these correlations with accurate data.

People Analytics combines two types of data:

  •  Operational data (OData) come from company applications, such as HR systems, and serve as a very important decision-making tool for management. The collected data are, for example, personal data from employees or applicants.
  • Experience data (XData) differ fundamentally from OData by focusing on human factors, such as employee motivation.

Now that we’ve clarified the terms “OData” and “XData,” let’s take a look at what a company can achieve by means of the analysis and professional interpretation of these data:

  • Improving processes and strategies
  • Detecting developments at an early stage, such as cases of sick leave
  • Deriving and operationalizing measures
  • Detecting critical developments
  • Working with scenario analysis

A possible question that you can answer using People Analytics is:

For which employees is there an increased risk that they’ll leave the company again after just 12 months?

The 3 levels of People Analytics

Personnel controlling captures the current state of affairs and considers key figures over a pre-defined period of time. People Analytics, on the other hand, looks at forecasts and researches causal relationships. Appropriately conducting this research requires processing company data on multiple levels. The first level addresses data reporting and asks the question “What happened?” – Here, past performance levels are measured and checked regarding average turnover rates, for example. This part concerns the descriptive perspective of the data. The second level deals with the “why” question. Drivers for strategic human resources are identified, such as employees’ payments and satisfaction as drivers of turnover. The third level looks at future actions, such as better payment, which influences future turnover probability. The aim is to create models, forecasts and relationships, and to discern causal relationships between data. This procedure requires that the

What solutions in People Analytics does SAP offer?

SAP, too, offers several possibilities for People Analytics:

People Reporting is related to operational key figures, i.e., it asks the question “What happened?” It serves the analysis and understanding of employees’ needs and motives, for arriving at a better appreciation of proactive and personalized HR management.

The Advanced Analytics analysis tool looks at the existing staff as a whole and its structure and dynamics over the course of time, for the sake of a better decision-making basis regarding human capital in the company that is available and will be required in the future. Additional license costs will then apply. The highest level of Advanced Analytics comprises autonomously operating processes that provide support in difficult decision-making.

Enterprise Planning is comparable to the third level of People Analytics. A roadmap supports planning and implementation of the digital journey. Future scenarios can still be simulated and storytelling analyzed and planned. Additional license costs again apply. In sum, the tool identifies risks and qualification gaps while mapping what-if scenarios and cost models, with the aim of optimizing personnel requirement planning and developing strategies for hiring talented people.

How does it differ from SAP Analytics Cloud?

The SAP Analytics Cloud (SAC) offers employees a simple cloud solution as a data source. Here, too, the product serves the purposes of reporting, analysis and planning. In contrast to SAP People Analytics, however, the SAC is a comprehensive Analytics solution that can be integrated with the SAP Data Warehouse Cloud. The greatest advantage is the possibility of integrating data from the SuccessFactors modules into other solutions, such as CRM or Finance. That requires a separate license as well, however.

There are three different approaches in SuccessFactors HXM: 

  1. Reporting: Provides information on HR processes
  2. Workforce Analytics: Insight into impacts on the HR environment
  3. Workforce Planning: Planning future processes

Reporting also allows using analytic tools such as Canvas, Table/Custom, Dashboard/Tile, and Stories. Canvas creates reports in tabular form, including their visualization. Table Reports provide real-time reporting and are displayed as lists. Dashboards and Tiles summarize and display multiple tiles on a single page. Here you can create diagrams and integrate data from both SuccessFactors and Workforce Analytics Data in Dashboards and Homepages.

The stories form part of the People Analytics solution, and support reports, dashboard creation and the presentation of charts, visualizations as displays, texts, images and pictographs.

The advantage here is that the system can make all relevant information available in a database. We therefore prefer to speak here of a “small SAP Analytics Cloud” embedded in SAP SuccessFactors.


The relevance of data to managerial decision-making is continually growing. Companies must instill a basic understanding of such data, however. They must train employees in the interpretation of data and in the presentation and processing of data sets. This approach will ensure that employees obtain and correctly apply the necessary expertise for data analysis and interpretation.

Moreover, companies must become aware that huge data volumes are making the situation even more difficult. Employees must discern conclusions and connections even with highly complex data, for subsequently using this information in decision-making.

Data and their analysis can provide additional support in strategic decision-making, but should never be treated as the only single starting point.