Making people analytics more intelligent: How technology empowers HR analysts to answer advanced analytics questions

HR analysts perform a critical function for businesses. By collecting, analyzing, and interpreting workforce data, they enable talent leaders to make informed decisions about their people and business. From measuring the success of a new training initiative to comparing the efficacy of various recruiting practices to parsing reasons for turnover, an HR analyst can find, package, and explain the information that a talent leader needs to identify potential workforce issues and determine appropriate solutions.

Historically, access to HR data has been fairly limited to HR analysts, meaning talent leaders had to request reports or key performance indicator (KPI) metrics from an HR analyst. This often led to the HR analyst role being seen as an “order taker” as opposed to a strategic advisor, but recent innovations in HR technology are changing this status quo. 

Next-generation people analytics tools provide talent leaders with easier access to actionable, data-driven workforce insights. As leaders enjoy more direct access to this information, and AI helps automate lower-level data analysis tasks, HR analysts now have a strategic opportunity. Instead of spending most of their time, effort, and brainpower on fulfilling other stakeholders’ requests, they can focus their energy on unlocking new and greater value from HR data.

Faster data insights for a competitive edge 

Previously, high-quality data was extraordinarily challenging to access due to fragmented data sources or inconsistent data formats. Analysts often spent days or weeks collecting, cleaning, and integrating the data required to provide the information someone requested. As a result, by the time they presented the insights, the pertinent data had often already changed.

Developments in technology have greatly reduced this risk, eliminating the high costs of data extraction, harmonization and replication. You can now quickly access information from a single source of people data — one that’s fully reliable — as well as add business data for valuable context. This shift means you can leverage data for strategic decision-making more quickly and cost effectively, giving your organization a competitive edge. 

For example, if your organization is seeing a rise in employee turnover and a decrease in employee satisfaction, you can analyze data from performance reviews, surveys, and exit interviews to identify potential patterns and trends. With immediate access to the full set of data, an HR analyst can quickly uncover the underlying drivers and areas of greatest impact to provide guidance on how the business can adjust its strategies and policies to create a more enabled, engaged, and motivated workforce — whether that means offering more flexible work arrangements, creating professional development opportunities, or implementing a better recognition program. 

Better data and data analysis mean better decision making

With next-generation people analytics, you don’t just get faster access to insights; you also get higher-quality insights. The information is context-rich, which means the raw numbers and facts are enriched with relevant business semantics to make them more actionable and valuable for decision-making. This enables an HR analyst to provide meaningful insights that help business leaders make informed decisions that better align their specific business processes and objectives with their organization’s strategic goals. 

For example, if a company wants to improve its recruitment strategy, an HR analyst can perform a comprehensive review on the overall recruitment and hiring process to help identify — and prevent — bottlenecks that are impacting time to fill, cost per hire, and candidate quality. In addition, by bringing benchmark data into the picture, analysts can further validate the need for change and areas of prioritization based on an overlay of organizational and market data.  

Proactive problem solving with predictive analytics

An abundance of rich, reliable data, combined with advanced analysis technology, is shifting the HR analyst role from reactive to proactive. The latest people analytics tools enable you to look beyond the present day by making predictions about the future. You can build a custom predictive model to provide highly valuable information about specific areas of concern for HR teams, talent managers, and executives. 

For example, if there’s a concern with turnover at a given time, the model could analyze recent talent flow and churn trends and then forecast the expected turnover rate for the upcoming quarter or year. This helps you determine if it’s a seasonal trend or a long-term issue that needs to be addressed. By following up with custom what-if simulations of potential solutions to determine impact on retention, you can help transform turnover into a manageable risk.  

Maximize analyst impact with People Intelligence

HR analysts were once bogged down by incoming requests from talent and other business leaders, but improvements in technology have freed them to take on a more strategic role — one where they can enhance people decisions throughout the business. 

Take People Intelligence, SAP’s new people analytics solution, for instance. It provides direct access to pre-built workforce insights across all aspects of HR — for HR analysts and talent leaders. It also takes on the onus of harmonizing data from across the business and automating the integration of third-party data, allowing HR analysts and data gurus to spend more time on creating custom models and analytical applications. It’s this level of intelligence and flexibility that’s enabling organizations to transform workforce planning and business operations — with HR analysts front and center.  

To discover how your organization can benefit from people analytics, check out People Intelligence on SAP’s website or register to watch a virtual session for more in-depth information.

This article is part of a series covering people analytics. Check out the first and second articles.