People analytics are transforming the way organizations manage their operations and workforces, enabling companies to assess and act on everything from productivity and performance to employee engagement and satisfaction. HR organizations in particular can use this type of analytics to help address complex challenges such as employee retention and talent acquisition.
Despite these benefits, many companies are stuck in neutral due to a lack of understanding about what it means to build strong analytics capabilities. In a Deloitte survey, 75% of companies recognized that people analytics were “important,” but just 8% thought their organizations were “strong” in this area.1 Here are a few suggestions to help jumpstart your organization’s understanding of people analytics and set you on the path toward data-driven HR.
1. Build a Diverse Team
A people analytics team should be multi-disciplinary, combining employees with business knowledge, IT expertise, talent management insight, and consultative skills. It is often hard to find individuals with all these traits, which means companies must think beyond the HR organization and pull in people across functions.
2. Connect Analytics Directly to Business Strategy
With data so prevalent in HR organizations, a good way to make a powerful case for investing in analytics is to focus on an area that is relevant to the business strategy. For example, consider a company that wants to grow organically by entering new markets, which will require a larger workforce. To help address this need, the organization could analyze a targeted data set to evaluate the effectiveness of the recruiting process, such as examining the number of interviews candidates must undergo, how many drop out of the process, and when they drop out.
Success with people analytics hinges on technology investments being a well-thought-out part of the overall plan from the start.
3. Consider Technology Sooner Rather Than Later
HR organizations require more than just spreadsheets for accessing and analyzing information, and platforms such as SAP SuccessFactors solutions offer embedded, sophisticated analytics capabilities. This technology should not be tacked on at the end of an HR transformation — success hinges on technology investments being a well-thought-out part of the overall plan from the start.
4. Don’t Overlook Data Quality
Your business operations and insights are only as effective as the reliability of your data, and the same holds true when it comes to analytics. To ensure that you get the most value from adopting people analytics, the HR and IT organizations should work together early on to build a program for cleansing, rationalizing, and continuously monitoring data quality. It is critical to involve the HR organization in this process, as the HR staff has significant knowledge of the data and its context.
Shift into Gear with People Analytics
HR organizations can’t remain stuck in neutral for much longer. Research shows that companies using people analytics outperform their peers in the quality of hire, retention, and leadership capabilities.2 Deloitte has extensive experience assisting HR organizations in developing analytics capabilities, including devising a strategy, defining the organizational model, building the team, implementing the technology, and designing the data governance processes. Visit www.deloitte.com/sap or contact me at firstname.lastname@example.org if you’re ready to shift into gear with people analytics.
As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries. Certain services may not be available to attest clients under the rules and regulations of public accounting.
1 Deloitte, “2015 Global Human Capital Trends” (www2.deloitte.com/us/en/pages/human-capital/articles/introduction-human-capital-trends.html). [back]
2 Bersin by Deloitte, Deloitte Consulting LLP, “High-Impact Talent Analytics: Building a World-Class HR Measurement and Analytics Function” (October 2013; www.bersin.com/library). [back]