Relational Analytics: Taking people analytics a step further to improve performance

Addressing hot button HR issues such as gender inclusivity, upskilling/reskilling, and employee retention require deep analytical insights. CEOs and CHROS understand this. Nearly 70% of companies are looking to build their People Analytics database. While tech giants like Google and Dell have been successfully using people analytics to improve performance for almost a decade, only a small percentage of organizations leverage people analytics today. According to a TCS survey, HR accounts for only 5% of Big Data investments. One of the major factors inhibiting large scale adoption of analytics in HR is the lack of understanding of the talent metrics that drive performance in the organization. This is where relational analytics can help C-suite leaders better assess and improve performance across the organization.

Relational analytics: Tapping into the emerging discipline 

While attribute analysis based on employee traits and background is a necessary first step, it is often insufficient for holistic decision-making. Relational analytics, an emerging field that focuses on employee relationships with peers, customers and other stakeholders, enables managers to gain a true understanding of employee performance in order to improve it. One company, for instance, found that their highest performing engineers had more meetings and relationships with others. So, they rearranged the engineering team’s offices and pushed the cafeteria to the other end of the campus – so the team members were forced to walk across the campus and meet others.

How does relational analytics create value? 

Relational data goes beyond aggregate people data and provides a deeper understanding of performance within as well as across teams. This form of analytics is relatively easy to deploy as relational data already exists within organizations in the form of digital exhaust such as e-mail exchanges, file transfers, etc. 

Here’s how it works. Analyzing emails, work chat and online communication between employees and external parties provides valuable insights into which individuals, teams or business units will be successful and why. According to HBR, relational analytics focuses on the following six signatures: 

Ideation: Which employees will come up with the best ideas 

Influence: Which employees will change the behavior of their colleagues

Efficiency: Which teams will complete projects on time 

Innovation: Which teams will drive innovation

Silos: Which functions within the organization are siloed 

Vulnerability: Which employees can the organization not afford to lose

In essence, analyzing the six key signatures helps organizations identify their high potential employees based on their ability to influence stakeholders and drive innovation. This knowledge can be immensely useful for HR leaders in understanding which employees they must retain and how to break down the silos around them to increase their influence. Here are two companies that have effectively leveraged relational analytics.

Genpact: Relational analytics for performance improvement

Genpact, the leading professional services firm, analyzed months of messaging data for communication patterns. As a result, the company was able to identify certain types of communication behavior that drove better relationships, and hence, superior business performance. Today, Genpact can identify ‘rockstar performers’ who are more focused, influential and respected - with 74% accuracy – to build high performing teams.  

Nielsen: Relational analytics for talent retention 

Nielsen launched a predictive people analytics model to increase employee retention. The model was initially applied to variables such as gender, age, manager rating, etc. In order to make the model more relevant, the company included interactions between employees. It analyzed factors such as whether or not employees built critical contact points in the first year of their employment and tracked when their first check-in with their manager took place. The results of the analysis were critical in improving retention during the first year. 

Putting relational analytics to work

Relationships and interactions evolve constantly, making timely analysis critical to driving value.  Consider using tools and developing easy-to-understand dashboards to disseminate the insights quickly to HR leaders. Another important concern that needs to be addressed while implementing relational analytics is privacy. One way to ensure total transparency is to create employee agreements that highlight the type and depth of interaction information being collected via digital exhaust. Done right, relational analytics can provide evidence-based insights necessary to improve innovation, identify top leaders and improve performance across functions. 

Sources: 

https://www.forbes.com/sites/joshbersin/2017/12/16/people-analytics-here-with-a-vengeance/#5e50fc2832a1

https://hbr.org/2018/11/better-people-analytics 

http://www.thelowdownblog.com/2018/11/relational-analytics-why-measuring-who.html

https://www.analyticsinhr.com/blog/hr-analytics-case-studies/ 

https://hbr.org/product/better-people-analytics-measure-who-they-know-not-just-who-they-are/R1806E-HCB-ENG?referral=03069 

https://joshbersin.com/2018/10/what-emails-reveal-about-your-performance-at-work/

https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/using-people-analytics-to-drive-business-performance-a-case-study