Three Problems with Combining People Analytics and Performance Management, and How to Overcome Them

Posted by Kathi Enderes on October 16, 2018.

In the blog “Merging Performance Management and People Analytics,” I wrote about how combining performance management and people analytics can lead to better and more frequent data for making people decisions and evaluating performance, as well as the opportunity to embed both performance management and people analytics into the flow of work itself. Bersin research shows that combining these entities can drive increased business and workforce performance.1 The performance management software vendor Reflektive, for example, effectively integrated its performance management and people analytics efforts.2

If this sounds too good to be true, it might well be. Data is abundant, but insights are scarce. Too much data could result in paralysis, confusion, and a lack of decision-making. Solution providers and organizations each have a role to play to guide individuals, teams, and leaders to act based on people-related insights. The former should focus relentlessly on a consumer-grade experience to create solutions that are adopted instead of ignored and add value instead of noise.

Simplicity is key when designing user interactions. Embedding simple, action-oriented alerts or suggestions into work systems like email, project management, collaboration, or sales management systems helps further the integration of people-related decisions into the flow of work.

Organizations that use combined performance management and people analytics insights are accountable for helping people focus on what matters, too. These companies should identify what types of data predict performance and focus insights on those vital areas. But it can be easy to lose sight of important objectives while integrating these previously disparate data sources. Just because data can be combined does not necessarily make it meaningful or actionable. Forward-thinking organizations use data analysis to determine the factors that drive critical outcomes in people-related dashboards or alerts.

The last—and arguably most significant—challenge involves growing ethical concerns. In times of heightened data privacy and security risks, organizations and solution providers should collaborate to protect individual data and mitigate privacy concerns. Performance management processes contain deeply personal data around an individual’s performance and development that needs to be protected, both legally and ethically.

The importance of data privacy has only been heightened by high-profile breaches in the recent months, and new technologies present new ethical risks. Algorithms and machine-based decisions could perpetuate bias due to flaws in the underlying data or the algorithm itself—“algorithmic bias” can seep into an organization’s fabric and multiply human bias with incredible efficiency. Organizations should monitor machine-generated decisions to ensure they are reasonable and impartial. In turn, solution providers should leverage algorithms that actively decrease partiality issues and improve outcomes, and constantly review the results to avoid teaching machines human biases.

The opportunities presented by integrating performance management and people analytics are plentiful. Done right, the insights gained from integration can enable individuals to do their best work and leaders to support team and organizational performance. Organizations and solution providers each have a responsibility to mitigate the risks of overwhelming individuals and leaders with too much data and of making false conclusions that do not result in desired outcomes. Most importantly, they should take steps to systemically address data privacy concerns and counteract algorithmic bias.

Kathi EnderesKathi Enderes, leads talent and workforce research for Bersin, enabling organizations to transform work and the worker experience for increased organizational performance. With over 20 years of global human capital experience from management consulting with IBM, PwC, and EY, and as a talent management leader in large complex organizations, she specializes in talent strategies, talent development and management, performance management, and change management. Kathi holds a doctorate in mathematics and a master’s degree in mathematics from the University of Vienna, Austria.

1 High-Impact People Analytics, Bersin, Deloitte Consulting LLP / Madhura Chakrabarti, PhD, 2017

2 “Reflektive Acquires Shape, Leveraging People Analytics Innovation for Real-Time Performance Management and Growth,” Reflective, 2017,

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