HR leaders can follow 4 best practices to ensure responsible use of employee information and analytics in decision making.
Most of us are happy to share personal details with our employer if it helps us choose between benefit options, avoid safety and compliance risks or save time filling out forms. We are less comfortable if personal information is used to make decisions about work opportunities or pay.
In the wake of high profile privacy breaches, organizations have become more vigilant about customer data, but are they giving due attention to employee data?
Methods used to collect data about employees are growing, and range from standard employee engagement and exit surveys to data mining of publicly available professional data and highly experimental employee monitoring approaches like microchipping. At the same time, the use of talent analytics is also expanding.
Transparency is the key to trust, and employers need to articulate the benefits
“It raises new questions for HR about digital ethics,” said Robin Boomer, Gartner Senior Executive Advisor, during Gartner ReimagineHR Conference in Sydney, Australia. “As your employees’ advocates, HR leaders can and should set and enforce employee data ethics principles for their teams and their organizations,” he says.
4 Employee Data Usage Best Practices
HR leaders can get started by following these four best practices.
1. Identify and learn from key partners
HR, privacy and other leaders should be asking key questions of each other. What data is used and how? Who has access and where is the data stored? What policies and procedures are in place to protect our data? What regulations apply to us? It’s not a one-way learning experience, so make sure to identify and share learnings with other key stakeholders — from legal and compliance or data privacy organization, IT or information security executives, data and analytics team and other business leaders in sales, marketing and finance.
2. Articulate an ethics code grounded in culture
Take your organization’s culture statement and work out how it applies to your use of data. For example, if innovation is top of…continue reading article
