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Optimizing Return-to-Office Strategies With Organizational Network Analysis

Using organizational network analysis to map employee work relationships and patterns helps companies answer critical questions for hybrid work planning

Source | sloanreview.mit.edu | Rob Cross | Peter Gray

Leaders of organizations large and small are struggling to define return-to-office strategies that reflect an appropriate balance of in-person and virtual interactions. In the absence of data, many leaders are advocating for hybrid models based on intuition. You don’t have to look far to find examples of companies advocating for policies fueled by a desire to get back to “seeing people,” or the blanket belief that engagement or innovation is suffering in virtual settings. But such approaches don’t optimize business performance, innovation, or engagement, because they are blind to the informal networks through which collaborative work happens.

For most organizations, the balance between in-person and virtual interactions will certainly shift as a result of the pandemic. In order to coax back employees who have personally experienced the benefits of fully remote work, leaders will need to offer a compelling rationale for why work models that include some degree of in-person collaboration are not only good for the company but also valuable for employees.

Organizational network analysis (ONA) — a methodology that maps employees’ working relationships — offers a novel approach for guiding return-to-office decisions. ONA provides an evidence-based lens that can help leaders understand which connections among employees should ideally happen in person and which ones can occur virtually, as well as the benefits that each modality produces for the employee and organization. This method also helps motivate employees to resume some in-person interactions by showing them how hybrid work can improve their own effectiveness.

ONA is uniquely positioned to address three critical questions in a return-to-office strategy:

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Source
sloanreview.mit.edu
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