Optimizing Microsoft 365 Licenses Using Behavior Data (E3/E1/F3)

Hi everyone,

We are currently working on a Microsoft 365 license optimization initiative and would appreciate insights from the community and Microsoft experts.

Our approach focuses on two main areas: (1) Revoking licenses for inactive users, and (2) Reviewing active users to ensure their assigned license (E3, E1, or F3) aligns with actual usage and collaboration needs.

From a data perspective, we are leveraging Microsoft 365 usage signals such as Teams activity, Outlook email interactions, meetings, and SharePoint/OneDrive collaboration. While usage reports provide raw metrics, we are looking for guidance on how these signals should be interpreted and combined in a meaningful and fair way.

Specifically, we would like to understand: (1) Which usage metrics best represent user collaboration behavior? (2) Are there any recommended thresholds or patterns that help distinguish light, standard, and heavy collaboration users to map E3, E1, or F3?

Any best practices, references, or real-world experiences would be greatly appreciated. I'm sorry if this is the wrong forums to ask for. Thanks in advance for sharing your insights.