The Potential of Microsoft's Copilot on Change Management
Damon Centola's groundbreaking work in the field of social network analysis introduced us to the power of strong ties within networks for driving change (Damon's book Change). As we look towards the future of enterprise networks, particularly businesses using the Microsoft suite, we are pondering the question: Can Microsoft's CoPilot help enable change management when applied to the Microsoft graph?
The Power of Microsoft Graph
In the modern enterprise, particularly those leveraging Microsoft, tools such as Delve and Usage Reports provide invaluable insights into the official reporting structure and interconnectedness between people. Yet, to truly harness the power of Centola's work, we must dive deeper into the unofficial structure of information flow within an organization.
Essentially, we need to understand the nodes within the network with strong ties. These are the individuals or groups who, through their connections, have the potential to instigate and spread change. One place this data exists is within usage reports, which Microsoft's system can provide through the Microsoft Graph.
Microsoft Teams, for example, shows the number of meetings held, the number of messages exchanged, and the number of emails sent. While these figures give us some insight, they don't necessarily indicate influential nodes within a network.
The Role of AI in Change Management
The key lies in understanding the quantity and breadth of the conversations that occur. A "chatty" individual isn't necessarily an influencer, but one who discusses a wide variety of topics might be. Microsoft's CoPilot can come into play here.
The application of CoPilot could involve identifying influencers within an organization by analyzing both the number of messages and the variety of topics discussed. Suppose a node or person within the network exhibits a higher-than-average number of messages and a broader range of topics. In that case, they may be an influential tie and, therefore, pivotal in managing change.
Unfortunately, at this time, the data needed to run this kind of analysis is too disparate and disconnected. The manual analysis would be painstakingly slow and likely error-prone.
The Future of AI and Change Management
But what if, in the future, Microsoft CoPilot, with access to your Microsoft Graph data, can process all the interactions between users? Would this enable us to run this experiment, analyzing admin reports and usage data from tools like Teams and Viva to identify the strong ties between users?
The potential here is staggering. With an AI like CoPilot at the helm, the concept of leveraging the open graph for change management could evolve drastically.
As we anticipate the release of CoPilot, these questions will become even more pertinent. How might an AI-powered understanding of our networks enable more effective change management? How can we harness the strong ties within our organizations to drive forward positive, impactful change?
The future of change management is undoubtedly tied to AI. We will be able to understand existing behaviors faster than ever. With the integration of tools like CoPilot, we may be on the brink of understanding our enterprise networks and users like never before.
