1. What does the collaboration spider web really look like?

Traditionally, collaborations between employees in organizations have been imagined as a hierarchical top-down structure. More often than not, this traditional top-down hierarchy has been the go-to structure for staff-related planning and risk analysis. However, collaboration is closer to a holacracy—but even more distributed, since it’s not only about projects’ related tasks but also social connections within office spaces, company events, etc. Essentially, like a spider web. Check out the example shown in the below image:

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In the image above, the most connected people in the organization are marked as the green dots, and these are the employees who are very often engaged in more than one project and also the most connected employees when it comes to co-worker relationships inside a company.
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2. Why is it important to understand the employees who are the most connected with others?

It is hard to overestimate the value of social connections between workers, especially when they connect inside projects or collaborative teams. 

Employers should understand which employees act as fulcrums, holding together key structures and processes in the organization. While their performance reviews may be unremarkable, these employees are a unique type of high performer and can inordinately impact the productivity and retention of other team members.

When one of these socially connected employees leaves a company, the risk of connected employees becoming disengaged and leaving significantly increases. At Praisidio, we have seen situations in which one of these quiet connectors leaves, as connected employees pull away from the organization the internal processes they facilitated fall apart.

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3. How we find the connections between employees.

In the modern world, employees collaborate across roles, functions, levels, and geography using technologies such as email, video conferencing, Slack, calendars, task trackers, and many more. Using only the metadata, these technologies  provide the ability to identify collaborations and connections, and measure their strength.

At Praisidio, we discover and map collaborations as part of our product platform. We help identify non-traditional high-performers. By combining this data with other enterprise information we predict the risk of attrition, well in advance and with enough time for management to take action. Our machine learning engine also recommends specific actions to prevent attrition.

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4. Predict possible risks and be ready.

Identifying your most crucial connectors is just one step in building your culture and understanding your risk profile. To find out more about Praisidio, visit www.praisidio.com

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