Reducing Employee Attrition with ONA: A Case Study from a European IT Company

Employee attrition poses a considerable challenge for organizations, leading to loss of talent and resources. To address this issue, many companies are turning to Organizational Network Analysis (ONA) as a powerful tool to predict and mitigate attrition. In this article, we will explore how ONA can help companies reduce undesired talent retention by identifying potential attrition scenarios, using a case study of a European IT company that successfully leveraged ONA to predict attrition based on the level of influence of employees and the ratio of interactions received versus provided at the team level.

ONA is a data-driven approach that involves studying the interactions, relationships, and communication patterns within an organization. It provides insights into the informal networks that exist alongside the formal organizational structure, helping organizations understand how employees collaborate, share information, and influence one another.

Key ONA Metrics for Predicting Attrition

To predict attrition, ONA focuses on two key metrics:

1. Level of Influence: This metric indicates the influence an employee has within the organization. Notably, it also reveals that peripheral employees, those who are disconnected from the organizational network, have a higher attrition risk than well-connected employees. Influential employees can significantly impact their colleagues and potentially influence their decisions to stay or leave the company.
2. Ratio of Interactions Received vs. Provided: This metric highlights the engagement level of employees within the organization. Teams with more interactions received than interactions provided are at higher risk of attrition. Employees in these teams might feel disconnected or undervalued, making them more likely to consider leaving the organization.

Case Study: European IT Company's Success with ONA

Let's delve into the case of a European IT company that harnessed the power of ONA to predict attrition based on the level of influence and the ratio of interactions received versus provided at the team level.

This IT company was grappling with a persistent issue of high attrition rates, which was negatively impacting productivity and morale.

The company implemented ONA by collecting data on employee interactions, relationships, and influence levels leveraging both active and passive data sources. The analysis focused on both formal and informal networks within the organization.

Results:

1. Identifying Peripheral Employees: The ONA data unveiled that peripheral employees, those who were less connected to the organizational network, had a higher attrition risk. The company recognized the need to address their disengagement and consider tailored retention strategies.
2. Teams with High Attrition Risk: By examining the ratio of interactions received versus provided, the company identified specific teams where employees were more likely to leave due to a lack of engagement and communication. These teams became the primary focus of the organization's talent retention efforts.
3. Tailored Interventions: Armed with the insights from ONA, the company implemented targeted interventions, such as team-building activities, mentorship programs, and communication enhancement initiatives, to boost employee engagement and reduce attrition risk.

Outcome: The company successfully predicted attrition with 85% accuracy using ONA data. Moreover, they achieved a significant reduction in attrition rates within the identified at-risk teams, resulting in improved overall employee retention and organizational performance.

Conclusion

Organizational Network Analysis, with a focus on the level of influence and the ratio of interactions received versus provided, is a valuable tool for organizations seeking to reduce undesired talent retention by identifying potential attrition scenarios. The case study of the European IT company exemplifies the practical application of ONA, showcasing how it can help predict and mitigate attrition, ultimately leading to a more stable and productive workforce. By addressing the attrition risks identified through ONA, organizations can foster a more engaged and satisfied workforce, thereby reducing the loss of valuable talent.