In the fast-paced world of biotechnology, staying ahead requires not just innovation in the lab, but also in how a company operates and collaborates internally. A Fortune 500 biotech company, with a global workforce of 130,000 employees, faced the challenge of enhancing its business performance and gaining deeper insights into its internal collaboration and communication. The solution? A strategic implementation of AI-powered Organizational Network Analysis (ONA).
The Challenge
As the biotech landscape evolves, the need for rapid adaptation and efficient internal processes becomes paramount. For this biotech giant, understanding the intricacies of how information flowed within its vast organization was crucial. The goal was clear: to monitor and enhance business performance and secure insights into internal collaboration and communication. But how could such a large entity analyze and optimize its internal networks effectively?
The Solution: A Data-Driven Approach with AI-powered ONA
The company’s approach was innovative and comprehensive, combining active and passive ONA methodologies to uncover the dynamics of information flow throughout the organization. The active ONA component consisted of an online survey that mapped informal interactions like sharing information, technical support, personal support and inspiration among others. Passive ONA intelligence gathering played a pivotal role, with the company analyzing teams’ digital footprints within Microsoft 365. This included an aggregate-level analysis of email, calendar, and Microsoft Teams metadata, ensuring privacy by avoiding the exploration of employee content.
An integral part of the company’s strategy was the use of advanced AI technologies to automatically detect organizational silos and bottlenecks that hinder effective communication and workflow. By integrating AI with the ONA data, the system could identify areas where information flow was interrupted or inefficient, thereby allowing for targeted interventions. This AI capability extended to providing customized recommendations at the individual employee level, providing relevant stakeholders with tailored advice on how to improve the employees’ connectivity, collaboration, and overall productivity. This innovative use of AI not only enhanced the effectiveness of the ONA initiative but also reinforced the company’s commitment to leveraging cutting-edge technology to foster a more connected, efficient, and resilient organization.
Results
The implementation of AI-powered ONA by the company yielded significant results:
- 40% Reduction in New Hire Time-to-Productivity: Streamlining the onboarding process, thereby accelerating the contribution of new employees to the company’s goals.
- 20% Reduction in Unwanted Attrition: Retaining valuable talent through better understanding and addressing their needs and concerns.
- 70% Improvement in Strategic Change Adoption: Enhancing the company’s agility and responsiveness to changes in the market and internal processes.
Outcomes Beyond Numbers
The tangible results were complemented by strategic outcomes that further solidified the company’s internal cohesion and operational efficiency:
- Identification of High-Potential Employee Influencers and Change Management Leaders: Empowering those who could drive the company forward.
- Monitoring of Teams’ Productivity and Burnout Risk: Ensuring the well-being of the workforce while maintaining high levels of productivity.
- Actionable DE&I Insights: Providing executive stakeholders with valuable insights into collaboration dynamics across genders and age groups, enhancing the company’s commitment to diversity, equity, and inclusion.
- Enhanced Inclusion of New Hires from HBCUs: Strengthening the company’s talent pipeline and diversity through strategic hiring.
- Informed Employee Relocation Decisions: Making relocation decisions based on deep insights into team dynamics and individual contributions.
Conclusion
The Fortune 500 biotech company’s strategic use of AI-powered ONA illustrates the power of data-driven approaches in transforming internal operations and fostering a culture of efficiency, inclusion, and innovation. By leveraging the insights gained through AI-powered ONA, the company not only improved its business performance but also set a new standard for internal collaboration and strategic change adoption in the biotech industry. This case study serves as a compelling example for other organizations seeking to navigate the complexities of internal networks and drive meaningful change.
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