.svg){kind=icon}
Data for AI-Driven Talent Insights
Problem Statement
Talent is the most scarce and critical resource for most organizations, driving growth, innovation, and competitiveness. However, while every organization collects people data through HR processes, individual datasets are often too limited to generate meaningful insights for advanced analytics or to train sophisticated AI models. This lack of data volume and diversity limits the potential for benchmarking, predictive analytics, and the development of AI solutions that could vastly improve talent management and employee outcomes.
Solution Description
Through People Data Collaboration between HR departments across organizations, a new frontier of people analytics can be unlocked. By securely sharing data across organizations, highly segmented benchmarks can be created, allowing companies to gain insights into their talent management relative to industry standards. This collaboration also enables the training of AI models and algorithms focused on nine critical HR domains, including recruitment, performance management, diversity and inclusion, and employee engagement. The solution leverages federated learning to ensure that data remains secure and privacy-compliant, while still facilitating advanced analytics.
Ocean Enterprise Features Used
- Compute-to-Data
- Enterprise Compliance Features
Details and Description
The goal is to enable HR departments to share people data securely and privately through federated learning. This approach ensures data never leaves the organization, but its value can still be harnessed through decentralized AI model training. By comparing data across industries and segments, organizations can develop better insights into recruitment patterns, employee retention strategies, and workforce diversity. This cross-organizational collaboration aims to foster stronger talent management strategies and more informed decision-making at every stage of the employee lifecycle.
Value Creation
The primary value comes from the jointly created data products, such as benchmarking reports and predictive models, which are made available to contributors of the collaboration. These insights will help companies optimize their HR processes, predict talent shortages, and identify best practices across industries. While the collaboration is primarily focused on data sharing and AI model training, there is also the potential for monetization by selling these insights or data products to other organizations. However, monetization remains optional, with the emphasis placed on the shared value and mutual benefit of participating organizations.
Contributors
This case study is being actively worked on by Rocketstar and FELT Labs, founding members of the Ocean Enterprise Collective. Learn more and get in touch with Rocketstar here and with FELT Labs here
