Talent CRM

This project aims to build a comprehensive Talent Customer Relationship Management (CRM) system, a business intelligence tool designed for organizations to track and optimize talent progression through data-driven insights. The system will synthesize user profiles, market data, and engagement metrics from our AI coach, recruiter, and mentor agents to deliver actionable insights for career development optimization.

The Talent CRM addresses a critical gap in how career centers and companies manage talent development. Currently, organizations struggle with fragmented data across multiple systems, resulting in missed opportunities for timely interventions and support. Our solution will provide unified dashboards displaying individual and cohort progression, enabling data-driven decision-making for career services professionals.

The project will be executed across three semesters with a Master of Management Analytics student:
Phase 1 (Semester 1): Foundation and data architecture development. Focus on establishing the analytics infrastructure, integrating data sources from AI agents, and building core talent tracking capabilities with basic cohort management and reporting dashboards.

Phase 2 (Semester 2): Advanced analytics and automation implementation. Development of machine learning models for journey detection/generation, predictive analytics for student success factors, and automated intervention recommendations. This phase emphasizes sophisticated analytical models for talent trajectory prediction.

Phase 3 (Semester 3): Integration and optimization. Seamless integration with existing DotsCareer enterprise solutions, performance optimization, and development of executive-level analytics features including weekly summaries and risk alerts.

Key technical components include real-time data processing, advanced visualization tools, and privacy-compliant data handling frameworks for educational settings.

Expected outcomes include full integration with our enterprise solutions, enabling enhanced insights and value delivery to current customers. This integration will provide comprehensive analytics capabilities, validated predictive models for career outcomes, and actionable intelligence empowering organizations to make data-driven decisions for improved talent development and retention.

Faculty Supervisor:

Fredrik Odegaard;Mustafa Tongarlak

Student:

Partner:

DotsLive

Discipline:

Business

Sector:

Information and cultural industries

University:

The University of Western Ontario

Program: