Case Study: Evaluating the Effectiveness of Telecommunication Company Talent Scouting Program
- Farvis Indonesia
- Jul 25
- 2 min read
1. Background
One of Indonesia’s leading telecommunication company is undergoing rapid transformation into a digital lifestyle enabler. To stay competitive, the company launched the “Digital Future Talent Scouting Program” to attract, assess, and onboard top young talents in areas such as AI, cloud computing, cybersecurity, digital marketing, and product innovation.
Now in its third year, the People & Culture team initiated a formal program effectiveness evaluation to ensure Return On Investment (ROI), strategic alignment, and long-term talent sustainability.
2. Objectives of the Evaluation
· Assess the quality and impact of talent hired through scouting efforts.
· Determine which sources and channels yield the highest potential.
· Identify gaps in readiness, diversity, and post-hire performance.
· Provide date-driven recommendations to improve future scouting cycles.
3. Key Evaluation Metrics (Dummy Data)
Dimension | Key Metric | Target | Actual | Insights |
Strategic Talent Match | % of hires in digital growth areas | 75% | 58% | Misalignment in university outreach; high in sales, low in digital roles |
Talent Quality | Average manager rating after 6 months (scale 1–5) | 4.0 | 3.5 | Talent lacks real-world readiness in AI/Cloud roles |
Source Effectiveness | Conversion from competition (e.g., Hackathons | 25% | 40% | Hackathons yield high-performing talent |
Cost per successful hire (IDR) | 12M | 15M | Slightly over budget due to external assessment tools | |
Diversity & Reach | % of hires from outside Java | 30% | 12% | Limited presence in Eastern Indonesia and smaller universities |
Candidate Experience | Candidate NPS | 70 | 82 | Great brand reputation and engagement experience |
Post-Hire Success | 1-year retention of scouted talent | 90% | 78% | Need for stronger onboarding and early career mentoring |
Internal promotion within2 years | 15% | 5% | Still early, but needs tracking mechanism |
4. Visual Dashboard Snapshot (Mock Example)
Talent Source Effectiveness – By Channel
Source | Conversion Rate | Avg. Manager Rating | Cost/Hire (IDR) |
Hackathon | 40% | 4.2 | 10M |
Campus Job Fair | 18% | 3.4 | 14M |
12% | 3.5 | 13M | |
Digital Academy Partnership | 22% | 3.6 | 12.5M |
5. Key Findings
1. High engagement and brand recognition, especially in Java and top universities.
2. Talent from competitions performed better than traditional recruitment sources.
3. Digital skills readiness gap exists, particularly in AI and cloud roles
4. Diversity targets underachieved, especially in representation from Eastern Indonesia
5. Retention and promotion metrics suggest the need for stronger early career pathways.
6. Recommendations to Improve Effectiveness
1. Recalibrate Talent Scouting Channels:
Increase focus on technical competitions, tech bootcamps, and industry-linked academies.
Strengthen campus partnerships with regional universities and vocational institutions outside Java.
2. Embed Real-World Readiness Assessments
Integrate problem-solving simulations, hackathons, and digital skill testing into early screening.
3. Implement Talent Analytics System
Create a real-time dashboard that tracks scouted talent journey: source --> performance --> promotion/retention.
4. Strengthen Onboarding & Mentoring
Launch a Digital Talent Buddy Program with early career coaching and structured development pathways.
5. Set Annual Strategic Alignment Goals
Co-create scouting needs with Digital Product & IT leadership to align with business transformation goals.
7. Conclusion
The talent scouting program has strong foundations in candidate experience and innovation, but needs sharper alignment with the company’s digital priorities and diversity aspirations. With better analytics, deeper outreach, and structured talent acceleration, the company can build a sustainable pipeline of future-ready digital leaders.
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