Tech Mahindra

Tech Mahindra, India's fifth-largest IT services company, entered fiscal year 2024 (April 2023 – March 2024) in acute financial distress. Revenue declined 5.0% to $6.277 billion from $6.607 billion in FY2023. EBITDA margin contracted sharply from 15.1% (FY2023) to 9.6% (FY2024) — a 550-basis-point collapse. PAT fell 51.2% from ₹4,832 crore (FY2023) to ₹2,358 crore (FY2024). The deterioration stemmed from multiple factors: an industry-wide demand slowdown, over-reliance on expensive third-party subcontractors, an over-lateral-heavy talent pyramid distorted by aggressive hiring in FY2022–FY2023, and poor employee utilization as headcount outpaced demand. Headcount peaked at 152,400 in FY2023 and fell to 145,455 by FY2024 (a reduction of ~6,945 employees). Mohit Joshi became CEO in November 2023 with a mandate to structurally restore margins without sacrificing competitive positioning.

In April 2024, Tech Mahindra unveiled its "Vision 2027" strategic roadmap and its accompanying operational turnaround initiative, "Project Fortius," targeting 15% EBIT margin by FY2027. Six specific operational levers were disclosed in investor communications:

1. Pyramid optimization: Increased fresher hiring to rebalance the talent pyramid toward lower-cost junior grades, reducing dependence on expensive lateral mid-career hires that had inflated delivery costs during the FY2022–FY2023 growth phase.
2. Subcontractor cost reduction: Actively reduced reliance on third-party subcontractors by replacing them with internal capacity. Management cited subcontractor reduction explicitly in Q4 FY2024 earnings as a direct driver of the sequential margin improvement observed in that quarter.
3. Offshore mix improvement: Increased the proportion of work delivered from offshore (lower-cost) locations relative to onshore, improving effective cost per unit of output.
4. Utilization improvement: Improved employee utilization; utilization excluding trainees reached 86% in Q4 FY2024 (disclosed in Q4 FY2024 earnings materials).
5. Delivery model centralization: Reorganized from a geography-based delivery model to a centralized delivery structure, reducing organizational overhead and improving resource allocation.
6. AI upskilling at scale: Trained more than 80,000 employees in AI and generative AI, with AI certifications made mandatory across delivery functions, improving delivery efficiency and positioning the company for AI-linked deal wins.