Retaining Tacit Knowledge in High-Turnover Indian Automotive Embedded Engineering Companies: An Integrated Theoretical and Practical Framework

Abstract

Tacit knowledge comprising experiential problem-solving, nuanced technical judgment, and client-specific adaptation—forms the backbone of India’s automotive embedded engineering sector, enabling compliance with rigorous standards such as ISO 26262, AUTOSAR, and ASPICE. Yet, this non-codified expertise is increasingly at risk in an environment marked by high turnover due to competitive talent poaching, contract-based staffing, and short job tenures. This study develops an integrated retention framework combining Nonaka et al.’s SECI model, Tan et al.’s live capture methodology, and Mohamed & Nordin’s lean tacit transfer strategies with behavioral and generational insights from Gaghman (2019) and Tokarz &Rosinski (2024). A mixed-methods survey of 91 managers and team leads from Chennai, Coimbatore, Bangalore, Hyderabad, and Cochin managing teams of 2–50 members with 3–20 years of experience revealed weak retention systems, unclear competency mapping, high perceived turnover risk, and moderate organizational support. The findings underscore the need for a multi-layered approach that integrates SECI-based workflows, generativity-driven mentoring, trust-based behavioral enablers, and lean-frugal skill transfer platforms, institutionalized within HR policy and operational routines. The proposed framework offers a scalable, context-specific strategy for sustaining tacit knowledge, strengthening organizational resilience, and safeguarding innovation capacity in high-attrition engineering environments.