International Journal on Science and Technology

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Risk Quantification Models for Enterprise Hardware Launches

Author(s) Amit Jha
Country United States
Abstract Enterprise hardware launches involve tightly coupled risks across design readiness, supplier performance, manufacturing yield, logistics, regulatory compliance, and market timing. These risks evolve dynamically across launch phases and often propagate across functional boundaries, limiting the effectiveness of traditional qualitative risk registers. This paper presents a quantitative risk modeling framework specifically designed for enterprise hardware launches. The framework combines probabilistic risk estimation, Bayesian dependency modeling, and expected loss analysis to quantify launch readiness across pre-launch, ramp, and general availability phases. Risk likelihood and impact are derived from empirical program data, supplier metrics, validation coverage, and schedule buffers. A composite launch risk index is calculated to support objective go or no-go decisions and mitigation prioritization. A representative enterprise hardware launch case study demonstrates improved early risk visibility, stronger executive decision support, and reduced late-stage disruptions compared to qualitative methods. The results show that quantitative risk aggregation enables more accurate forecasting and proactive intervention in complex hardware programs.
Keywords Enterprise hardware launch, Risk quantification, Bayesian risk modeling, Probabilistic risk assessment, Expected loss analysis, Product lifecycle risk, Program and portfolio management.
Field Engineering
Published In Volume 17, Issue 1, January-March 2026
Published On 2026-01-22
DOI https://doi.org/10.71097/IJSAT.v17.i1.10199
Short DOI https://doi.org/hbm8bh
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