Software Defined Vehicles (SDV), Software Defined Networks, Software Defined (electricity) Grids are just a few examples of how the Software Defined Transformation is unfolding across many industries today. This paper defines a maturity model for Software Defined Transformation and evaluates different industries including Automotive. This cross-industry view of Software Defined X (SDx) helps in analyzing where SDV's could be headed. Koster et all [2023] by BCG mentions 'The industries' SDV transformation is overshadowed by complexity', with players pursuing several directions in this transformation. While companies like Tesla are already making software centric cars, traditional OEMs like Stellantis, Toyota, Ford etc. are making huge investments and redefining their own business models, tech stacks and operations to leverage the power of software. There is an opportunity to introduce an overarching framework to bring clarity on this front by comparing SDx across industries. We propose a three-step "Define-Evaluate-Forecast" Framework We "Define" a multi-dimensional SDx Maturity Model around three strategic areas: Technical, Operational and Business. Technical areas include State of the Architecture, Reusable Innovation Enablers and level of Autonomy between Hardware and Software. Operational parameters considered are Organization Alignment for Software, Availability/Adoption of Regulations & Standards, and Contribution towards safety & sustainability. "Business" aspects include Customer Experience, Ecosystem value proposition and Return on Investment. We "Evaluate" similar traditional industries like Telecom, Power Grid etc. and score them per the SDx maturity levels, accounting for their differences in complexity. We "Forecast" the course for Software Defined Vehicle over the next 3 to 5 years, based on the understanding of the journey and the best-practices/lessons-learnt from the more mature industries. In conclusion, this paper studies the evolving software defined transformation across several industries and provides a "Define-Evaluate-Forecast" framework to compare them and prognosticate the future of SDV, leveraging the advancements and learnings from other industries.