This research presents a quantifiable value modeling approach for tracking and optimizing value addition at different stages of the product development process (PDP) and supply chain management (SCM). While there is a vast abundance of papers in the literature harping on the need to maximize the value, especially in lean thinking context, in PDP and SCM, there is a dearth of propositions on how to quantitatively measure and optimize value at each stage of product development and supply chain. This paper presents a multi-dimensional value modeling approach that incorporates parameters and variables from different stages of PDP and SCM by mathematically mapping them on to two macroscopic metrics, namely Product Information Evolution and Risk Reduction. These two metrics are in turn modeled by incorporating value attribute variables such as performance, risk, schedule, cost, form, fit, function and timeliness from different stages of PDP-SCM such as customer needs ideation, product functions, inventory management, logistics management and product delivery. The efficacy of the proposed model was tested by utilizing it to measure value additions at different stages of PDP-SCM as well as the total value addition for an ordinance disposal (OD) robot product family, once developed and supplied using traditional production method and once using lean production method, with the underlying axiom being the lean method will result in higher value. To ensure a fair and accurate comparison, both production methods used the proposed mathematical value model and worked toward maximizing total value using nonlinear programming. The results showed that lean PDP-SCM method added higher value at each of the stages as well as total value when compared to the traditional PDP-SCM method thus establishing the proposed value model as a viable mathematical way to measure value. While the proposed value model passed test of efficacy against the lean axiom, further research is needed to test it against other established axioms to establish it as a robust mathematical way to measure value in PDP-SCM.