Most research work and refinery decision makers mainly focus on direct planning results such as the optimal combination of raw materials, unit loads, and production rates. There exists much more useful hidden information from an LP model such as marginal values of the feed stocks, the intermediate products, and the final products than direct planning results. One of the limitations of using marginal values is that they are only applied for stream flows at the solution point. We have no idea how these marginal values are changed beyond the solution. To tackle this problem, two analytical methods, namely sensitivity analysis ( SA) and parametric programming ( PP), are proposed and applied in MVA ( marginal value analysis). With these two analysis methods, MVA can be extended beyond the solution point and applied to process constraints. This article first uses a simple gasoline blending example to illustrate the required modeling techniques and procedures for performing these analyses. Then a multi-period refinery case study is presented to show how to interpret the results and apply the analyses to a real world refinery. The approach proposed here can be of great help for debottlenecking, retrofitting, pricing, and investment evaluation. The analytical methods proposed can also be generally applied to other chemical plants.