Cancer policymakers, researchers, and advocates have different priorities for cancer treatment research and may define ‘value’ of new treatments differently. Harmonizing the priorities and values of diverse stakeholders may be neither possible nor desirable. In November 2012, as part of its Patient Access to Cancer care Excellence (PACE) initiative, Lilly Oncology convened a Global Council of opinion leaders in cancer research, care, and policy to identify barriers to innovation in oncology research and develop strategies to improve cancer care. Participants concluded that the cancer policy field lacked tools to visualize these differences and to track progress in cancer treatments based on variable sets of values. Responding to this need, PACE developed the Continuous Innovation Indicators: novel, scientifically rigorous progress trackers designed to increase understanding of continuous innovation in cancer treatments among different stakeholders. The Indicators quantify progress in cancer treatments by: 1) mining the literature to determine the strength of the evidence supporting each treatment; 2) weighting the analysis according to the audience’s priorities and values; and 3) calculating Evidence Scores (E-Scores), which are measures of progress based on the strength of the evidence weighted by the assigned value. We introduce a flexible model to illustrate differing values, show how the values from the model can be used to weight the evidence from the scientific literature to obtain E-Scores, and demonstrate how assigning different values influences E-Scores. Differentiated analyses based on values provided by various stakeholders will help the cancer policy field to obtain accurate representations of the complex, stepwise progress against different cancers over time. We envision partnerships and collaborations to support educational efforts, identification and illustration of policy goals, and work in the field of health technology assessments. We will not make this tool available to individuals or organizations for the purpose of deriving treatment recommendations.