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A Process characterization is a regulatory imperative for process validation within the biopharmaceutical industry. Several individual steps must be conducted to achieve the final control strategy. For that purpose, tools from the Quality by Design (QbD) toolbox are often considered. These tools require process knowledge to conduct the associated data analysis. They include cause and effect analysis, multivariate data analysis, risk assessment and design space evaluation. However, this approach is limited to the evaluation of single unit operations. This is risky as the interactions of the operations may render the control strategy invalid. Hence, a holistic process evaluation is required. Here, we present a novel workflow that shows how simple data analysis tools can be used to investigate the process holistically. This results in a significant reduction of the experimental effort and in the development of an integrated process control strategy. This novel QbD workflow is based on a novel combination of risk assessment and integrated process modeling. We demonstrate this workflow in a case study and show that the herein presented approach can be applied to any biopharmaceutical process. We demonstrate a workflow that can reduce the number of factors and increase the amount of responses within a Design of Experiments (DoE). Consequently, this result demonstrates that experimental costs and time can be reduced by investing more time in thoughtful data analysis.