The development of complex products is frequently supported by decision-making applications (models and tools) that do not always deliver the right answers. In part, this can be explained by the GIGO principle, which states that if the inputs are flawed, the resulting outputs will be unsound. There are various reasons for faulty inputs, and this work narrows its perspective to focus on those caused by judgment and cognitive biases. The hypothesis herein is that biased observations lead to biased models, and these models produce biased outputs. These outputs may misinform the designer (decision-maker), ultimately resulting in poor designs (by poor decisions). That is, biases lead to poor designs.

Aiming to improve judgment in decision-making along the design process, the author postulates the following research question: How might this article apply bias mitigation strategies effectively, to make decision-making applications more resilient to cognitive biases?

To address this question, this article reviews a wide spectrum of design processes and the decisions along those processes. Then, it broadens the general outlook and examines well-studied cognitive biases and their mitigating strategies. To conclude, this article presents metacognitive strategies and tools for decision-makers. The novelty of this work is not in its findings in psychology or behavioral economy: these concepts are borrowed from well-established and documented sources. Thus, the novelty of this article lies in the approach proposed to pragmatically apply allaying strategies for use in the design process.