Trade-offs in Design: A Theory Building Qualitative Study on the Role of Problem Formulation and Framing in Resolving Trade-offs in Design

Design projects are complex problem-solving endeavors that can involve many goals that are often conflicting. These trade-offs between goals have been primarily studied through the lens of optimization, attempting to create the best possible solution under the constraints of the conflicting goals. However, the broader design literature indicates that design problems are characterized by being ill-defined. As a result, designers need to interpret, formulate, and frame the problem they are attempting to solve, and they must do this without a well-defined set of constraints and requirements. To this end, designers use solutions concepts to explore their problem, and this causes the design problem and solution to coevolve. This research explores the ways that designers formulate and frame trade-offs, how they can manipulate their formulation and framings of the problem to resolve trade-offs, and the aspects of their design situations that influence how challenging these reformulation and reframing processes are. A theoretical framework was derived using set theory to model and describe a designer’s formulation and framing of their problem and solution, which is labeled the design space. The framework also utilizes the concept of Pareto optimality to formally define design trade-offs within a design space. An intensionally defined set of possible manipulations to this design space was identified using this theoretical framework, which informs how those manipulations can be used to resolve trade-offs. This framework also models how a designer’s perceptions and expectations of their design spaces can differ from the real performance of their solutions due to inherent cognitive limitations, information availability, and biases. A semi-structured interview approach was used to explore how practicing designers framed and formulated their initial trade-off situation, and how they manipulated those aspects in their resolution of the trade-off, if at all. Additionally, an echo interview process was used to investigate what influences the designers perceived as affecting how challenging their trade-off situations were to resolve. Seven different approaches to resolving trade-offs were identified in the dataset through a case study analysis, which were classified by how they manipulated the design space. Four of these approaches actively manipulated the designer’s perceived design space to resolve the trade-off, two altering the boundaries of the space and two altering the parameters that comprised the space. These manipulations allowed the designers to restructure their design space and the trade-offs therein to make them easier to resolve. In some of the cases studied, the manipulations also allowed the derivation of solutions that dominated the Pareto frontier of the original design space. In addition to the case study analysis, a thematic analysis was used to identify the aspects of the situation that made manipulating design spaces and resolving trade-offs either easier or more challenging. From this nine codes were identified, sorted into three themes. The three themes were how the design space was initially structured, how well a designer’s expectations aligned with the real outcomes of decisions, and how previous decisions impacted the options available to a designer. The results showed that designers can and do manipulate their problem formulation and framing to resolve trade-offs. This indicates that optimization approaches in design need to account for the dynamic structure of the problem, and that designers should be aware that results of an optimization approach reflect the structure they impose on their design problems. Overall, this research contributes to understanding how designers perceive and frame trade-offs, what tools they have at their disposal to resolve them, and what challenges they encounter while resolving them