What's taking so long? A collaborative method of collecting designers' insight into what factors increase design effort levels in projects

Holliman, Alexander (Freddie) and Thomson, Avril and Hird, Abigail and Wilson, Nicola (2020) What's taking so long? A collaborative method of collecting designers' insight into what factors increase design effort levels in projects. AI EDAM - Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 34 (3). pp. 341-362. ISSN 0890-0604 (https://doi.org/10.1017/S0890060420000359)

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Abstract

Design effort is a key resource for product design projects. Environments where design effort is scarce, and therefore valuable, include hackathons and other time-limited design challenges. Predicting design effort needs is key to successful project planning; therefore, understanding design effort-influencing factors (objective considerations that are universally accepted to exert influence on a subject, that is, types of phenomena, constraints, characteristics, or stimulus) will aid in planning success, offering an improved organizational understanding of product design, characterizing the design space and providing a perspective to assess project briefs from the outset. This paper presents the Collaborative Factor Identification for Design Effort (CoFIDE) Method based on Hird's (2012) method for developing resource forecasting tools for new product development teams. CoFIDE enables the collection of novel data of, and insight into, the collaborative understanding and perceptions of the most influential factors of design effort levels in design projects and how their behavior changes over the course of design projects. CoFIDE also enables design teams, hackathon teams, and makerspace collaborators to characterize their creative spaces, to quickly enable mutual understanding, without the need for complex software and large bodies of past project data. This insight offers design teams, hackathon teams, and makerspace collaborators opportunities to capitalize on positive influences while minimizing negative influences. This paper demonstrates the use of CoFIDE through a case study with a UK-based product design agency, which enabled the design team to identify and model the behavior of four influential factors.