Identifying & Modelling Design Effort Influencing Factors in Product Design Company Projects

Research output: ThesisDoctoral Thesis


Product design is an uncertain, complex activity that is difficult to predict, being influenced by many factors. Understanding how these factors behave can provide great insight and value to practicing designers when planning their projects. A review of the approaches that identify these factors, specifically those influencing project resources show found that these methods tend to either have a specific use case or require the sophisticated analysis of large data sets. Valuable in their own context and emphasising the need to understand these factors, but are of little use to product design companies, who rely on expert judgement to estimate project resources. The capture of that expert judgement may offer a means of understanding these factors for product design companies.
This research presents the methods, analysis and findings of an evolutionary multiple round case-based approach, working with three UK-based product design companies (PDCs) to answer the following research questions:
RQ1: What factors are considered to have the greatest influence over product design company project resources and how do those considered by product design company teams differ from those in the literature?
RQ2: How do factors influence the resource demands of product design company projects and how does that influence changes throughout a project?
RQ3: How might PDC teams enhance their understanding of the project planning process and of their own teams through the collaborative capture and modelling of their own understanding?
Answering these research questions resulted in four contributions.
1. The identification and modelling of which factors have the greatest influence on design effort demands of PDC projects, based on the PDC team’s tacit knowledge and experience.
Five factors with the greatest influence on design effort needs of PDC projects were identified: “Brief Clarity”, “Designer’s Experience”, “Designer’s Intuition of the Client”, “Delivery Output Complexity” and “Product Complexity”. Sets of graphical models were produced depicting the behaviour of each factor.
2. The identification and synthesis of various dimensions of product complexity
As “Product Complexity” was the most significant factor identified in the cases, the accompanying collected data has been used to synthesise a range of dimensions and units of measure for the factor. These dimensions are: the number of parts a product is anticipated to have and whether they need to be custom designed; the intended functionality of the product, including its degrees of freedom, and the technologies required to enable those freedoms and functionalities; and the creativity required of the design team to design the project.
3. The identification of “budget” as a novel category for design effort influencing factors and the synthesis of a novel set of categories to apply to design effort influencing factors in design projects derived from literature
Through the analysis of design effort influencing factors found in literature, several categories were synthesised. Through the findings of the cross-case analysis, an additional, novel category of “budget” was identified, resulting in the following nine categories: Team Management, Product, Business Management, Information, Tools & Technology, Client, Project, External Influences and Budget
4. The development of the CoFIDE method, a novel, tacit knowledge capturing, influential factor identification and modelling method for design effort level influencing factors in PDC projects.
To address RQ3, a method was developed to identify and model the behaviour of the most influential factors of design effort demands of design projects. Based on the case-based research approach, CoFIDE is a method which models the behaviour of the most influential factors per phase of a design project, utilising two graphical methods to produce the models. The Mean Effect Plots (MEP) of each design team member for a given factor overlaid in a simple line graph provide a clean means of identifying the behavior of a factor, and how its average influence changes from being at its perceived lowest state to its perceived highest. The Percentage Influence Graphs (PIG) provide a direct means of identifying which factors exert the greatest influence over design effort requirements. By representing percentage influence in linear bars, direct comparisons between designers and their perceptions of factors can be made quickly. In combination, these models enable design teams to identify which factors have the greatest influence and how that influence behaves based on the magnitude of their presence. This provides design teams with potential opportunities to take action to reduce negative impacts, and increase positive impacts, on projects.
The novel research presented in this thesis and its outputs has the potential to save the SME-intensive design industry time and resources by offering insight into their design space and the factors that influence it.
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
  • Thomson, Avril, Supervisor
  • Hird, Abigail, Supervisor
Award date21 Jun 2024
Place of PublicationGlasgow
Publication statusAccepted/In press - 21 Jun 2024


  • design management
  • product design
  • design projects
  • project planning


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