Digitally enhanced consumer packaged goods: a data-inspired ideation approach

Berumen Salazar, Jose Gustavo (2022) Digitally enhanced consumer packaged goods: a data-inspired ideation approach. PhD thesis, University of Nottingham.

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Abstract

Consumer packaged goods (CPG) are disposable, relatively low-price, frequently-purchased products such as a bottle of milk or a bar of chocolate. CPGs have a pervasive presence in our everyday practices, and a number of instances have shown the potential of integrating their existing functionalities into the Internet of Things (IoT). Such innovations as, for example, a pill container which reminds one when to take their medication, or a disposable toothbrush which teaches children about oral hygiene, illustrate the capacity of digitally enhanced CPGs to have a positive impact in countless aspects of our lives. However, despite recent research in human-computer interaction (HCI) aimed specifically at enhancing interactions with CPGs, devising enhanced versions of these goods which meet people's needs and reflect their values remains quite elusive. Many challenges in the design of enhanced CPGs stem from their defining characteristics, including their disposability and frequent need to be replenished, as well as from the fact that they are rarely used in isolation, but rather in conjunction with one another as sets.

While it has been demonstrated that providing data about item usage during the design process represents a substantially powerful approach for creating effective products, this has not yet been applied in the creation of enhanced CPGs, as we currently lack even a rudimentary understanding of their use. This thesis represents the body of knowledge gathered through the completion of two fieldwork studies focused on how CPGs are used in the practice of cooking. Furthermore, it utilises an understanding of CPG interactions and, through two participatory design workshops, explores how such insights can inspire the conceptualisation of enhanced CPGs.

The fieldwork study of this thesis focused on the interactions of CPGs in cooking, which was chosen due to it being one of the most prevalent everyday practices involving CPGs. We examined cooking in two situational contexts: the preparation of familiar meals (those which could be prepared from memory) and that of unfamiliar meals (those which people had never cooked before). The first analysis was concerned with only the preparation of the unfamiliar meals, while in the second analysis we conducted a comparative analysis between familiar and unfamiliar meals. We employed a mixed-methods approach for blending quantitative and qualitative analysis methods. Overall, these studies revealed different characteristics of CPG interactions, including aspects of information-gathering, frequency of task saturation, and the sets of CPGs and utensils which appear together often. One example of our findings was that meal preparation was generally similar regardless of familiarity, as revealed by the repeated use of a select few CPGs across many meals and the consistency of their number of interactions. We then discussed the implications these findings have for the design of digitally-enhanced CPGs with the overall goal of promoting enhancements which fit our routines and habits rather than require us to adapt our practices to the IoT.

Inspired by frameworks which have placed data at the centre of the design process, the participatory designs employed in this thesis, made use of the data gathered from the above mentioned fieldwork studies as a tool for participants to inspire the design of enhanced CPGs. We devised a structured workshop to study how participants drew upon the data, as well as how they perceive the influence this approach had on their ideation process. To facilitate their use of the data, we devised an array of design resources including data visualisations and design cards. We explored our approach in two studies: one which consisted of participants from the general public, and the other which consisted of professional designers. Analysing the role of data as expressed through participants’ comments and designs, we found that data served as a basis for the creation of unique concepts imbued with a sense of empathy and a greater consideration for the experiences and interests of others. Furthermore, we found that participants considered possible negative ramifications of the use of data for design, including ethical and privacy issues which may stem from such data collection, as well as a potential bias towards focusing on aspects highlighted by the data.

This thesis makes a number of contributions in showing that a detailed understanding of CPG interactions in practice can lead to insights which inspire the design of technologically-enhanced CPGs. It also presents analysis methods to further study the use of CPGs in practice, as well as an approach which enables people with no relevant formal training to utilise data effectively. In addition, this work provides implications for designing enhanced versions of CPGs which fit their practical contexts of use. For an accurate view of this research and its contributions, its limitations must be acknowledged, such as the relatively small size of our data sample and our bias towards the use of technologies to provide product enhancements. Nevertheless, our work highlights the need for an understanding of the practical use of objects to better design technological innovations which fit well into their real-world interactions, and serves to emphasise the need to continue research on CPG innovations. This work represents merely the first steps towards CPGs which are designed using a solid foundation of an empirical working knowledge of the practices in which CPGs play a role.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Fischer, Joel E
Baumers, Martin
Keywords: Consumer packaged goods, CPG, Internet of Things, IoT
Subjects: Q Science > QA Mathematics > QA 75 Electronic computers. Computer science
Faculties/Schools: UK Campuses > Faculty of Science > School of Computer Science
Item ID: 69815
Depositing User: Berumen Salazar, Jose Gustavo
Date Deposited: 31 Dec 2022 04:40
Last Modified: 31 Dec 2022 04:40
URI: https://eprints.nottingham.ac.uk/id/eprint/69815

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