Data-Driven Personas and Scenarios Enhance Future Urban Mobility Design

Why It Matters

This approach bridges the gap between design practice and complex future uncertainties, enabling the creation of more resilient and inclusive urban mobility solutions. By grounding design decisions in data-informed user archetypes and plausible future conditions, practitioners can mitigate risks associated with unforeseen technological, demographic, or environmental shifts.

Key Finding

The research demonstrates a method to create user profiles (personas) that are informed by data and adaptable to various future possibilities, facilitating better design of urban mobility systems.

Key Findings

• Data-driven proto-personas can be created and validated.
• Proto-personas can be transformed to reflect different future scenarios.
• Full personas and synthetic populations serve as effective intermediary design objects for interdisciplinary collaboration.

Research Evidence

Aim: How can diverse future user needs be integrated into the design processes for urban mobility systems, considering future uncertainties?

Method: Scenario-based design and data-driven persona development

Procedure: The methodology involves creating data-driven proto-personas with assigned characteristics and behaviours, testing their validity, deriving geographical distributions, and transforming them for different future scenarios. These are then used to develop full personas and synthetic populations as intermediary design objects for collaboration between designers and simulation experts.

Context: Urban mobility systems design

Design Principle

Design for adaptability by integrating future uncertainties and diverse user needs through data-informed scenario planning and persona development.

How to Apply

When designing new urban mobility services or infrastructure, develop proto-personas based on available demographic and behavioural data, then project these personas into 2-3 distinct future scenarios to test the robustness of your design concepts.

Limitations

The effectiveness of the method is dependent on the quality and availability of input data for persona creation and scenario definition. The transferability to vastly different urban contexts may require adaptation.

Student Guide (IB Design Technology)

Simple Explanation: To design better future transport systems, we can create 'pretend people' (personas) based on real data and imagine different futures (scenarios) to make sure our designs work for everyone, no matter what happens.

Why This Matters: This research shows how to make your design projects more relevant to the future by considering how people might use your product or system in different, uncertain conditions.

Critical Thinking: How might the biases present in the data used to create personas inadvertently lead to the exclusion of certain user groups in future mobility designs?

IA-Ready Paragraph: This design project addresses the challenge of designing for future uncertainty by employing a data-driven persona and scenario-based approach, inspired by Gall et al. (2023). By developing proto-personas grounded in existing data and projecting them into plausible future scenarios, the project aims to ensure that the proposed solutions are robust, inclusive, and adaptable to evolving user needs and environmental conditions.

Project Tips

• When defining your target users, go beyond simple demographics and consider behaviours and potential future adaptations.
• Use publicly available data sets (e.g., census data, transportation surveys) to inform your persona development.

How to Use in IA

• Reference this study when discussing your user research methodology, particularly if you are using personas or considering future trends.
• Use the concept of scenario planning to justify the exploration of multiple design solutions or features.

Examiner Tips

• Demonstrate an understanding of how future uncertainties can impact user needs and product viability.
• Show how your chosen user research methods allow for flexibility and adaptation to evolving contexts.

Independent Variable: Integration of future trends and uncertainties; Data-driven personas and scenarios

Dependent Variable: Ability to design future urban mobility systems; Consideration of diverse user needs

Controlled Variables: Urban mobility context; Design process methods

Strengths

• Provides a structured method for integrating uncertainty into design.
• Facilitates interdisciplinary collaboration through shared design objects (personas, synthetic populations).

Critical Questions

• What are the ethical considerations when creating synthetic populations for design purposes?
• How can the validity and reliability of data-driven personas be rigorously assessed?

Extended Essay Application

• An Extended Essay could explore the development and validation of specific data-driven personas for a novel mobility service, testing their utility across multiple future scenarios.
• Another avenue could be a comparative study of different methods for integrating uncertainty into design, evaluating the effectiveness of persona-based approaches.

Source

Integrating future trends and uncertainties in urban mobility design via data-driven personas and scenarios · European Transport Research Review · 2023 · 10.1186/s12544-023-00622-0