Iconstorm Unveils 'R3ASON': Revolutionizing Design Research with AI Automation

30.11.2023 / Felix Guder We unveil the transformative power of AI in our work processes, the creation of 'R3ASON,' and our innovative approaches to overcome challenges in design research.

As a strategic design agency, Iconstorm continually evaluates its own work processes. We analyze processes and methods from our portfolio for their effectiveness, focusing primarily on customer benefits. This involves assessing the extent to which our processes can help us and our clients achieve their goals. Additionally, we consider opportunities for optimization and digitalization, recognizing that our portfolio always has room for improvement in enhancing customer value, systematically mitigating risks in development, and boosting performance in product development.

Design Research: The Untapped Goldmine in Early Phase Product Development

In early 2023, our focus was on Design Research, a field that involves developing and processing specifications with an emphasis on integrating user requirements. We understand that meaningful innovations and products result from the combination of economic, technological, and human requirements. Although design research yields reliable and crucial information about users and their context, incorporating this information into the product development decision-making process is challenging. Consequently, many of our clients are reluctant to embark on comprehensive design research projects in the early phase of their projects.

Due to the complexity and time-intensiveness of user research, clients often avoid it in the early planning stages. They prefer to risk inaccuracies in their own assessment of customer needs and context over conducting extensive user research in the preliminary stages of projects.

Time vs. Insight: The Struggle to Balance User Research in Agile Development

Our agency has witnessed numerous projects where costly changes were needed later in the development process due to improper prioritization. User research was often only acknowledged after significant problems had emerged in the project. There are four main reasons why user research is often favored despite potential risks:

  • Costly: User research is resource-intensive. Recruiting test subjects can be complex, and documentation is extensive. These factors contribute to high costs even in the initial phase of a project, making user research challenging to implement.

  • Qualitative Results: Small groups of test subjects typically yield qualitative findings rather than statistically validated results. Unfortunately, this limitation is inherent in current methods.

  • Opaque Analysis Process: While information collected is meticulously documented, its origin becomes obscure in subsequent steps. For instance, a well-organized Excel list may document requirements, but the connection to this list in the prototype that incorporates these requirements is often not evident and hard to validate. This issue also affects the traceability of user requirements. To manage complexity, data is often abstracted, losing its connection to the actual context.

  • Time-Consuming: Planning and executing user research requires careful recruiting, especially challenging in the B2B sector. Issues like data protection, confidentiality, and logistical complications add to the difficulty. Analyzing video and audio recordings is also labor-intensive. Thus, integrating user research into agile sprint systems is a complex task.

Enhancing Repeatability and Traceability: Iconstorm's New Approach to User Research

We then examined this process using our tools from the customer's perspective, which helped us understand these challenges.

It became evident that although our user research and requirements management portfolio were robust, investment was necessary. When a critical step in product development is challenging to implement and faces significant resistance, the issue lies in execution, not the concept.

After thorough analyses, we explored various aspects of user research at Iconstorm.

Technical and commercial requirements engineering were already well-integrated into Iconstorm's playbook. Our process of mapping, exploration, gathering insights, and formulating requirements was established and proven in practice. Recognizing the need for further investment in user research and requirements management, we focused on optimizing our playbook and enhancing user research methods to ensure repeatability and traceability. We also investigated how digital tools could reduce routine research tasks.

Our efforts in refining the playbook and methodological enhancements led to substantial progress, alleviating client hesitations. Innovations such as the Visioneering Sprint, which integrates requirements management and user research within a set timeframe, were developed. We also refined methods for better integration into workflows, like our optimized version of the Jobs-to-be-Done framework.

Iconstorm Unveils 'R3ASON': Revolutionizing Design Research with AI Automation

Furthermore, we explored automating or partially automating the process, uncovering the disruptive potential of new AI technologies. This led to a completely new working methodology. Various data types generated during user research, including transcriptions of interviews and videos, are now AI-supported. Adopting modern data analytics tools and transactional database engines that store data in graphs instead of tables was a breakthrough, fundamentally altering the entire process.

This innovation revolutionized Iconstorm's approach to design research and requirements management in product development. Various AI and ML frameworks have simplified and automated data handling, from collection to delivery. New interfaces for data analysis tools have made it easier to analyze information for both our researchers and clients.

The full potential of this shift to a fully digital request process is yet to be realized, but the use of AI continually opens new possibilities. Our system, "R3ASON," exists as a working prototype, ready for new tasks and further exploration of balancing human intervention and data processing through data science tools