Betolar’s next-generation building material, Geoprime®, enables concrete production without pollutive cement by transforming industrial side streams into a sustainable business.
My team was tasked to build a researcher-friendly analytics tool that utilises data to increase efficiency in the R&D process and help realise its full potential.
My responsibility
Product vision & roadmap, user research, prototyping, and UI design.
I worked closely with the product manager and engineers.
Duration
12 months
The challenge
The client needs to scale up the material research process to meet both business objectives and market demands. However, the current process is often long and heavily manual. To tackle this problem, the management recognised the need for leveraging technology and data to reach a higher degree of assistance and automation. The goal is to harness data and technology to maximize the efficiency and automation of the material research process.
The process
Discovery
With no prior background in material research, the logical starting point was to deep dive into understanding the R&D process and the various industry standards in use. Several qualitative research methods were employed to bring rich and comprehensive insights into the topics. Together with the product manager, I conducted a series of semi-structured interviews with the researchers, a field study trip to the experiment lab and various in-person observations with senior researchers.
Key findings
Based on the findings, we identified 3 key themes in the researcher's work: researching material characteristics, designing experiments, and documenting project progress. These were then translated into the key scenarios for creating tangible design concepts.
Key scenarios based on insights
Opportunities mapping and prioritisation
During this phase, it is important to quickly turn the gathered insights into more actionable design solutions. For this purpose, I adopted a scenario framework to support ideating and creating concrete outcomes.
Scenarios framework overview
The user’s journey and opportunities map were used as the foundation for ideating and prioritization. A strategic decision was made to focus on exploring the opportunities around the themes of working with experiments and projects.
Concepts for working with experiments
Concepts for working with projects
Design & validate
Together with Betolar’s researchers, we co-created the solution, an R&D analytics tool. The visual design adopted elements from Material Design UI with a focus on simplicity and efficiency. The product roadmap and feature design were shaped to realise the following principles:
Adaptability
R&D data can come from various sources, such as lab experiments and pilot trials. For effective analysis and collaboration, researchers should be able to access and work with all relevant data from one interface.
Standardisation
The R&D process is not always linear but having good data quality is vital for successful outcomes. To ensure the research quality, it's important to collect and analyse data consistently and according to industry standards.
Flexibility & robustness
The information may include structured and unstructured data. Researchers need various approaches to quickly analyse and create charts, graphs, and reports.
Report & communication
Sharing research findings helps researchers avoid duplicated work and increases efficiency. Sufficient data transparency and simplifying documentation are key elements to encourage this practice.
The impact
The R&D tool helps Betolar’s researchers and engineers speed up data analysis considerably. In addition, it increases the amount of data involved in iterating Geoprime® recipes. The tool has helped the R&D team improve their efficiency both individually and as a team by providing tools to document and share the findings. Due to the value provided and the emphasis on user experience, the tool is now used by the vast majority of the R&D team daily and has become a central part of the workflow.
*The image was blurred out due to confidential data
We establish a continuous validation cycle to ensure the developed features solve the right problems. Analytics were implemented early to help monitor and measure success. Key metrics of product usage were used to support prioritisation and shape the road map:
~80%
daily active users were reached in
2 months after launched
daily active users were reached in
2 months after launched
2h/day
is the average time users spend on the tool
is the average time users spend on the tool
90%
of users used the tool at least 2 days/month
of users used the tool at least 2 days/month
180-200
comparisons were created monthly
comparisons were created monthly
