Design Sprint.
The optimiSation and management tool for biomethane consumables orders
Overview
GRDF, a major gas distributor in France, is committed to promoting biomethane, the green gas produced from organic materials such as agricultural and food waste. Biomethane represents a significant step towards energy independence and the reduction of greenhouse gas emissions.
The injection points at the edge of agricultural operations are crucial for injecting biomethane into the gas network. However, to ensure the compliance of the gas produced with safety and quality standards, the addition of specific consumables is necessary.
These consumables include:
- THT (Tetrahydrothiophene) to odorize the gas,
- Nitrogen to push the THT into the conduits,
- Helium to propel the odorized gas into a quality controller before its injection into the network.
Understanding the problem
The maintenance of these stations, carried out by biomethane referents, involves the use of consumables to ensure the quality and safety of the gas. Currently, each referent manages this complex task using individual Excel files. This labor-intensive process requires meticulous collection and analysis of information, resulting in a very time-consuming management.
So, how to create an efficient management tool that allows anticipating orders of consumables (THT, nitrogen, and helium) for the maintenance of biomethane stations to optimize costs and reduce risks?
Define and understand the need
We interviewed an expert biomethane referent to better understand the challenges (pain points) in managing injection stations. This discussion highlighted their responsibilities and the issues faced. Our notes identified key problems, using open-ended questions (how could we?) to gain insight into crucial steps in the user journey
Pain points
Data isolation
The use of an individual Excel file isolates the data and makes real-time collaboration with other team members challenging. This can lead to delays in communication and coordination
Lack of visibillity
The biomethane referent may struggle to obtain a clear overview of maintenance activities, leading to decisions based on limited or outdated information
Time and Effort
The manual collection and analysis of data in an Excel file can be extremely time-consuming, limiting the time that the biomethane referent could dedicate to more strategic tasks
Forecasting challenge
The absence of automated tools can make it challenging to accurately forecast consumable needs, which may impact production continuity and gas quality
Personal Dependancy
Relying on a single individual to manage the entire process poses a risk of critical dependence on that person, which can affect operational resilience
Solution
Create an intelligent and learning tool that will support referents in their decision-making, helping them anticipate, optimize, and arbitrate orders, taking into account all constraints: safety, quality, logistics, and finances.
Brainstorming
Ideation
User flow and Storyboard
User Flow: Guided by the highest-rated ideas, we developed a user flow, which is a visual representation of the path users will take when interacting with the solution. This representation highlighted key steps, decision points, and interactions
Storyboarding: to bring the user journey to life, we used a storyboard. This technique involves creating a sequence of images or sketches illustrating each step of the experience, from start to finish. This helped visualize in a tangible way how users would interact with the solution:
High fidelity Prototype. Preparation for User Tests
User Tests
Individual Interviews: we conducted five individual interviews, each lasting approximately 45 minutes. Each participant had the opportunity to test interactions with the prototype while being visible on screen during these video conference sessions.
Debrief & Feedback: after the five user tests, our team gathered to review the feedback received. We analyzed trends and common issues to define necessary corrections for improving the prototype.
Prototype Iteration: feedback from the tests was taken into account to make adjustments to the high-fidelity prototype.
Results and takeaways
In conclusion, our journey through this project to address GRDF’s challenges in managing biomethane injection stations has been exciting and fruitful. After meticulously exploring needs and issues, we translated this knowledge into a tangible solution. Through carefully designed steps, including iterative design of the high-fidelity prototype and thorough user testing, we presented our proposal in a 7-minute pitch. The positive reaction from GRDF underscores the effectiveness of our approach and the alignment of our solution with their needs. Their enthusiasm to further explore and implement our solution validates our work and demonstrates its potential to create a positive impact
