Economic Parameters Module
Ahmed Yehia
User Researcher
Product Designer
UI Designer
Figma
Microsoft Teams
Miro
Business Overview 🏗️
Raisa Energy, founded in Denver in 2014 with a tech hub in Cairo, manages over $2 billion in energy sector investments through a unique platform. Its mission is to set the standard for energy investments by valuing risk in real-time using automation, AI, and Big Data, enhancing expert decision-making at the intersection of O&G, finance, and technology.
Problem Space 🚀
To manage investment risk, we need to predict lease operating expenses "LOE" for over 30,000 wells in the coming years. We're building a system that uses AI and Big Data to achieve this. Currently, we rely on both external and internal tools. Our goal is to integrate all external tools into our internal system, "Jarvis," to streamline the prediction process.
This snapshot illustrates user processes for predicting LOE and our plan to replace external tools with new internal ones.
Process 🪜
This flow outlines our process from problem understanding to solution implementation.
Discovery 🥽
We conducted ongoing stakeholder and user interviews to deepen our understanding of the problem. Based on this, we developed multiple flows that illustrate the user work processes and our vision.
a snap shot from an interview analysis process
Design 🖌️
We iterated designs to reach the desired MVP, using hi-fi prototypes as they were as easy to produce as wireframes.we later found this approach flawed⚠️, which I'll explain in the reflection.
empty lookup (table contains economic assumptions for lease operation expenses(LOE) for the wells)
adding economic assumptions to the lookup
lookup before pushing it to access tool (to populate the assumptions to more than 30,000 wells)
Testing & Iteration ⏰
The product manager and I conducted multiple usability testing sessions to evaluate the overall concept and specific design components.
A snapshot from a usability testing session with Geoff
an example of two different design components we tested
Implementation 🖥️
We focused on handing off designs tested with users and stakeholders to avoid mistakes that would require significant effort and time to fix.
Results 📝
Users provided positive feedback on the latest concept. We are preparing for full launch and will monitor user behavior using tools such as Mixpanel.
Reflection 🔦
Key Learnings
Key LearningsUsing flows to explain the design to the dev team helped them grasp the concept quickly.
Users often can't describe their work process easily due to its randomness, so we should build and validate the process with them.
To understand the user process, try performing it yourself.
Challenges and Corrections
Challenges and CorrectionsDue to advanced design tools enabling rapid hi-fi creation, we aimed for clear concept illustration. However, stakeholders felt constrained in critiquing due to perceived effort in hi-fi designs. Thus, we shifted to wireframing to encourage open feedback.
Our business is complex, requiring understanding of the US oil & gas industry, financials, and governmental regulations. With no competitors in this niche, we are pioneering new tools for the market.
