Trying to capture a $10B enterprise market
Summary
How I navigated the complexities of building an enterprise tool for startups
In late 2024, I joined a 7-member startup to design an MVP for a financial forecasting tool tailored to climate-focused companies. These organizations struggle to model the financial impact of their initiatives, so our goal was to simplify budgeting, forecasting, and risk analysis through an intuitive interface.
With no existing design strategy, I led the UX efforts to create a platform that made complex financial modeling accessible and user-friendly—all while working within tight deadlines.
Role
Mid-Senior UX Designer
Responsibilities
Information Architecture
Competitor Analysis
User Task Flows
Wireframes
Prototyping
Stakeholder presentation
Timeline
3 months (2024)
The Problem
Enterprise financial planning
stuck in spreadsheet hell
Imagine managing complex financial planning with outdated Excel sheets and scattered tools—juggling numbers, wrestling with clunky visuals, and worrying about errors that could derail critical decisions.
As one analyst put it during market research: "I spend about 15 hours a week just validating Excel files instead of actually working on stuff I need to." This wasn't just about inefficient tools - it was about brilliant minds spending their time fighting spreadsheets instead of fighting climate change.
Accuracy at Risk
When financial planning depends on manually copying data between tools, errors are inevitable. One project manager recalled how a single miscopied cell led to a week-long wild goose chase through their financial models.
Inefficient collaboration and versioning
We've all seen it: finalversion5_REAL_FINAL_v2.xlsx. What begins as simple file sharing soon turns into a mess of competing versions, lost feedback in email chains, and painfully slow iterations.
Scenario planning issues
“What if” scenarios were turning into “what now” nightmares. Teams duplicated entire spreadsheets to test assumptions, creating a tangled web of files that made tracking changes and explaining variances to stakeholders nearly impossible.
I spend about 15 hours/week validating excel files than actually working on stuff I need to…
Excel limitations single-handedly driving up Xanax purchases for program managers
My contributions
to the final designs
Over 3 months, I set out to bridge the gap between Excel's familiarity and the advanced capabilities modern enterprises need.
Feature #1
Robust Data
Visualization Tools
Every financial model tells a story—of growth, impact, and the future. I designed a modular dashboard that turned complex data into clear, interactive visuals, allowing project managers to present financial models without losing their audience.
Feature #2
Scenario Analysis Sandbox
Teams could now explore scenarios with ease. Want to see the impact of a 20% drop in material costs? Click. Need best- and worst-case models? Click, click. No more duplicated spreadsheets or broken formulas.
Feature #3
Versioning and Collaboration Support
Inspired by tools like Atlassian, I prioritized page-level sharing and robust version control, ending the chaos of endless email chains and conflicting file versions for stakeholders and investors.
So how did
we get there?
I believe every project has something for me to learn and no design process is set in stone! This project in particular, cut both ways and required me to fail and learn quickly and often.
A talented team
and a running clock
No idea too big or small
Startups move fast—tight timelines, limited budgets, and little upfront design thinking. With just three months to deliver an MVP, the pressure was constant. But what made this project thrive was the team’s deep investment in the product and adaptability under pressure.
Surrounded by resourceful experts who knew their market inside out, I had the freedom to ideate boldly. Technical challenges weren’t roadblocks—every idea, big or small, was worth exploring.
Following the trail
with secondary research
Previously conducted user interviews laid the groundwork for understanding our target users. To maximize a limited timeframe, I conducted stakeholder meetings, tapped into Discord communities and financial contacts for secondary insights, and analyzed existing primary research for deeper user understanding.
The SCAMPER method was invaluable during the early stages, helping us explore product strategy and identify potential functionalities from business, engineering, and product perspectives.
I'm in! Now.. what the hell
even is a TEA?
Designing enterprise solutions with a non-financial background
A Techno-Economic Analysis (TEA) assesses a technology’s value by weighing its benefits against its costs.
Without a financial background, I had to quickly learn key concepts like this to design an intuitive, efficient platform. It meant countless Google searches and plenty of reading—but that learning curve was part of the journey!
"You'll be drinking from the fire hose!"
I created an ecosystem of relevant components of a economic analysis that I could refer while building out the information architecture and user work flows
Aligning features
and product strategy
Identifying table stakes and differentiators
With the clock ticking, we needed to be strategic about what we built first. I led a competitive analysis to identify what features were table stakes versus true differentiators. This wasn't just about checking boxes - it was about finding gaps where we could add unique value.
Some pushback
to embrace the startup mindset
During feature ideation sprints, I initially held back, self-editing ideas to fit constraints—a habit from my technical background. But the team encouraged open exploration, prioritizing rapid creation, testing, and iteration. This shift aligned perfectly with the startup’s ethos and pushed me to embrace a more experimental approach.
The product analysis helped us refine the design by building on current feature iterations found in competitors while saving precious time ideating
Learning
Putting all the
pieces together
Iterating well on the way to the finish line
During the design phase, I began iterating on the features the team had finalized. Using the established information architecture and visual hierarchy, I rapidly created and refined wireframes to achieve the visual fidelity needed for developers to begin implementation and for user testing to validate our direction.
Something I'd do differently…
Following the F-Pattern due to primarily western user base, I created simple visual guidelines to inform wireframes
An example of the iteration process for data visualization dashboards across sprints
And now we wait…
As my contract ended, I checked in with the team to see how things were progressing. They were already recording improvements for future iterations as developers built on our foundational designs. An awesome experience and a team full of promise.
It was a fantastic learning experience with a team deeply invested in their product—I hope to work with them again someday!
