January 2022 - April 2025
1
Origami’s business strategy was to focus on the operations and management of Battery Energy Storage Systems (BESS), recognising it as the sector’s fastest-growing asset class.
2
At the time, the company’s financial runway was tightening, having just emerged from a demanding nine-month platform and technology migration.
3
The broader energy industry presented additional challenges: slow progress toward standardisation and poorly documented requirements from manufacturers.
4
Compounding this, no two BESS units operated in exactly the same way — even when their technical specifications appeared similar — creating significant complexity for product development and integration.
4 Backend squads
1 Frontend squad
Developers code bases:
React
Java
Spring
LLM (machine learning)
1 Product Designer
Softwares I used:
Figma & Figjam
Story Book
Jira
1
Origami’s business strategy was to focus on the operations and management of Battery Energy Storage Systems (BESS), recognising it as the sector’s fastest-growing asset class.
2
At the time, the company’s financial runway was tightening, having just emerged from a demanding nine-month platform and technology migration.
3
The broader energy industry presented additional challenges: slow progress toward standardisation and poorly documented requirements from manufacturers.
4
Compounding this, no two BESS units operated in exactly the same way — even when their technical specifications appeared similar — creating significant complexity for product development and integration.
Developers code bases:
4 Backend squads
1 Frontend squad
React
Java
Spring
LLM
Softwares I used:
1 Product Designer
Figma & Figjam
Story Book
Jira
1
Origami’s business strategy was to focus on the operations and management of Battery Energy Storage Systems (BESS), recognising it as the sector’s fastest-growing asset class.
2
At the time, the company’s financial runway was tightening, having just emerged from a demanding nine-month platform and technology migration.
3
The broader energy industry presented additional challenges: slow progress toward standardisation and poorly documented requirements from manufacturers.
4
Compounding this, no two BESS units operated in exactly the same way — even when their technical specifications appeared similar — creating significant complexity for product development and integration.
Developers
code bases:
4 Backend squads
1 Frontend squad
React
Java
Spring
LLM (machine learning)
Softwares
I used:
1 Product Designer
Figma & Figjam
Story Book
Jira
PERSONA - ASSET MANAGER
Asset managers like Nigella would benefit from a one-stop platform to effectively manage their assets as their portfolios grow. The platform was designed not only for clients’ internal teams but also for third parties involved in operations and maintenance — all working toward maximising the often elusive yield of each asset.
Nigella's challengers
Maximise the profitability of assets (BESS, generators, sites) across their full strategic lifespans (e.g., BESS ≈ 25 years) by identifying and leveraging market opportunities.
Manage asset health by optimising cycling strategies (full discharge to full charge) while mitigating risks such as warranty breaches and battery cell thermal runaway (fire).
Capture reliable performance data — both financial and physical — to demonstrate operational effectiveness, build investor confidence, and support future funding rounds.
Strengthen market positioning by managing relationships and opportunities with Routes to Market (RTMs).
Produce actionable reports for asset owners and investors to inform decision-making.
PERSONA - ASSET MANAGER
Asset managers like Nigella would benefit from a one-stop platform to effectively manage their assets as their portfolios grow. The platform was designed not only for clients’ internal teams but also for third parties involved in operations and maintenance — all working toward maximising the often elusive yield of each asset.
Nigella's challengers
Maximise the profitability of assets (BESS, generators, sites) across their full strategic lifespans (e.g., BESS ≈ 25 years) by identifying and leveraging market opportunities.
Manage asset health by optimising cycling strategies (full discharge to full charge) while mitigating risks such as warranty breaches and battery cell thermal runaway (fire).
Capture reliable performance data — both financial and physical — to demonstrate operational effectiveness, build investor confidence, and support future funding rounds.
Strengthen market positioning by managing relationships and opportunities with Routes to Market (RTMs).
Produce actionable reports for asset owners and investors to inform decision-making.
PERSONA - ASSET MANAGER
Asset managers like Nigella would benefit from a one-stop platform to effectively manage their assets as their portfolios grow. The platform was designed not only for clients’ internal teams but also for third parties involved in operations and maintenance — all working toward maximising the often elusive yield of each asset.
Nigella's challengers
Maximise the profitability of assets (BESS, generators, sites) across their full strategic lifespans (e.g., BESS ≈ 25 years) by identifying and leveraging market opportunities.
Manage asset health by optimising cycling strategies (full discharge to full charge) while mitigating risks such as warranty breaches and battery cell thermal runaway (fire).
Capture reliable performance data — both financial and physical — to demonstrate operational effectiveness, build investor confidence, and support future funding rounds.
Strengthen market positioning by managing relationships and opportunities with Routes to Market (RTMs).
Produce actionable reports for asset owners and investors to inform decision-making.
Following a self-driven UX/UI audit, I developed a clear overview of how the product looked and functioned. This process also surfaced the most pressing issues — effectively identifying the “worst of a bad bunch.” Below are three examples of these recurring themes.
1 - No Informational architectural hierarchy.
Report generation appeared to be the primary reason users accessed the platform. However, this feature was neither unique nor supported by a strong business case. More importantly, the reports were siloed — none of them shared data or insights with each other. As a result, users were left to manually piece together meaning across multiple files: DC market data → separate file Power data → separate file Connectivity data → separate file
2 - Crowded view from options overload.
3 - No financial, market or asset health data.
Following a self-driven UX/UI audit, I developed a clear overview of how the product looked and functioned. This process also surfaced the most pressing issues — effectively identifying the “worst of a bad bunch.” Below are three examples of these recurring themes.
1 - No Informational architectural hierarchy.
Report generation appeared to be the primary reason users accessed the platform. However, this feature was neither unique nor supported by a strong business case. More importantly, the reports were siloed — none of them shared data or insights with each other. As a result, users were left to manually piece together meaning across multiple files: DC market data → separate file Power data → separate file Connectivity data → separate file
2 - Crowded view from options overload.
3 - No financial, market or asset health data.
Following a self-driven UX/UI audit, I developed a clear overview of how the product looked and functioned. This process also surfaced the most pressing issues — effectively identifying the “worst of a bad bunch.” Below are three examples of these recurring themes.
1 - No Informational architectural hierarchy.
Report generation appeared to be the primary reason users accessed the platform. However, this feature was neither unique nor supported by a strong business case. More importantly, the reports were siloed — none of them shared data or insights with each other. As a result, users were left to manually piece together meaning across multiple files: DC market data → separate file Power data → separate file Connectivity data → separate file
2 - Crowded view from options overload.
3 - No financial, market or asset health data.
PARTS I PLAYED IN
PARTS I PLAYED IN
PARTS I PLAYED IN
PARTS I PLAYED IN
01.
While exploring the product’s value proposition, I introduced “How Might We” and “Jobs to Be Done” workshop methods. These approaches helped the team expand its collective understanding and generate realistic scenarios and use cases.
01.
While exploring the product’s value proposition, I introduced “How Might We” and “Jobs to Be Done” workshop methods. These approaches helped the team expand its collective understanding and generate realistic scenarios and use cases.
01.
While exploring the product’s value proposition, I introduced “How Might We” and “Jobs to Be Done” workshop methods. These approaches helped the team expand its collective understanding and generate realistic scenarios and use cases.
02.
I collaborated with energy industry expert Dan Brimelow to explore concepts around Asset Availability and Maintenance. Our key findings included: The importance of clearly displaying when an engineer is on site. The need to capture and communicate reasons for maintenance work.
02.
I collaborated with energy industry expert Dan Brimelow to explore concepts around Asset Availability and Maintenance. Our key findings included: The importance of clearly displaying when an engineer is on site. The need to capture and communicate reasons for maintenance work.
02.
I collaborated with energy industry expert Dan Brimelow to explore concepts around Asset Availability and Maintenance. Our key findings included: The importance of clearly displaying when an engineer is on site. The need to capture and communicate reasons for maintenance work.
03.
BESS was identified as the target segment, but we needed deeper insight into potential customers and their real needs. Under Crystal He’s leadership, the Product Owners conducted user interviews, which helped us build a richer understanding of customer pains and priorities.
03.
BESS was identified as the target segment, but we needed deeper insight into potential customers and their real needs. Under Crystal He’s leadership, the Product Owners conducted user interviews, which helped us build a richer understanding of customer pains and priorities.
03.
BESS was identified as the target segment, but we needed deeper insight into potential customers and their real needs. Under Crystal He’s leadership, the Product Owners conducted user interviews, which helped us build a richer understanding of customer pains and priorities.
04.
After 2.5 years of value proposition exploration, the team was running in circles. Then Crystal He brought clarity and focus, defining a tangible goal (see example: Configuration mind map) that gave us a foundation to shape and size the product. For me, it was a revelation — and the real product experiments finally began.
04.
After 2.5yrs of value proposition exploration we were a dizzy bunch. Enter Crystal He who sorted the focus, giving us a clear tangible goal (image example “Configuration mind map”) from which we could both size and work into the products shape. Was a revelation for me and so the products experiments began, good times.
04.
After 2.5 years of value proposition exploration, the team was running in circles. Then Crystal He brought clarity and focus, defining a tangible goal (see example: Configuration mind map) that gave us a foundation to shape and size the product. For me, it was a revelation — and the real product experiments finally began.
05.
Once we had a clearer sense of what the product might entail, it became clear the design language was still undefined. To bridge this gap, I turned to desk research and developed a visual language inspired by the interfaces service engineers use daily — primarily manual service dashboards and minimal, utilitarian UIs.
05.
Once we had a clearer sense of what the product might entail, it became clear the design language was still undefined. To bridge this gap, I turned to desk research and developed a visual language inspired by the interfaces service engineers use daily — primarily manual service dashboards and minimal, utilitarian UIs.
05.
Once we had a clearer sense of what the product might entail, it became clear the design language was still undefined. To bridge this gap, I turned to desk research and developed a visual language inspired by the interfaces service engineers use daily — primarily manual service dashboards and minimal, utilitarian UIs.
06.
The business was exploring the idea of global markets as a scalable proposition, while I experimented with console and dashboard concepts informed by insights from industry expert interviews. Together with the Product Owners, we developed lightweight use-case narratives, which I quickly transformed into Figma clickable prototypes for the next round of weekly and monthly concept validation sessions with users.
06.
The business flirted with notion of global markets as a scalable proposition. Whilst I was experimenting with consol/dashboard concepts from industry experts interview insights. Then the PO's and I worked up light weight narrative for a use case which I would then wiz up into a figma clickable prototype for next monthly/weekly interview slot.
06.
The business was exploring the idea of global markets as a scalable proposition, while I experimented with console and dashboard concepts informed by insights from industry expert interviews. Together with the Product Owners, we developed lightweight use-case narratives, which I quickly transformed into Figma clickable prototypes for the next round of weekly and monthly concept validation sessions with users.
07.
With the support of champion engineer Ben Neal, we established a Storybook design system. I provided the high-fidelity components, from which styles were extracted and integrated into his development branch/schema.
07.
Big thanks to Ben Neal champion engineer, we realised a “Story Book” design system, and I provided the hi-fidelity components from which the styles could be lifted and added to his schema.
07.
With the support of champion engineer Ben Neal, we established a Storybook design system. I provided the high-fidelity components, from which styles were extracted and integrated into his development branch/schema.
In practice, this meant operators were “flying blind,” unable to assess the financial cost, loss, or impact of running an asset. And because this view applied only to individual assets, scalability was ruled out from the start.
creating critical blind spots. Not knowing how an asset is functioning physically can be detrimental in three key ways:
Thermal runaway (fire risk): caused when an asset is cycled too aggressively (e.g., 4+ full charge/discharge cycles per day).
Warranty impact: overuse or misuse can invalidate coverage.
Maintenance inefficiency: wasted engineer time and increased costs.
At a glance, Nigella can now track an asset’s real-time trades across different markets and revenue pools.
At a glance, Nigella can now track an asset’s real-time trades across different markets and revenue pools.
A simple traffic-light system now visualises warranty, cycles, and availability (with targets), giving users an instant read on performance.
A simple traffic-light system now visualises warranty, cycles, and availability (with targets), giving users an instant read on performance.
With performance clearly summarised through a traffic-light system, Nigella is motivated to dive into the areas that need her attention.
With performance clearly summarised through a traffic-light system, Nigella is motivated to dive into the areas that need her attention.
MWh data was now available, thanks to the development team’s excellent work integrating new data into the front end through patches, connectors, sub-bus routines, relays, and API calls. This gave Nigella the ability to participate in intraday markets, diversifying her portfolio’s revenue streams.
MWh data was now available, thanks to the development team’s excellent work integrating new data into the front end through patches, connectors, sub-bus routines, relays, and API calls. This gave Nigella the ability to participate in intraday markets, diversifying her portfolio’s revenue streams.
Having a blind spot of not knowing in real time how your asset is functioning physically can be detrimental in 3 main ways. 1: Heat runaway (fire) if an asset is "thrashed" to hard, means cycled from empty/negative to positive/full charge to aggressively (eg 4+ cycles per day is high), 2: Warranty impact and 3: Maintenance engineers time wastage/cost.
Flying blind is an appropriate term when you don't know the financial cost/loss/impact of running your asset. Never mind the fact that this is only for a single asset, so scalability is ruled out at the get go.
Now Nigella can see in a snap shot the realtime trades of an asset, in various markets and revenue pools.
Warranty, Cycles, Availability (+targets) data is presented with clear traffic light system of a metrics performance.
Nigella is motivated to engage with areas of interest based off their summarised traffic light system of the metrics performance..
MWh data was now on the cards as the dev squad/team had done a smashing job at piping/weaving new data into the front end with patches/ports/connectors/sub-buss routines/relays and API's calls. Giving Nigella the opportunity to conduct Intraday markets diversifying her portfolios revenue stream.
With limited data, you also limit your options. Basic figures like asset location and energy output may be reassuring, but they don’t translate into real revenue opportunities.
Without market data, it’s impossible to know whether the energy produced was truly worth the effort. This lack of insight also weakens a producer’s position in discussions with Routes to Market (RTM) traders.
With Daily Availability and Revenue Impact data now integrated, Nigella can instantly see how her asset performed against Within-Day Availability and Market Prices. This opened the door to intraday trading, enabling her to maximise portfolio performance across variable markets.
She can also clearly identify where the greatest revenue opportunities were lost and focus on specific time periods to investigate potential availability or fault issues.
The daily availability and revenue impact of Nigella's asset portfolio can now be tracked across different time ranges, giving her the insight needed to adjust strategy and better meet performance targets.
With no market data you can't tell if what energy you produced was worth the effort. Additionally this weakens a producers power in conversations with root to market (RTM's) traders.
With limited data you limit your options, here having simple asset location and energy out put figures are reassuring but are not money makers.
With Daily Availability & Revenue Impact data now coming through, Nigella can now see instantly how her asset did with delivery in direct comparison to the new Within Day Availability & Market Prices, meaning Intraday tradings was on the cards for Nigella so she could maximise here portfolio in variable markets
Nigella can get a clear view of were she may have lost most revenue opportunity and then give her a time period to investigate for availability or fault issues.
Portfolio of assets daily availability and revenue impact is clear to track over various time ranges, giving Nigella the opportunity to adjust her strategy to better meet targets.
January 2022 - April 2025
assets
assets
have
have
loaded
loaded
January 2022 - April 2025