01.

Indiation methods
Whilst we were exploring the product's value proposition, I introduced “How Might We” and “Jobs To Be Done” workshop methods to better expand on our general knowledge, and bake up some realistic scenarios and use cases.
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
01.

Whilst we were exploring the product's value proposition, I introduced “How Might We” and “Jobs To Be Done” workshop methods to better expand on our general knowledge, and bake up some realistic scenarios and use cases.
01.

Whilst we were exploring the product's value proposition, I introduced “How Might We” and “Jobs To Be Done” workshop methods to better expand on our general knowledge, and bake up some realistic scenarios and use cases.
01.

Whilst we were exploring the product's value proposition, I introduced “How Might We” and “Jobs To Be Done” workshop methods to better expand on our general knowledge, and bake up some realistic scenarios and use cases.
02.

I was teamed up with an energy industry expert Dan Brimelow, tasked with looking at Asset Availability and Maintenance concepts. Key findings 1: Displaying engineer on sight. 2: Adding Reasons for maintenance work were of particular importance.
02.

I was teamed up with an energy industry expert Dan Brimelow, tasked with looking at Asset Availability and Maintenance concepts. Key findings 1: Displaying engineer on sight. 2: Adding Reasons for maintenance work were of particular importance.
02.

I was teamed up with an energy industry expert Dan Brimelow, tasked with looking at Asset Availability and Maintenance concepts. Key findings 1: Displaying engineer on sight. 2: Adding Reasons for maintenance work were of particular importance.
03.

BESS was the target segment, but we needed to become more familiar with the potential customers and their actual needs. So under Crystal He's leadership the PO’s set out conducting potential user interviews that helped us to build a richer picture of their pains and needs.
03.

BESS was the target segment, but we needed to become more familiar with the potential customers and their actual needs. So under Crystal He's leadership the PO’s set out conducting potential user interviews that helped us to build a richer picture of their pains and needs.
03.

BESS was the target segment, but we needed to become more familiar with the potential customers and their actual needs. So under Crystal He's leadership the PO’s set out conducting potential user interviews that helped us to build a richer picture of their pains and needs.
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 2.5yrs 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 2.5yrs 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.
05.

Now that we had a clear notion of what the product may entail - the design language was a long ways off. So I turned to good old desk research and formulated a language based off what interfaces service engineers engage with on a daily basis, largely manually operated service dashboards and barebones basic user interfaces.
05.

Now that we had a clear notion of what the product may entail - the design language was a long ways off. So I turned to good old desk research and formulated a language based off what interfaces service engineers engage with on a daily basis, largely manually operated service dashboards and barebones basic user interfaces.
05.

Now that we had a clear notion of what the product may entail - the design language was a long ways off. So I turned to good old desk research and formulated a language based off what interfaces service engineers engage with on a daily basis, largely manually operated service dashboards and barebones basic user interfaces.
06.

The business flirted with notion of global markets as a scalable proposition. Whilst I was also experimenting with consol/dashboard concepts from industry experts interview insights. The PO's and I worked up light weight narratives for use cases, which I wizzed up into figma clickable prototypes for the next monthly/weekly interview round of concept and proposition validation sessions.
06.

The business flirted with notion of global markets as a scalable proposition. Whilst I was also experimenting with consol/dashboard concepts from industry experts interview insights. The PO's and I worked up light weight narratives for use cases, which I wizzed up into figma clickable prototypes for the next monthly/weekly interview round of concept and proposition validation sessions.
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.
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 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 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.
PARTS I PLAYED IN
PARTS I PLAYED IN
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.
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.
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.
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.
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 Nigella an instant read on performance.
A simple traffic-light system now visualises warranty, cycles, and availability (with targets), giving Nigella 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.
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 limited data you limit your options, here having simple asset location and energy out put figures are reassuring but are not money makers.
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 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 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.
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.
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.
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.
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 Nigella 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 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.