GreenBox is a produce-box startup with 200 subscribers in Perth, racing to reach 1,000 within six months. They’ve discovered their customers care more about convenience than local sourcing – and now they need to figure out whether the business model actually works at scale.
Maya has a board meeting in three weeks. The agenda is simple: present a credible path from 200 subscribers to 1,000 within six months. Show the board that GreenBox is worth the next tranche of funding. If she can’t make the case, the money stops.
She’s been working on the pitch deck in the evenings. Slides about subscriber growth, churn reduction, the JTBD insight, the assumption mapping results. Good slides. Compelling narrative. The kind of thing that makes investors nod.
But on Wednesday morning, she stares at slide nine – the financial projections – and realises she’s been avoiding the hard question. Not “can we grow?” but “can we grow profitably?”
She brings it to the team. “I can tell the board we know our customers. I can show them the JTBD data, the assumption mapping, the churn improvements. But they’re going to ask me one question I can’t answer: do the numbers work at 1,000 subscribers?”
Reaching for the familiar
Tom suggests Impact Mapping. “We could map the path to 1,000 subscribers the same way we mapped the path to 200. Goal, actors, impacts, deliverables.”
It’s a reasonable instinct, and the team spends thirty minutes on it. The Impact Map is useful – it shows that the path to 1,000 involves both reducing churn and expanding acquisition channels. But after half an hour, Maya shakes her head.
“This tells me how to grow. It doesn’t tell me whether we can afford to.”
She’s right. Impact Mapping connects features to goals. It’s powerful for prioritising work. But it doesn’t look at the business as a whole – revenue, costs, margins, partnerships, distribution. It doesn’t answer “does this business model actually work?”
Lee recognises the gap. “Impact Mapping is about which levers move the goal. What you need now is a picture of the whole machine – how money comes in, where it goes out, and whether the engine runs at the scale you’re targeting.”
He pauses. The team is watching him. Lee has been their guide through the entire discovery journey – Event Storming, Example Mapping, Impact Mapping, JTBD, assumption mapping. He’s the person who always has the next technique, the next framework, the calm voice that says “let’s try this.” Maya has grown to depend on that voice. They all have.
“I want to be honest with you,” Lee says. “I can help you map a business process. I can facilitate a discovery session. I can coach you on interview technique. But business model analysis – unit economics, pricing strategy, financial viability – that’s not my world. I’ve been around it, but I’ve never done it. And if I try to guide you through this, I’ll be doing exactly what we tell teams not to do: guessing at the answers instead of finding someone who knows.”
The room is quiet. It’s a harder thing to say than it sounds. Lee has been the authority in this room for months. Admitting a limit feels like stepping off a cliff. But he feels something he hasn’t felt in twenty years of consulting: relief. Relief at saying “I don’t know” before it becomes obvious.
During the silence, his phone buzzes in his pocket. He glances at it reflexively – a text from Yuki: Dad, can you call me this weekend? He puts the phone away. Maya notices.
“You can take that,” she says.
“She’ll call back,” Lee says.
Maya looks at him for a moment longer than necessary. “Will she?”
Lee doesn’t answer. He turns back to the whiteboard.
“I know someone who can help,” he says. “Charlotte Wong. She’s a senior agile coach, but not the kind who runs retrospectives and draws burndown charts. She’s scaled two subscription businesses past Series A. One of them grew from 300 to 50,000 subscribers in three years. She knows the patterns you’re about to hit.”
He suggests a Business Model Canvas – and suggests Charlotte help them fill it in.
What a Business Model Canvas is
The Business Model Canvas was created by Alexander Osterwalder. It’s a single-page framework with nine building blocks that describe how a business creates, delivers, and captures value.
The nine blocks:
- Customer Segments – Who are you creating value for?
- Value Propositions – What value do you deliver to each segment?
- Channels – How do you reach and deliver to customers?
- Customer Relationships – How do you acquire, retain, and grow customers?
- Revenue Streams – How does money come in?
- Key Resources – What do you need to deliver the value proposition?
- Key Activities – What must you do to make the model work?
- Key Partners – Who helps you do what you can’t do alone?
- Cost Structure – What are the major costs?
The power of the canvas is that it forces you to see everything on one page. Most teams think about their business in fragments – the product team thinks about features, the marketing team thinks about channels, the finance person thinks about costs. The canvas puts it all together so the connections (and contradictions) become visible.
Filling it in
Lee facilitates. The team takes a morning – nine o’clock to twelve-thirty, with a coffee break. Everyone contributes. Maya brings the business knowledge, Sam brings the customer data, Tom and Priya bring the operational reality, Jas brings the product perspective.
They use a large whiteboard divided into nine sections. Sticky notes again. (At this point, Tom jokes that he’s going to buy shares in 3M. Nobody laughs, which tells you something about the mood in the room.)
They work through each block.
Customer Segments:
Two segments emerged from the JTBD and assumption mapping work:
Convenience seekers (60%) – They hire GreenBox to eliminate dinner stress. They’d accept non-local produce if the price dropped. They want recipe cards, box previews, and flexible delivery schedules. Price-sensitive but loyal if the job gets done.
Local food advocates (40%) – They hire GreenBox because they believe in supporting local farms and eating seasonal produce. They’re willing to pay a premium. Local sourcing is part of their identity, not just a nice-to-have.
These aren’t guesses any more. They’re segments validated by the JTBD interviews and the assumption mapping survey.
Value Propositions:
For convenience seekers: “Dinner decided. A box of fresh produce with recipe cards arrives on your doorstep. No shopping, no meal planning, no stress.”
For local food advocates: “Know your farmer. 100% locally sourced, seasonal produce from farms within fifty kilometres.”
Maya writes both on the board and steps back. “We’ve been marketing one value proposition to two segments. That’s a problem.”
Lee nods. “The convenience seeker doesn’t care about the farmer story. The local advocate doesn’t care about recipe cards. You’re trying to be one thing for two different groups.”
Channels:
How does GreenBox reach customers? The assumption mapping data is useful here.
- Word-of-mouth: 31% of acquisitions
- Google search: 28%
- Instagram: 19%
- Local press: 14%
- Other: 8%
Delivery is via a local courier service. Customer communication is email (box preview, delivery notification, feedback requests).
Customer Relationships:
Acquisition: sign-up via website, first-box discount for convenience seekers, farmer stories and provenance information for local advocates.
Retention: recipe cards (major churn reducer), pause/skip functionality, box preview emails, feedback loop after each delivery.
Growth: referral programme (in development), potential upsell to add-on items.
Revenue Streams:
Simple: weekly subscription fees. $25/week for the standard box. Potentially $20/week for a mixed-sourcing box (not yet launched).
At 200 subscribers, all on the $25 box, that’s $5,000 per week in revenue. $260,000 per year. Sounds decent.
But Maya hasn’t looked at the other side yet.
Key Resources:
- The platform (Tom and Priya’s software)
- Farm relationships (Maya’s network)
- Delivery logistics (courier partnership)
- The team (Maya, Tom, Priya, Jas, Sam)
- Warehouse space for packing
Key Activities:
- Sourcing produce from farms weekly
- Matching supply to demand (partially automated, still requires Maya’s judgement)
- Packing boxes
- Managing deliveries
- Creating recipe cards
- Customer communication
- Platform development and maintenance
Key Partners:
- Local farms (supply)
- Courier service (delivery)
- Stripe (payments)
- LLM providers (recipe generation, customer analysis, development assistance)
Cost Structure:
This is where the room goes quiet.
Maya has the numbers in a spreadsheet. She hasn’t shared them with the full team before. She pulls them up on the projector.
Cost per box, at current volume (200 subscribers/week):
| Cost component | Per box |
|---|---|
| Produce (farm gate price) | $14.00 |
| Packing (materials + labour) | $3.50 |
| Delivery (courier) | $4.50 |
| Total variable cost | $22.00 |
Revenue per box: $25.00.
Margin per box: $3.00.
Tom does the arithmetic in his head. “Three dollars margin per box. Two hundred boxes a week. That’s $600 a week. $31,200 a year.”
The room is silent.
$31,200 doesn’t cover Maya’s salary, let alone the rest of the team, the warehouse rent, the software costs, or the marketing spend. At 200 subscribers, GreenBox is burning through its seed funding every single week.
“What about at 1,000 subscribers?” Priya asks.
Maya updates the spreadsheet. Some costs come down with volume – packing labour gets more efficient, courier rates drop with guaranteed volume. But produce costs are relatively fixed. Farms don’t offer bulk discounts at these scales.
Cost per box at 1,000 subscribers (estimated):
| Cost component | Per box |
|---|---|
| Produce (farm gate price) | $13.00 |
| Packing (materials + labour) | $2.50 |
| Delivery (courier, volume rate) | $3.50 |
| Total variable cost | $19.00 |
Revenue per box: $25.00.
Margin per box: $6.00.
$6,000 per week. $312,000 per year. That covers salaries and basic operations, barely. There’s no money for growth, no cushion for bad weeks, no investment in the platform.
Tom stares at the projector. “We’re building a charity.”
The uncomfortable discovery
The canvas is doing exactly what it’s supposed to do: showing the whole business on one page so the contradictions become visible.
The JTBD insight was correct – subscribers hire GreenBox to eliminate dinner stress. The assumption mapping was valuable – it revealed that 60% of subscribers would accept non-local produce at a lower price. The churn reduction from recipe cards is real.
But none of that matters if the unit economics don’t work.
The problem is structural. 100% local sourcing is expensive. Farm gate prices within fifty kilometres are higher than wholesale market rates. That’s not surprising – small local farms can’t compete on price with industrial agriculture. The premium is the point. But the premium is also eating the margin.
Maya looks at the canvas and sees the contradiction staring back at her. The value proposition for 60% of her customers is convenience, not local sourcing. But the cost structure assumes 100% local sourcing. She’s paying the premium for local produce, but the majority of her customers wouldn’t notice if she didn’t.
“What if we offered the mixed-sourcing box?” Jas asks. “The assumption mapping showed 60% would switch to a $20 mixed box.”
Maya runs the numbers. If produce cost drops to $8 per box with mixed sourcing (a blend of local and wholesale market produce), the economics change dramatically:
| Model | Revenue/box | Cost/box | Margin/box | Weekly margin (1,000 subs) |
|---|---|---|---|---|
| 100% local, $25 | $25.00 | $19.00 | $6.00 | $6,000 |
| Mixed sourcing, $20 | $20.00 | $14.00 | $6.00 | $6,000 |
| Blended (40% local, 60% mixed) | — | — | $6.00 | $6,000 |
Wait. The margin per box is the same. Tom frowns at the spreadsheet. “That can’t be right. The mixed box is cheaper to make and cheaper to sell?”
“The margin per box is the same,” Maya says. “But look at what happens to the subscriber count.”
She draws a scenario on the whiteboard:
Scenario A: 100% local only, $25/box. Addressable market is the 40% of potential subscribers who value local sourcing enough to pay the premium. Growth ceiling is lower. Churn is higher among the 60% who are price-sensitive.
Scenario B: Two tiers. $25 local box for advocates, $20 mixed box for convenience seekers. Addressable market doubles. The mixed box brings in subscribers who would never pay $25. The local box retains the advocates who’d feel betrayed by non-local produce.
“If we had both options and reached 1,000 subscribers – say 400 local boxes and 600 mixed boxes – the weekly margin is still about $6,000. But reaching 1,000 becomes much more plausible because we’re not excluding 60% of the market.”
Tom leans back. “And if the mixed box customers grow faster because they’re cheaper to acquire and retain, we could hit 1,000 faster and have better cash flow on the way there.”
Priya adds: “And the mixed sourcing means we’re not dependent on local farms scaling up in six months. Dave told you he can’t increase supply until next growing season. Mixed sourcing solves that constraint.”
The canvas made the problem visible. The JTBD data and assumption mapping results provided the solution. Each technique on its own would have produced a partial picture. Together, they’ve reframed the entire business model.
Where Lee’s honesty pays off
The team is energised. For the first time in weeks, the path to 1,000 feels not just possible but practical. Two product tiers. Two value propositions for two segments. Better margins, larger addressable market, reduced supply chain risk.
But the conversation quickly moves beyond what any of them – Lee included – can answer with confidence. The questions come fast.
“How do we price the local box to maximise the segment that values it?” Sam asks.
“Should we offer an annual subscription at a discount to lock in commitments?” Maya wonders.
“What about the investor pitch? Do we position the mixed box as the growth engine and the local box as the premium tier? Or do we lead with local and frame mixed as the accessible option?” Jas is already thinking about the narrative.
“How does the cost of customer acquisition compare between the two segments? And what’s the lifetime value difference?” Priya asks, surprising everyone with a question that’s pure business, not engineering.
Lee catches Maya’s eye. These are exactly the kind of questions he’d flagged earlier – the ones that live outside his competence. The team needs Charlotte. Lee’s honesty that morning, hard as it was to voice, means nobody is looking to him for answers he doesn’t have. They’re looking forward instead of sideways.
“I’ll set up a call with Charlotte for Friday,” Lee says. “Bring the canvas. Bring the numbers. And bring your hardest questions – she won’t flinch.”
“How do you know her?” Tom asks.
“We worked together five years ago. I was helping a SaaS company with their domain modelling and she was coaching the leadership team on growth strategy. We overlapped for six months. She challenged half the things I thought I knew about how businesses actually scale. She’ll be direct with you – sometimes uncomfortably so. But she’s seen the movie you’re about to watch.”
Charlotte
They set up a video call for Friday afternoon. Charlotte joins from what looks like a home office in Perth’s northern suburbs. She’s 41, short grey hair, a bookshelf behind her stuffed with business books and, inexplicably, a small collection of wooden ducks. Her camera angle is precise – good lighting, uncluttered background. The kind of frame that says this person has done a thousand video calls and knows exactly what the other side sees.
Charlotte Wong grew up in Penang, Malaysia. She moved to Australia at fifteen when her father took a university position in Sydney. Engineering degree from UNSW, then a career that zigzagged through the specific kind of companies that either scale or die: a meal kit company, a SaaS platform, a logistics startup. The SaaS platform was acquired. The logistics startup is still running. The meal kit company – the one she doesn’t talk about unless you ask directly – folded eighteen months after she joined as lead coach. She’d done everything right, or thought she had. Process. Structure. Cadence. The unit economics were wrong from the start and nobody caught it until the cash ran out. She keeps a spreadsheet of every business she’s ever worked with – what they got right, what they got wrong, what she wishes she’d said sooner. Row 47 is GreenBox. She added it yesterday, after Lee’s call.
She lives with her husband James, a quantity surveyor, and their twin sons Max and Ollie, twelve years old and at the age where everything is either “boring” or “unfair.” James jokes that their family operates on two-week sprints. Charlotte doesn’t find it as funny as he does.
Lee does introductions and gives Charlotte a ten-minute summary: the GreenBox story, the discovery work, the JTBD insights, the assumption mapping, the Business Model Canvas they’d just built. He shares his screen and shows the canvas.
Charlotte listens without interrupting. Her face is still. Not hostile – diagnostic. She’s reading the canvas the way a mechanic reads an engine: looking for the part that’s about to fail.
Then she asks three questions.
“What’s your customer acquisition cost?”
Silence. Nobody knows. Sam has rough numbers – they spent about $800 on Instagram ads last month and got maybe fifteen sign-ups from it – but that’s one channel, one month, with no attribution model.
“You don’t know,” Charlotte says. It’s not accusatory. It’s diagnostic. “That’s the most important number in a subscription business and you don’t know it. If you can’t tell the board what it costs to acquire a customer, you can’t tell them whether growth is profitable or just expensive.”
Second question: “What’s your subscriber lifetime value?”
Maya starts to answer: “Well, the average subscriber stays for…” She trails off. “We don’t actually track cohort retention that way. We know monthly churn is about 5% now, down from 8%.”
“So at 5% monthly churn, average lifetime is about twenty months,” Charlotte says, doing the maths instantly. “At $25 a week, that’s roughly $2,000 lifetime revenue per subscriber. Minus the variable costs you showed me, that’s about $120 lifetime margin at current scale, $480 at 1,000 subscribers. Does that sound right?”
Maya blinks. “I… think so?”
“Good. Because if your customer acquisition cost is more than $480, you lose money on every subscriber you add. Growth makes you poorer, not richer. That’s the death spiral that kills subscription businesses and it’s invisible until you’re out of cash.”
She says this without emotion, but behind the flat tone is the meal kit company. Row 12 on her spreadsheet. They’d grown to 4,000 subscribers before anyone realised the CAC was higher than the lifetime margin. Every new customer made the company poorer. By the time Charlotte identified the problem, the runway was three months. They closed in two. She’s never fully stopped carrying that one.
Charlotte pauses. “One more thing. Lee mentioned a competitor – Freshly. What do they charge?”
“Eighteen dollars a week,” Sam says.
“So at twenty-five dollars, you’re competing with a company that charges seven dollars less, has sixty times your funding, and delivers a polished technology experience. If your customers are convenience-driven – and your JTBD data says sixty percent of them are – and Freshly delivers convenience at a lower price with better technology, what’s your moat?”
Nobody answers. Charlotte doesn’t wait for one.
Third question: “Your canvas shows two customer segments with different value propositions. Have you modelled what happens to your farm relationships if you introduce mixed sourcing?”
“What do you mean?” Maya asks.
“Your local farms are your key partners. They’re also your brand. If you launch a $20 mixed box and 60% of your subscribers switch to it, your local farm orders drop by 60%. Dave and Rachel are suddenly selling you 40% of what they used to. Can their businesses survive that? And if they can’t, what happens to your $25 local box when you don’t have local farms to supply it?”
Nobody had considered this. The canvas showed key partners in one box and cost structure in another. Charlotte saw the dependency between them – that changing the cost structure could destroy the partnerships.
The room is very quiet.
“I’m not saying the mixed box is wrong,” Charlotte says. “I’m saying you need to model the second-order effects. A two-tier model might work brilliantly. But you need to bring your farms along, or you’ll have a cheap box with no story and an expensive box with no supply.”
Maya writes furiously. Tom is typing notes. Priya has her thinking face on – the one she gets when she’s modelling a system in her head.
“I’ve got a lot more questions,” Charlotte says. “But those three are the ones that’ll tell you whether your board pitch holds water. Can I see the full financials and subscriber data before our next call?”
Maya nods.
“Good. I’ll send you a framework for calculating CAC and LTV by segment. It’s a spreadsheet. Nothing fancy. But it’ll make the board conversation much sharper.”
She pauses, then: “Lee told me about the discovery work you’ve done. The Event Storming, the JTBD interviews, the assumption mapping. That’s genuinely impressive for a team this size. Most startups at your stage are still arguing about what the product should be. You know your domain, you know your customers, and you know which of your assumptions are shaky. That’s rare.”
“The next problem is different. You need to know whether the business works, not just whether the product works. They’re different questions, and they need different tools. I can help with that.”
Lee smiles. It’s the smile of someone who’s been carrying a weight and just handed part of it to someone who can hold it properly.
After the call, Charlotte closes her laptop and sits in her home office for a moment. The wooden ducks on the shelf – Max and Ollie gave them to her, one each, for her birthday three years ago – stare back with painted eyes. She picks up her phone and calls James.
“How was it?” he asks. She can hear the boys arguing about something in the background.
“I just told a founder her business model doesn’t work. The look on her face.”
“Is the business worth saving?”
Charlotte thinks about Maya’s eyes when the $3 margin appeared on the projector. Not defeat – recognition. Like someone who’d suspected the answer and was relieved to finally see it written down.
“I think so,” Charlotte says. “But she has to decide that, not me.”
She opens her spreadsheet. Row 47. In the “First Impression” column, she types: Strong discovery culture. Broken unit economics. Founder identity tied to local sourcing – biggest risk is emotional, not financial.
That night, Maya sits at the kitchen table in Fremantle. Nadia is in the other room reading. The house is quiet. Maya opens her laptop and starts a new email.
Dear GreenBox subscribers,
We’ve made the difficult decision to pause operations while we–
She stops. She stares at the words. She writes another sentence:
–reassess our business model to ensure we can continue to deliver the quality you expect.
She reads the three sentences back. They’re corporate and bloodless and they sound nothing like her. She imagines Mrs Patterson reading them. She imagines Patrick reading them. She imagines Dave reading them and thinking: Another one.
She doesn’t delete the draft. She doesn’t send it. She just sits there, looking at the three sentences on the screen.
Nadia appears in the doorway. “Come to bed.”
Maya closes the laptop. “Coming.”
She doesn’t tell Nadia about the email. She doesn’t tell anyone. The draft sits in her email, unsent, for the next six months.
What the canvas revealed
The Business Model Canvas session took a morning. It didn’t require special software, consultants, or weeks of analysis. It required the team to sit down and look at everything on one page.
What it revealed:
The unit economics don’t work at current pricing with 100% local sourcing. $3 margin per box at 200 subscribers is a burning platform. Even at 1,000, the $6 margin barely covers operating costs. The business model needs restructuring, not just growth.
The JTBD and assumption mapping insights have business model implications. The fact that 60% of subscribers would accept mixed sourcing isn’t just a product insight – it’s a business model pivot. Different cost structure, different value proposition, different addressable market.
The canvas exposes dependencies between building blocks. Changing one block (cost structure) affects others (key partners, value propositions, customer segments). These dependencies aren’t obvious when you think about the business in fragments. They’re unavoidable when you see everything on one page.
The team has product expertise but needs business model expertise. Lee’s techniques got the team from chaos to clarity on the product side. Charlotte’s experience can do the same on the business side.
The canvas is a snapshot, not a strategy
One thing Lee is careful to point out before the session wraps up: the Business Model Canvas is not a strategy. It’s a snapshot of your current thinking about the business model. It shows you where you are and what the assumptions are. It doesn’t tell you where to go.
“Update it regularly,” Lee says. “The canvas you fill in today will be wrong in three months. Your customer segments will shift. Your cost structure will change as you add mixed sourcing. Your channels will evolve as you invest in SEO. The canvas is useful because it makes the current state visible, not because it predicts the future.”
Maya photographs the whiteboard. She’ll update it after Charlotte’s framework produces the CAC and LTV numbers. And again after the board meeting. And again when (if) they launch the mixed-sourcing box.
The canvas is a living document. The moment it becomes a poster on the wall that nobody updates, it stops being useful.
When to use a Business Model Canvas
When you’re preparing to pitch investors. The canvas forces you to think about the whole business, not just the product. Investors will ask about cost structure, channels, partnerships, and revenue streams. The canvas makes sure you’ve thought about all of them.
When you’re considering a significant business model change. Launching a new pricing tier, entering a new market, changing your distribution model – any of these affect multiple blocks on the canvas. Seeing them all on one page helps you anticipate second-order effects (like Charlotte’s question about farm partnerships).
When different parts of the team have different mental models of the business. Product thinks about features. Marketing thinks about channels. Operations thinks about costs. The canvas puts everyone’s perspective on one page and shows where they connect – and where they contradict.
When you’re post-revenue but pre-profitability. This is exactly where GreenBox sits. The product works. People pay for it. But the business model might not sustain itself. The canvas helps you diagnose why.
When not to use it
When you’re pre-product. If you haven’t built anything yet and don’t have customers, the canvas will be mostly speculation. Build something, get customers, learn from them, then canvas.
When the problem is execution, not strategy. If the business model is sound but deliveries keep arriving late, you don’t need a canvas – you need to fix your logistics. The canvas is for strategic clarity, not operational debugging.
As a one-off exercise that produces a poster. A canvas that gets filled in once and never updated is wallpaper. The value is in the regular revisiting – seeing what’s changed, what assumptions have been validated or invalidated, what blocks need to shift.
When you need detailed financial modelling. The canvas is a strategic overview. It tells you what the cost structure looks like, not the exact numbers. For detailed unit economics, CAC/LTV calculations, and financial projections, you need a spreadsheet (or Charlotte’s framework). The canvas tells you which numbers matter; the spreadsheet tells you what they are.
What comes next
The GreenBox team is at an inflection point. They’ve gone from “building the wrong thing fast” (Series 1) to “understanding the domain and shipping what matters” (Series 1 and 2) to “understanding the customer and the business model” (this series).
The discovery techniques from the earlier series – Event Storming, Example Mapping, BDD, Impact Mapping, User Story Mapping – remain essential. The team will use them every week. But the new techniques – JTBD, Assumption Mapping, Business Model Canvas – address different questions. Not “what should we build?” but “what business are we actually in?”
Lee hasn’t left. He’s still the team’s guide for domain modelling, story writing, and turning business understanding into working software. But he’s no longer the only guide. Charlotte brings something Lee doesn’t have: experience scaling subscription businesses through the specific challenges of Series A, pricing strategy, and growth mechanics.
Some problems need a domain expert. Some need a business model expert. The team that recognises which is which – and has the humility to ask for the right help – is the team that reaches 1,000.
Maya has three weeks to prepare her board pitch. She has the JTBD data, the validated and invalidated assumptions, the Business Model Canvas, and Charlotte’s framework for calculating the numbers that matter. For the first time, she’s preparing a pitch based on evidence rather than conviction.
She’s also preparing to propose something that would have been unthinkable three months ago: a two-tier product model that partially abandons the 100% local sourcing she built the company around. The data says it’s the right move. Her gut says it’s a betrayal of the founding vision.
Charlotte told her, on that first call: “The founders who scale are the ones who fall in love with the problem, not the solution. You fell in love with local sourcing. Your customers fell in love with not thinking about dinner. Those aren’t the same thing. The question is which love you’re willing to let evolve.”
Maya is still thinking about that.
But thinking isn’t a plan. The team has JTBD data, invalidated assumptions, a BMC showing broken unit economics, and Charlotte’s frameworks. They know what’s wrong. They can’t fix everything at once. The board meeting is in three weeks.
The question isn’t what to change. It’s what changes first (coming 7 July).