Ecom CFO Notebook - cash decision making

Welcome to this issue of Ecom CFO Notebook – a weekly letter for 7–9 figure ecommerce founders and CFOs, sharing my perspective and stories for profitable growth.

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Sam here.

This is one of the longer newsletters I’ve written. Tried to shorten it but I have alot to say.

A few years ago, I advised a client not to pay his credit card for three months.

He had strong unit economics and was profitable, but just needed time for the cash to catch up.

So we went through what he could and couldn't move. Payroll? Can't skip that. Ad spend? Turn it off and revenue stops. Suppliers? Already had inventory in production.

Credit card payment? That was the softest constraint.

He was leasing his place, had no plans to buy anything that would pull his credit, and didn't care if his personal credit score took a hit.

So he just stopped paying. Ignored it for three months.

The credit card company eventually offered a payment plan with (better than expected) terms. And, paradoxically, he opened a new card to keep the ads running.

Sounds crazy. But it was the right move for his specific situation.

Parts 1 and 2 of our cash flow series focused on building the forecast. Now, let’s get into the next step: how to use that forecast in decision-making.

The constraints and opportunities framework

Cash flow decision-making comes down to two scenarios.

When cash is tight, the focus is on constraints. What can be moved, delayed, or renegotiated to avoid hitting zero?

When cash is abundant, the focus shifts to opportunities. What should be done with the surplus—pull initiatives forward, invest in growth, optimize terms?

The decision-making process is the same for both.

Just applied in opposite directions.

The core question for every line item in the forecast: what if.

What if that payment gets pushed two weeks? What if the order gets split? What if terms get renegotiated?

Each "what if" gets evaluated on two things: impact and timing.

Impact has two parts: quantitative (the dollar amount) and qualitative (relationships, future flexibility, strategic positioning).

Timing is straightforward: which specific week does this affect?

Let's start with the constraint side since that's where most of the decision-making pressure lives when the forecast shows cash getting tight.

Managing constraints

Not all constraints are equal. The key is working from least constrained to most constrained.

Tier 1 - Softer constraints: Lines of credit, credit card balances, and personal credit score impacts all vary by individual situation.

Tier 2 - Soft constraints: Suppliers and contract manufacturers are relationship-dependent. Inventory obligations already in motion have some flexibility.

Tier 3 - Hard constraints: Payroll is technically flexible, but requires brutal conversations. Ad spend auto-shuts off if Meta doesn't get paid. 3PLs won't ship orders without payment.

Start with Tier 1. Only move to the harder constraints if the softer ones don't solve the problem.

Here's an example…

Let's say the forecast shows a problem for a client selling writing supplies. A $100,000 payment is due to their pen manufacturer this week. They've been working together for five years. But making that payment means the bank account hits zero.

Let’s go through the what if process.

Option 1: Push the payment two weeks

Call the supplier. "Hey, I need two more weeks on this payment. Everything's solid, just need a little breathing room."

Given the five years of history means something, the relationship has equity. More than likely, the response is "no problem."

This keeps $100K in the account for two more weeks. Qualitatively, it uses some relationship capital but probably doesn't damage anything long-term. The cash outflow moves from week 2 to week 4.

We all know this intuitively.

Option 2: Split the order

If the original order was for 100,000 pens, they could change it to 50,000 now and 50,000 in four weeks.

Same outcome eventually, but different cash outlay timing.

This reduces the immediate payment by $50K, though it might affect the supplier's production schedule and delay getting full inventory to market. The cash outflow changes from $100K in week 2 to $50K in week 2 and another $50K in week 6.

Option 3: Reduce scope

Let’s say that original order included 100,000 pens and 10,000 phone cables as a new SKU test.

They can just forget the cables and only order the hero product.

Maybe that $100K order drops to $80K. Qualitatively, this delays or cancels a product launch, but keeps the core business running. $80K goes out in week 2 instead of $100K.

Option 4: Renegotiate terms

Original terms were 50% deposit upfront, 50% on delivery.

What if it was 30% upfront instead?

Immediate savings of $20K. Might require giving something back—maybe slightly higher unit costs or longer lead times. Depends on the relationship and the supplier's flexibility. $30K goes out in week 2, then $70K in week 10 when delivery happens.

Each scenario has a quantitative impact with the dollar amount and a qualitative impact with relationships, reputation, and future flexibility. Plus, there is the specific timing of which week gets affected.

The goal is figuring out which combination of moves keeps the business running while preserving the most important relationships and options.

Leveraging opportunities

Same framework. Opposite direction.

When the forecast shows abundant cash, the question isn't "what can we cut" but "what should we do with this."

The first step is determining the minimum working capital. How much cash needs to stay in the system to keep operations running smoothly? Everything above that line becomes available for optimization.

Then it's the same what-if exercise. 

What if we pulled that product launch forward six months or hired in-house instead of staying fractional? What if we negotiated priority positioning with suppliers—paying 75% upfront instead of 50% in exchange for jumping the queue and cutting lead times in half?

Even something simple like pre-paying annual software subscriptions to get the 15% discount. Small move, but if cash is sitting there anyway, it’s probably worth it.

The decision-making process is identical to constraint thinking. Still asking "what if" for every option. Still evaluating impact and timing. Just optimizing for growth instead of survival.

The human element

The forecast shows the numbers. The decisions factor in everything the forecast can't see.

That five-year relationship with the pen supplier is invisible on a spreadsheet. But it's real leverage when asking for two more weeks on payment. A brand new supplier who doesn't know or trust the business yet? That's a completely different conversation with different options.

Personal constraints matter too. A founder buying a house next month needs to protect their credit score. An owner with 90% of their net worth tied up in the business has a different risk tolerance than someone diversified across multiple assets. Some clients live in $100,000 houses as multi-millionaires. Others buy airplanes. 

The human element drives these decisions as much as the numbers do, which is why AI won't replace this work. Too many inputs. Too much context that only exists in relationships and conversations.

But there's one constraint that applies universally: time.

The further out a problem or opportunity appears in the forecast, the more levers are available to pull. Seeing a cash deficit 90 days out means options like renegotiating supplier terms, adjusting purchasing strategy, or exploring financing before actually needing it. Three weeks out and the options narrow significantly. SBA loans take months. Building supplier relationships takes years.

This is why the forecast gets reviewed weekly, or at minimum monthly. Waiting until the problem is right in front eliminates most of the optionality.

The goal isn't perfection. It's informed optimization. We’re not trying to meet every obligation exactly as originally planned, but instead just trying to hit the cash target while preserving the most important relationships and opportunities.

What's next

Next week I'll walk through automation—what parts of this can be systematized, what parts should always stay human, and how to build this into a sustainable rhythm instead of a quarterly fire drill.

For now, if the forecast shows an upcoming problem, go through the constraint hierarchy. Ask "what if" for each one, then model the impact and timing.

If you ever want to bounce these what ifs by me, send me a note. Always happy to chat about this stuff.

— Sam

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