Real-Number Examples @ Mibowi Sayifi

Scenario 01

The Saturday Oversell: 8 candles, two platforms, one problem

You make soy candles. On a Saturday morning you have 8 units of your most popular scent in stock. Etsy shows 8. Shopify shows 8. You haven't updated either manually in a few days because you've been making more.

At 10:14am, an Etsy order comes in for 3. You see the notification on your phone. At 10:21am, a Shopify order comes in for 6. You don't see that one yet. At 10:47am, you sit down to update your quantities and realize what happened.

You've sold 9 candles. You have 8.

What this scenario illustrates

The 7-minute window between orders is not unusual. During high-traffic periods, like a weekend after you've shared a new product on social media, this kind of collision can happen multiple times a day. The root problem is that both platforms hold independent quantity records that you update manually. There is no shared source of truth.

The short-term answer is almost always to fulfill the smaller order, contact the customer who placed the larger order, and explain what happened. How you write that message matters. The long-term answer is a spreadsheet architecture that makes this kind of collision visible before you hit send on the second confirmation.

Starting inventory 8 units

Etsy order (10:14am) -3 units

Shopify order (10:21am) -6 units

Actual available -1 unit

A shared sheet with a single "available" cell that both platforms pull from (manually) would have shown the problem the moment the first order was recorded.

Scenario 02

The wholesale order that didn't fit: 24 units across two size variants

A purchase order form on a clipboard next to handmade ceramic mugs organized by size variant on a studio shelf, warm overhead lighting

A boutique contacts you about a wholesale order: 12 small and 12 large of your hand-stamped ceramic mugs. You have 18 small and 9 large in stock. Your Etsy shop shows 18 small and 9 large. Your Shopify store shows the same.

You want to take the wholesale order. You can fulfill the 12 small easily. The 12 large is a problem. You could offer 9 large now and 3 more in two weeks. Or you could decline the large and offer only small.

Here's the inventory part that gets complicated: you accept the partial order, 12 small and 9 large, and you need to immediately reduce your Etsy and Shopify quantities to reflect that these units are now committed. But "committed" is not a status either platform recognizes. They only know "available."

The committed inventory problem

When you accept a wholesale order, the units are gone even though you haven't shipped them yet. If you don't manually reduce your platform quantities the moment you accept the order, you risk selling them again through retail. A spreadsheet column called "committed" that subtracts from "available" before you update platforms is one way to handle this. It's not automatic, but it's visible.

Scenario 03

Forecasting November with only last year's October data

You launched your shop in January of last year. By October you had a full year of sales data, but only one Q4 behind you. Now you're trying to decide how much to make before November.

Your total sales in November last year were higher than any previous month. But you also ran out of your most popular item on November 18th and left orders unfulfilled. You don't know how many sales you lost because you can't see the orders that never happened.

This is a fundamental forecasting limitation. You know your floor (what you sold) but not your ceiling (what you could have sold). One year of data gives you a starting point, not a reliable trend.

A reasonable approach with limited data

Look at your November-to-October ratio from last year. That's your observed seasonal lift. Apply it to your current October pace, then add a buffer for items you ran out of early. The buffer size is a judgment call, not a formula. Consider your production capacity, your storage space, and your cash flow. The goal is not to predict perfectly. It's to make a defensible decision you can explain to yourself.

Also worth asking: which items sold out first last year? Those are your highest-priority items to overproduce. Which items had leftover stock in January? Those are the candidates to make less of. One year of data tells you this, even if it can't tell you exactly how much to make.

A handmade seller surrounded by product samples and a calendar on a wooden desk, planning production schedule with colored sticky notes

Spreadsheet Design

How we think about the shared inventory sheet

Tab: Master Stock

SKU or item name
Physical count (what you actually have)
Committed (wholesale orders accepted, not shipped)
Available (physical minus committed)
Etsy quantity (what the platform shows)
Shopify quantity (what the platform shows)
Last updated timestamp

The "available" column is the number you update platforms to match. The other columns explain why it's that number.

Tab: Order Log

Date and time of order
Platform (Etsy, Shopify, wholesale)
Item SKU and quantity
Status (pending, fulfilled, cancelled)
Notes field

This tab is your audit trail. When something goes wrong, you can trace exactly when each quantity change happened and why.

Tab: Seasonal Forecast

Prior year sales by month
Month-over-month change
Q4 lift ratio
Current year pace
Projected Q4 need
Production target

Keep this simple. The goal is a number you can act on, not a model you spend more time maintaining than using.

The solopreneur section goes deeper on building these systems alone.

When you're the only person managing inventory, the systems need to be simpler and more forgiving. We explore what that looks like in practice.

For Solopreneurs

Inventory systems designed for one-person operations across multiple platforms.

Questions? Reach out

Inventory math that actually reflects how makers work.