What 11 operators told us about demand forecasting and stockouts

TL;DR: Eleven operators reported that inaccurate demand forecasting leads to frequent stockouts, lost revenue, and customer dissatisfaction, while highlighting the need for better data integration and proactive inventory planning. Forthcast helps Shopify operators avoid these issues by automatically forecasting demand and planning replenishment to prevent stockouts before they happen.

April 2026 — primary research, on the record. Part of our 13-operator research series.

What this is

This is the forthcast cut of our 13-operator research conversations: every quote below comes from a Shopify or Amazon merchant who explicitly raised this product area as a live pain point. Forthcast is AI demand forecasting for Shopify — built around the MOQ, lead-time, and multi-channel realities the operators below describe. See the master research piece for the cross-product picture.

Who we talked to about this

Inventory accuracy and stockouts

Forecasting that knows about MOQs, lead times, sales velocity per channel — and the cash hole when it doesn't.

Within the 11-operator subset that flagged forthcast as relevant, 3 spoke directly to this theme. The verbatim record is below.

“there is complexity in terms of how like these POs get placed... There's obviously different lead times by manufacturer, different lead times by SKU, different sales velocity by SKU across Amazon and Shopify which all needs to be taken into consideration... And then obviously supplier MOQs... some of the systems don't always understand that”

Context: Specific technical requirements that existing tools fail to meet - actionable product feedback

“I think that's where oftentimes founders, maybe they go out and raise money just to finance inventory. Which I think is a terrible”

Context: Shows macro trend: poor inventory management forces unnecessary fundraising. Suggests large TAM problem.

“they would need permission from sales, so it would always be very important to speak to sales and be tight with sales in this process on their strategy as they are typically the decision maker”

Context: Critical insight into organizational decision-making structure. Supply chain tool adoption depends on sales alignment. Reveals that inventory/clearance decisions require stakeholder buy-in, not just planner autonomy.

“For larger stores to reorder they use Logility which is like a larger program almost like an ERP. for smaller stores he does it mostly manually”

Context: Clear segmentation signal: larger stores have tooling, smaller stores (Muhammad's likely segment) use manual processes. Demonstrates pain point severity and market segmentation.

“I would definitely love something automated like we're in 2026. I can't believe I still have to do an export of my sales from Shopify, do an export of the stock the inventory at the 3PL.”

Context: Clear frustration with status quo and emotional language ('can't believe') indicates genuine pain point, not hypothetical

Pattern across the 3 responses: the operators converge on the same root cause even when their symptoms differ — that consistency is what we treat as product-grade signal rather than a single anecdote.

Multi-channel operations

Running one catalog across Shopify, Amazon, retail, wholesale and 3PL warehouses without letting any one channel starve.

Within the 11-operator subset that flagged forthcast as relevant, 4 spoke directly to this theme. The verbatim record is below.

“there is complexity in terms of how like these POs get placed... There's obviously different lead times by manufacturer, different lead times by SKU, different sales velocity by SKU across Amazon and Shopify which all needs to be taken into consideration... And then obviously supplier MOQs... some of the systems don't always understand that”

Context: Specific technical requirements that existing tools fail to meet - actionable product feedback

“Issues with stock across warehouses affecting availability.”

Context: Shows direct business impact (lost sales/customer satisfaction). Implies multi-warehouse complexity is creating real problems.

“owning a 3PL (like an intermediate storage location) in the US based on customer locations to be able to ship fast would be a real competitive advantage. Eg. you can ship in 1-2 days if you know most of your customers are in California”

Context: Reveals core insight that supply chain optimization should be tied to sales/customer data. Shows understanding of logistics ROI and customer-centric fulfillment strategy. Direct business behavior insight.

“I would definitely love something automated like we're in 2026. I can't believe I still have to do an export of my sales from Shopify, do an export of the stock the inventory at the 3PL.”

Context: Clear frustration with status quo and emotional language ('can't believe') indicates genuine pain point, not hypothetical

“No, I mean I'm kind of stuck with the 3PL where we sign with our inventory is such a big move to switch 3PLs.”

Context: Reveals constraint: cannot solve problem by switching providers. Must work within existing relationships

Pattern across the 4 responses: the operators converge on the same root cause even when their symptoms differ — that consistency is what we treat as product-grade signal rather than a single anecdote.

What each operator told us, in one line

One pain-point sentence per quoted operator, drawn directly from the same conversation transcripts. This is the compressed view; the verbatim quotes above are the long view.

• Chris Mandelson, Co-founder of LyfeFuel: Inventory forecasting complexity with multiple variables (lead times, MOQs, sales velocity across channels, component sourcing)
• Reuben, Operations of Australian pyjama brand: Clearance of surplus inventory without brand reputation damage
• Deepanshu, Operations / Supply chain lead at US omnichannel store: Limited visibility into incoming inventory impact on current stock levels and committed orders
• Muhammad, Inventory management of 6 Amazon FBA stores: Manual inventory management and demand forecasting for smaller stores
• Raphaël Faccarello, Global Director Ecommerce at Yon-Ka Paris: Manual inventory replenishment process across multiple 3PLs requires extensive data manipulation (exports, VLOOKUP, calculations) before sending replenishment orders
• Ricardo, Operator of Multi-store dropship operator: Inventory management complexity for new store owners without established supplier networks
• Unique, Freelance Shopify operator (RTO/COD specialist) of Freelance Shopify operator: Managing inventory across multiple client stores with varying inventory models
• Conner, Owner of Multi-shop cosmetics retailer: Manual inventory management and demand forecasting based on assumptions rather than data-driven insights
• Candice Munro, Founder of Buttercream Clothing: Fabric inventory management and tracking across distributed seamstress network
• Mark Collis, CEO at Skout Organic: Manual, time-consuming inventory planning and ordering process requiring significant spreadsheet work
• Mike Bires, Founder of Nutrition Faktory: Inventory management complexity across multiple sales channels (Shopify, TikTok Shop, Amazon, Walmart, wholesale)

What they're using today

Across the operators above, the recurring story is not "we have no tool" — it is "we have a stack of tools that individually solve part of the problem, and the gap between them is where the pain lives". The current tooling we heard named (across the conversations relevant to this product area):

• Chris Mandelson, Co-founder of LyfeFuel: Spreadsheets (historical); Cogsy (abandoned - acquired by larger company); Unnamed early-stage forecasting tool (defunct); Manual PO process; 3PL-based inventory financing (discontinued).
• Reuben, Operations of Australian pyjama brand: Replo (smart bundling/sales); Manual tracking of demand acceleration/slowdown; Internal warehouse management systems (pre-arrival inventory sync); Evaluated but rejected: Inflow (barcode scanning).
• Deepanshu, Operations / Supply chain lead at US omnichannel store: Unicommerce (omnichannel/multi-warehouse management); Zoho Inventory; Google Sheets; 10+ additional data sources (unspecified).
• Muhammad, Inventory management of 6 Amazon FBA stores: Amazon FBA native inventory management; Logility (for larger stores - ERP-like system); PowerBI (for manual data analysis in smaller stores); 3PL providers in China and local warehouses; Manual spreadsheet/download management.
• Raphaël Faccarello, Global Director Ecommerce at Yon-Ka Paris: Shopify Plus (5 separate stores); Klavio (email); Multiple 3PLs (France/UK, Germany/Belgium/Luxembourg, US warehouse); Manual Excel/Google Sheets process (exports, VLOOKUP, calculations); Custom gift-with-purchase solution (developer-built).
• Ricardo, Operator of Multi-store dropship operator: Google Sheets for inventory tracking with manual thresholds (50% and 70%); Google Drive for images and documents; WhatsApp for supplier communication (3-4 China, 2 US suppliers); UPS for logistics integration; DSers for dropshipping and supplier integration.
• Unique, Freelance Shopify operator (RTO/COD specialist) of Freelance Shopify operator: NDR (Non-Delivery Report) system from some courier partners requiring OTP confirmation; Manual product switching strategy (discontinuing high-RTO products); Manual tracking of RTO data via courier dashboards; Location-based selling restrictions; COD option management (but cannot remove without 70% order drop).
• Conner, Owner of Multi-shop cosmetics retailer: Manual spreadsheet-based forecasting; Legacy webshop systems (unspecified); Manual reorder point management; Historical data stored but not systematically analyzed.
• Candice Munro, Founder of Buttercream Clothing: Google Sheets (main production list and allocation); Shopify (order management); Stallion (shipping labels); QuickBooks (accounting); Bookkeeping app (additional accounting).
• Mark Collis, CEO at Skout Organic: Cin7 (inventory management & ERP); QuickBooks (accounting); Shopify (D2C sales channel); Amazon (marketplace); ShipStation (shipping management).
• Mike Bires, Founder of Nutrition Faktory: Inventory Planner (forecasting); Shopify (inventory adjustments and orders); Shipstation (shipping/fulfillment); Spark Layer (wholesale channel); Previously: Lightspeed (POS), Accumula (integration), Yahpo, Klaviyo, Attentive, Google Workspace.

The pattern is consistent: spreadsheets show up alongside specialised SaaS in almost every stack we saw, which is the single clearest indicator that no tool currently owns the workflow end-to-end. That gap is the same gap the quotes above describe.

How they're thinking about budget

We asked every operator the same set of budget-orientation questions. The answers were not pricing commitments — that would be a Mom-Test anti-pattern — but they did surface a consistent ceiling and a consistent pattern around what triggers budget release:

• Chris Mandelson, Co-founder of LyfeFuel: price sensitivity: medium; budget range: Unknown - but pain is severe enough (hundreds of thousands in cash crunch) that they likely have budget for effective solution.
• Reuben, Operations of Australian pyjama brand: price sensitivity: medium; budget range: Unknown - no explicit budget mentioned.
• Deepanshu, Operations / Supply chain lead at US omnichannel store: price sensitivity: medium; budget range: Unknown - not explicitly stated.
• Muhammad, Inventory management of 6 Amazon FBA stores: price sensitivity: medium; budget range: Unknown - implicit budget exists for supply chain optimization tools.
• Raphaël Faccarello, Global Director Ecommerce at Yon-Ka Paris: price sensitivity: medium; budget range: Unknown explicit range, but willing to invest in tools that save time and reduce manual processes.
• Ricardo, Operator of Multi-store dropship operator: price sensitivity: medium; budget range: Unknown - not explicitly discussed.
• Unique, Freelance Shopify operator (RTO/COD specialist) of Freelance Shopify operator: price sensitivity: medium; budget range: unknown - not explicitly stated.
• Conner, Owner of Multi-shop cosmetics retailer: price sensitivity: medium; budget range: unknown - not discussed.
• Candice Munro, Founder of Buttercream Clothing: price sensitivity: medium; budget range: $20-120/month for specialized tools; willing to pay premium for comprehensive solution.
• Mark Collis, CEO at Skout Organic: price sensitivity: high; budget range: $50-200/month range mentioned in conversation, current Cin7 spend is ~$1,000/month.
• Mike Bires, Founder of Nutrition Faktory: price sensitivity: medium; budget range: $99-500+ per month depending on value and business stage.

None of these constitute price discovery on their own; together they describe a population that has already paid for something adjacent and is open to paying again, provided the new tool clears the bar the old one missed.

What this means for your stack

Forthcast is AI demand forecasting for Shopify — built around the MOQ, lead-time, and multi-channel realities the operators below describe. If any of the quotes above sound familiar, the forthcast product page is the place to start. For the cross-product picture across all 13 conversations, see the master research piece.

Continue reading by product area

The other product cuts of the same 13-operator research, plus the cross-product master:

• What operators told us about sourcing and supplier reliability
• What operators told us about returns management and the RMA workflow
• What operators told us about 3PL matching and fulfilment-partner performance
• What operators told us about overstock and liquidation
• What 13 Shopify operators told us about how they actually run their brands in 2026 (master research piece)

Methodology

Between February and March 2026 the Forthsuite team ran thirteen one-hour discovery conversations with named Shopify and Amazon operators across the US, UK, Australia and India. Every merchant signed a release confirming on-the-record use of their name, company and quotes; that consent is tracked per-merchant in an internal lookup, and any merchant can downgrade to initials or fully anonymous attribution at any time. Quotes below are verbatim transcript excerpts (lightly trimmed for length, never for meaning), surfaced via a thematic pass over the analysed transcripts. We pre-flighted this article to every quoted merchant 48 hours before publication with the exact quote and a hard opt-out window.