Case Study: Building Predictive Sales Forecasts for a Microbrand — A Maker's Guide
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Case Study: Building Predictive Sales Forecasts for a Microbrand — A Maker's Guide

SSofia Martins
2026-01-08
8 min read
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Step‑by‑step case study showing how a microbrand used sheets to forecast sales, choose microfactory runs and coordinate local fulfilment.

Case Study: Building Predictive Sales Forecasts for a Microbrand — A Maker's Guide

Hook: This hands‑on case study follows a microbrand that used spreadsheet forecasts to decide between a microfactory short‑run and a bulk overseas order. The choices they made reduced risk and improved margin.

Context

The brand sells limited runs of upcycled furniture and needed to decide if a November drop should be produced locally or abroad. Production choices affected lead time, cost and flexibility. They used a sheet as the single source of truth for forecasts, production options and fulfillment allocation.

Data inputs and assumptions

  • Historical drop velocities for similar SKUs.
  • Production lead times: microfactory 7–14 days, overseas 45–75 days.
  • Costs: unit cost, tooling, shipping and customs.
  • Fulfillment nodes: local micro‑hubs and postal partners.

Model and decision process

The sheet computed percentile demand forecasts and ran three scenarios: conservative, expected and aggressive. For each scenario it calculated cashflow, carry cost and unsold inventory risk. The team then compared the scenarios against the microfactory option — the logic draws on microfactory advantages described in How Microfactories Are Rewriting the Rules of Retail.

Outcome

The model revealed that a small local run, combined with a rapid reorder option, provided the best marginal outcome under uncertainty. They reserved a small tooling budget for a second microfactory run, which the model treated as an optional decision with its own expected value.

Operational integrations

To execute, they connected the sheet to local fulfillment nodes and predictive postage estimates, following the evolution of postal fulfillment playbooks (Evolution of Postal Fulfillment for Makers).

Lessons learned

  • Model uncertainty must be visible to merchandisers.
  • Short runs reduce downside but require flexible logistics.
  • Keep decision options in the sheet as toggles to communicate tradeoffs to non‑technical stakeholders.

Further resources

If you're a maker looking to replicate the process, check maker tool roundups and deal lists (Deal Roundup: Tools for Makers) and fulfillment strategies (Evolution of Postal Fulfillment).

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Related Topics

#makers#case-study#forecasting#production
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Sofia Martins

Clinical Educator

Senior editor and content strategist. Writing about technology, design, and the future of digital media. Follow along for deep dives into the industry's moving parts.

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