HomeCompanyBlogenLogin
Book an intro call

Enabling integrated, intelligent and automated supply chain decisions

numi solutions GmbH
Chiemgaustr. 148
81549 Munich

Follow us on

Platform

  • Platform
  • AI Agents & Automation
  • All ERP integrations

Solutions

  • Retail, Wholesale & Brands
  • Industry & Manufacturing
  • Aftersales & Spare Parts Planning

Products

  • Forecasting
  • Inventory Optimization
  • Replenishment
  • Supplier Portal

Company

  • Company
  • Blog
  • Contact us

© 2026 numi solutions GmbH

  • Imprint
  • Privacy Policy
Loading...
Little John Bikes plans 70 stores with numi
Customer Success Stories15 Sep 2026

Little John Bikes plans 70 stores with numi

Little John Bikes uses numi to translate global demand forecasts into store-level assortment, inventory, and replenishment decisions across 70 locations.

Moritz Krol

Moritz Krol

Customer Success Stories

Contents
  1. One shared demand signal across 70 stores
  2. Making new models plannable from day one
  3. From assortment strategy to operational decisions
  4. Transparency from the entire network to each store
  5. Less manual coordination, better planning decisions

Contents

  1. One shared demand signal across 70 stores
  2. Making new models plannable from day one
  3. From assortment strategy to operational decisions
  4. Transparency from the entire network to each store
  5. Less manual coordination, better planning decisions

We are delighted to welcome Little John Bikes as a new numi customer. The modern bicycle retailer combines a nationwide store network with a broad range of bicycles, e-bikes, and accessories. Little John Bikes now uses numi to plan 70 stores on one shared, data-driven foundation.

Little John Bikes and numi launch their joint assortment and store planning solution

One shared demand signal across 70 stores

Planning a large store network comes with distinct challenges: not every item sells regularly at every location, regional demand varies, and each assortment has to reflect demand, available space, and in-store presentation requirements at the same time.

numi therefore starts by creating robust demand forecasts at the global item level. Expected demand is then distributed across individual stores using data-driven allocation logic. This keeps every local plan aligned with total expected network demand while still accounting for regional differences.

The joint project includes:

  • Global demand forecasts by item as a stable foundation for the entire store network.
  • Store-level forecasts and inventory targets that reflect local demand and available stock.
  • Rule-based assortment planning to manage assortment breadth, inventory depth, and display requirements by location.
  • NPI forecasting for new products and model generations, even when no product-specific sales history exists yet.
  • Hierarchical analysis of demand, purchasing, and inventory development across the global network or by brand, product group, item, and store.

Making new models plannable from day one

The bicycle industry introduces new models, variants, and model years on a regular basis. Purchasing and assortment decisions therefore often have to be made before reliable sales data for a new item is available.

numi addresses this challenge using demand patterns from comparable products, representative launch curves, like items, and seasonal profiles. As soon as the first actual demand becomes available, the forecast can be updated. New products can therefore be planned systematically from launch and adjusted in a controlled way as real demand develops.

From assortment strategy to operational decisions

Forecasts alone do not determine which items a store should carry or how many units should be stocked. numi connects its forecasts with the strategic guardrails of the assortment.

Product groups can be segmented by attributes such as brand, category, model family, or display type. Each segment can have its own rules for minimum and maximum breadth, local forecast thresholds, days of supply, and minimum quantities. The result is an explainable item selection for every location that can be translated directly into inventory and replenishment decisions.

Transparency from the entire network to each store

With Hierarchy Lookup, planning teams can analyse demand, forecasts, purchasing, and inventory from different perspectives. Developments can be reviewed across the complete network or for an individual brand, product group, or store.

This creates one shared view of the key planning questions: Where is demand developing? What inventory levels can be expected? Which items require attention? And how does local performance fit into the overall network picture?

Less manual coordination, better planning decisions

numi connects global forecasts, local demand, and strategic assortment rules in one continuous process. Planning information no longer has to be reconciled manually across separate reports. Decisions remain explainable and can be updated more quickly when new data becomes available or conditions change.

We would like to thank the entire Little John Bikes team for their trust and collaborative partnership. We look forward to continuing the development of assortment and store planning across 70 locations together.

Learn more about the methodology in our article Assortment Planning: How numi Plans Store Assortments.

Little John BikesCustomer Go-liveAssortment PlanningStore PlanningNPI ForecastingBicycle Retail

Continue reading

Altruan Goes Live with AI-Powered Supply Chain Intelligence
Customer Success Stories16 Jul 2026

Altruan Goes Live with AI-Powered Supply Chain Intelligence

Altruan now uses numi to bring AI-powered forecasting, automated replenishment and real-time supply chain visibility to more than 75,000 healthcare products.

Moritz Krol

Moritz Krol

AI in Procurement: How Karl Pichler AG Digitizes Timber Trade with numi
Customer Success Stories07 May 2026

AI in Procurement: How Karl Pichler AG Digitizes Timber Trade with numi

Karl Pichler AG uses AI in procurement and inventory optimization software from numi, with 19% better inventory turnover, automated forecasting and full procurement digitalization in timber and building materials trade.

Stefan Gaubatz

Stefan Gaubatz

AI in Recommerce: How refurbed Plans Supply and Demand with numi
Customer Success Stories09 Dec 2025

AI in Recommerce: How refurbed Plans Supply and Demand with numi

Refurbished electronics break the assumptions built into conventional planning systems. Here is how refurbed uses AI-powered demand forecasting, automated replenishment and supplier KPIs to plan a supply chain where both supply and demand are uncertain.

Stefan Gaubatz

Stefan Gaubatz

Want to make better decisions in your supply chain?

Talk to our team about your current processes and potential.

Talk to our team