Customer Success

Home Improvement Retailer

Improving Multi-Echelon Network Decisions Under Demand Uncertainty

See how a leading home improvement retailer moved beyond static planning to test different scenarios, evaluate trade-offs, and better understand how its network would respond as conditions changed.

Industry Snapshot

Industry:
Retail (Home Improvement)

Vertical:
Consumer / Building Materials

Headquarters:
North America

Key Outcomes

Stronger decision-making
Clearer trade-offs
Greater confidence in long-term planning
Faster iteration
Better alignment between planning and execution

Company Overview

A leading home improvement retailer operates a highly complex, multi-echelon supply chain supporting store replenishment, direct-to-home fulfillment, reverse logistics, and specialized delivery for large building materials. Serving both DIY customers and professional contractors, the company must continuously balance service, cost, capacity, and long-term growth investments.

The Challenge

Long-term network decisions need to hold up over time, but the environment around them doesn’t stand still. Demand shifts, costs change, and disruptions are expected.

Traditional planning approaches made it difficult to understand how decisions would play out across the network. Static models and single-scenario plans couldn’t fully account for changing conditions.

The retailer needed a better way to:

Balance short-term operational needs with long-term investments
Plan for uncertainty across demand, cost, and growth scenarios
Evaluate trade-offs between space, labor, service, and capital investment
Understand how the network would respond as conditions changed

The Solution

The retailer partnered with GAINS to take a more flexible approach to planning.

Instead of building toward a single answer, the team focused on testing different scenarios and understanding how the network performs under a range of conditions. By exploring different demand, growth, and cost assumptions, they gained a clearer view of where decisions begin to change and what drives performance across the network.

Download the Full Case Study

Learn how a leading home improvement retailer used scenario planning and sensitivity analysis to better evaluate risk, test assumptions, and make more informed long-term supply chain decisions.