Optimizing Inventory & Catalog Management
US customer
Our client, a leading national provider of office equipment leases, had a sales team that needed a faster, more reliable way to design custom leasing packages. Their ability to do so was hampered by siloed data, making it a constant challenge to determine equipment compatibility and quote optimal, cost-effective solutions from a vast catalog of products
The purpose of this engagement was to design and build a centralized product configuration engine that would serve as the single source of truth for our client's sales operations. Our goal was to eliminate the inefficiencies caused by fragmented data by creating a platform that could not only unify complex product information but also understand the relationships between them. Ultimately, we aimed to provide the sales team with a powerful tool to quickly and accurately build optimal leasing solutions, backed by intelligent, data-driven recommendations.
a. Centralized Product & Data Management
b. Complex Relationship & Compatibility Modeling
c. Intelligent Sales & Configuration Tools
d. API-Driven Architecture & Interoperability
Our client's sales process was hindered by several key problems stemming from their fragmented data:
To bring this platform to life, our team needed to solve three core challenges that went far beyond typical software development. Each required a unique and modern approach.
a. The Data Integrity Challenge: Our biggest initial hurdle was the data itself. It wasn't just siloed in different places—it was inconsistent and often unstructured, with the same product having different names, specifications, or pricing across industry databases, legacy systems, and internal notes.
b. The "Compatibility Maze": Once we had clean data, we faced a complex architectural problem: how to model the thousands of intricate compatibility rules. A traditional database would have buckled under the weight of querying a "spider web" of relationships.
c. The Intelligent Search Problem: Finally, the goal wasn't just to store data, but to make it truly useful. The sales team needed to ask complex, human questions like, "What's a cost-effective replacement for this obsolete printer?" which a standard keyword search simply can't answer.
To overcome these challenges, we engineered a platform with three core components:
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