Leading American Luxury Jewelry Retailer

A leading American luxury jewelry and specialty retailer — operating 300+ stores worldwide with over 2,500 frontline workers and 10,000+ active SKUs — faced a fundamental visibility problem in its casting and production facilities. Each SKU carried unique work instructions requiring precise control over variables like pour duration, temperature, and timing. Without a centralized system, workers learned procedures informally from colleagues, and each site maintained its own version of the work instructions. The result was batch-to-batch variation, inconsistent quality, and no reliable data to confirm whether best practices were actually being followed on the floor.

The company deployed Tulip's no-code manufacturing platform to digitize work instructions, time tracking, and data capture across its casting operations. Using Tulip's app library as a starting point, engineers configured apps within the same day — defining their own data structures to capture who performed each step, how long each step took, and how each batch was made. Tulip's version control feature ensured all sites pulled from a single authoritative work instruction, eliminating the informal knowledge drift that had plagued operations. IoT sensor integration and edge connectivity enabled real-time data collection directly from the production floor, replacing paper worksheets and manual logs without requiring a rigid, pre-defined MES data schema.

The deployment delivered an 18% productivity increase across the production workforce. Beyond the headline metric, the company gained complete process visibility it had never had before — including granular throughput data, step-level timing, and operator-level traceability for every batch. Key outcomes included:

• Standardized work instructions enforced consistently across multiple production sites
• Elimination of paper-based documentation and the data errors that came with it
• Real-time identification of bottlenecks previously hidden in informal workflows
• Error-proofed data capture enabling reliable industrial time studies
• Operator feedback loops built into iterative app development, driving adoption

• Visibility precedes improvement: The jeweler couldn't fix what it couldn't measure — digitizing data capture was the prerequisite to any productivity gain.
• Version control is a quality control tool: In high-SKU, multi-site operations, a single source of truth for work instructions directly reduces batch variation.
• Flexible data structures lower adoption barriers: Platforms that let engineers define what to track — rather than forcing a rigid schema — enable faster deployment and better fit.
• Build around operators, not systems: Involving frontline workers in iterative app design drove engagement and surfaced process improvements that management alone wouldn't have identified.
• Start narrow, expand fast: The team built and deployed functional apps in a single day, demonstrating that a quick start outperforms lengthy requirements-gathering cycles.