Production traceability and batch-level stock in an industrial ERP

Context

An industrial company manages production, inventory, and logistics through an ERP distributed across several operational applications. The work must coexist with historical records and active legacy workflows.

Problem

The information required to reconstruct a batch journey was distributed across processes and records with different models. This made it difficult to connect inputs, production operations, and inventory movements in a verifiable way.

My responsibility

I turn the client’s high-level needs into functional and technical analysis, scope, iterations, data models, domain rules, full-stack implementation, and tests. I own the initiative and coordinate decisions with the responsible team.

Constraints

• Preserve historical records and processes that remain in use
• Coordinate rules across several applications and inventory locations
• Deliver through verifiable iterations without interrupting existing operations

Key decisions

• Split the initiative into iterations so changes could be integrated, validated, and corrected in smaller steps
• Model traceability through domain rules and transactional movements
• Extend the system additively to preserve compatibility with existing records
• Block an uncertain operation rather than persist data that would be difficult to correct

Implementation

• Added domain relationships and rules connecting production operations with batches and inventory movements
• Built full-stack workflows and preventive validations across the modules involved
• Organized integration in stages so each change could be verified before expanding its scope

Quality and safeguards

• Automated tests around new functionality and domain rules
• MySQL integration tests for persistence, inventory, and traceability
• Merge-request CI safeguards that validate changes before integration

Verified status and outcome

• Implemented and tested a verifiable foundation connecting batches, production operations, and inventory movements
• Part of the solution is implemented and validated in test environments
• Full activation and post-release operational impact have not yet been validated in production

Trade-offs and work in progress

• Incremental evolution lowers risk compared with a full rewrite
• Staged rollout prioritizes compatibility and validation over activation speed