Every failed ERP implementation has one thing in common: they migrated 20 years of bad data into a new system and expected different results. We cleanse, validate, and migrate master data with gates at every stage — so your new ERP starts with data you can trust. Detroit is the birthplace of American automotive manufacturing. Operations like Ford, GM, Stellantis run on complex ERP environments — often on Plex, Epicor, SAP — where implementations frequently go over budget or under-deliver because scope is defined by modules, not operations. Detroit-area Automotive, Aerospace & Defense, Robotics & Automation businesses are choosing Odoo for its flexibility, and choosing Metrotechs to govern the implementation so it fits the actual operation.
The difference between a successful Odoo implementation and a failed one in Detroit is almost always the same: operational mapping before configuration. Businesses that define data contracts and workflow boundaries first go live on schedule. Those that start with modules almost never do.
Inventory every data domain — items, BOMs, customers, vendors, pricing, inventory, open orders — and profile quality: completeness, consistency, duplicates, and accuracy rates. You know exactly what you're working with before migration starts.
Deduplicate records, standardize naming conventions, fill attribute gaps, and resolve conflicts. Item masters, customer masters, and vendor masters cleaned to >95% accuracy before migration.
Map source fields to target ERP fields with transformation rules for format changes, unit conversions, code translations, and hierarchical restructuring. Every mapping is documented and reversible.
Staged migration with validation checkpoints — record counts, field-level accuracy checks, referential integrity, and business rule validation. Data does not advance to the next stage until it passes.
Multiple trial migrations into the target ERP with comparison reports against source data. Each trial identifies issues that are fixed before the final cutover migration.
Establish ownership, update procedures, and quality monitoring for each data domain. Without governance, data quality degrades to pre-migration levels within 90 days of go-live.
Extract data from all source systems and profile every domain for quality, volume, and complexity. Deliver a data readiness report with specific remediation tasks.
Execute cleansing rules — deduplication, standardization, enrichment, and conflict resolution — with business stakeholder sign-off on merge and purge decisions.
Build the mapping specifications and transformation scripts from source to target. Review with ERP configuration team to ensure alignment with module setup.
Run iterative trial migrations with detailed reconciliation reports. Fix issues, rerun, validate. Repeat until accuracy targets are met consistently.
Execute the final production migration with pre-validated scripts and post-migration verification. Reconcile every domain before signing off.
ERP Data Migration & Cleansing for Detroit automotive operations - configured around local workflows, data ownership, and implementation governance.
ERP Data Migration & Cleansing for Detroit aerospace & defense operations - configured around local workflows, data ownership, and implementation governance.
ERP Data Migration & Cleansing for Detroit robotics & automation operations - configured around local workflows, data ownership, and implementation governance.
ERP Data Migration & Cleansing for Detroit steel & metals operations - configured around local workflows, data ownership, and implementation governance.
ERP Data Migration & Cleansing for Detroit financial services operations - configured around local workflows, data ownership, and implementation governance.
ERP Data Migration & Cleansing for Detroit healthcare & medical operations - configured around local workflows, data ownership, and implementation governance.
Data cleansing and migration typically takes 6–12 weeks depending on data volume, source system count, and quality state. This runs in parallel with ERP configuration, not sequentially. Rushing it is the single biggest risk to your go-live date.
Yes. We extract from AS/400, DB2, flat files, Access databases, Excel workbooks, and any system that can export data. Legacy systems often have the most data quality issues, which is why cleansing is critical.
Minimum 95% accuracy on master data (items, customers, vendors) for a successful go-live. Inventory accuracy should be >97%. We measure accuracy at each stage and don't proceed until thresholds are met.
Your business stakeholders make merge, purge, and standardization decisions — not the IT team and not us. We facilitate the process, provide recommendations, and execute the approved changes. Business ownership is non-negotiable.
ERP projects fail more often than they succeed. Not because the software is bad, but because the selection and implementation process is vendor-led instead of operations-led. Here's what good looks like before you sign anything.
Odoo covers most manufacturing operations natively. But every operation has workflows where the standard modules fall short. We map your BOMs, pricing logic, warehouse complexity, and dealer channels against Odoo's capabilities — so you go into implementation with a realistic scope, not surprises at month three.
Odoo doesn't run in isolation. It connects to WMS, CRM, M2B Commerce, EDI, shipping, banking, and legacy systems — all hosted and managed on AWS. Without governed integration architecture, those connections become a fragile web of point-to-point scripts that break every time something changes.
Odoo covers most manufacturing operations without a line of custom code. But when your workflows genuinely require it, we build Python custom modules — documented, tested, and upgrade-safe. We don't bolt code onto standard modules. We extend Odoo the right way.
ERP go-live is the highest-risk moment in the entire implementation. Orders are in flight, inventory is moving, and you're switching the system that governs all of it. We structure the cutover with rollback plans, validation gates, and hypercare support so your operation doesn't skip a beat.
Go-live is not the finish line — it's where the real optimization begins. Edge cases surface, users discover workarounds, and the configuration that worked in testing meets production reality. We monitor, tune, and optimize your ERP through the first 90 days and beyond so performance improves, not degrades.
The scariest moment in any migration is the cutover. We eliminate that fear by running old and new systems in parallel with automated reconciliation -- you switch over only when the new system has proven it produces the same results as the old one.
Big-bang migrations fail because they try to replace everything simultaneously. We decompose your legacy system into modules and replace them one at a time -- each phase is self-contained, tested, and reversible. Your operation never stops.
Most Odoo projects start with modules. Ours start with operational mapping. We define data contracts, integration boundaries, and go-live governance before a single module is configured.
When standard Odoo modules don't fit your manufacturing workflows, we build custom modules that extend Odoo without creating upgrade-blocking technical debt. Every custom module follows Odoo's ORM patterns and is designed to survive version upgrades.
Standard Odoo covers 80% of manufacturing needs. We close the remaining 20% with targeted customizations — module configuration, workflow adjustments, custom fields, and UI tailoring — without creating technical debt.
Odoo is rarely the only system on your floor. We integrate it with your WMS, CRM, e-commerce platform, EDI partners, shipping carriers, and legacy systems — governed by data contracts that prevent sync failures and data drift.
Metrotechs starts with the operating questions: which records are trusted, which workflows are manual, which systems own each decision, and where AI can safely improve throughput.
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