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. Los Angeles is the largest manufacturing metro in the U.S. with unmatched aerospace and consumer goods production. Operations like Northrop Grumman, Boeing, Raytheon run on complex ERP environments — often on SAP, Oracle, Epicor — where implementations frequently go over budget or under-deliver because scope is defined by modules, not operations. Los Angeles-area Aerospace & Defense, Food & Beverage, Textiles & Apparel 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 Los Angeles 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.
Both systems process the same transactions simultaneously. Orders, invoices, inventory movements, and financial postings run through old and new in parallel.
Automated comparison of outputs -- order totals, inventory balances, financial summaries, and report data. Discrepancies flagged immediately for investigation.
Detailed reports on every discrepancy between old and new systems. Root cause analysis for each exception -- is it a bug, a data issue, or a business rule difference?
Predefined, measurable criteria for when to cut over -- reconciliation accuracy threshold, exception count, and processing time. No subjective judgment calls.
Option to transition user groups or business units incrementally. Start with a pilot group before cutting over the entire organization.
Legacy system remains fully operational throughout parallel running. If the new system isn\'t ready, you continue on legacy with no disruption.
Define which processes run in parallel, how long, and what success looks like. Identify the reconciliation points and acceptable variance thresholds.
Build automated reconciliation scripts that compare outputs between old and new systems. Define exception categories and escalation procedures.
Run both systems in parallel for the defined period. Monitor reconciliation results daily and investigate exceptions.
Diagnose and fix discrepancies -- configuration adjustments, data corrections, or code fixes in the new system.
When reconciliation meets the defined criteria, execute the cutover. Keep legacy in read-only mode for the defined safety period.
Parallel Running for Los Angeles aerospace & defense operations - configured around local workflows, data ownership, and implementation governance.
Parallel Running for Los Angeles food & beverage operations - configured around local workflows, data ownership, and implementation governance.
Parallel Running for Los Angeles textiles & apparel operations - configured around local workflows, data ownership, and implementation governance.
Parallel Running for Los Angeles electronics operations - configured around local workflows, data ownership, and implementation governance.
Parallel Running for Los Angeles technology & software operations - configured around local workflows, data ownership, and implementation governance.
Parallel Running for Los Angeles financial services operations - configured around local workflows, data ownership, and implementation governance.
Typically 2-4 weeks for transactional processes and one full month-end close cycle for financial processes. The duration depends on transaction volume and complexity -- you need enough data to be statistically confident.
We minimize user burden by automating data entry into both systems where possible. For processes that require manual input in both, we limit parallel running to critical processes and use a phased approach.
We target 99.9%+ for financial data and 99.5%+ for operational data. The remaining variances should be explained and documented -- timing differences, rounding, or known configuration differences.
That\'s the whole point of parallel running -- finding issues before cutover. We diagnose every discrepancy and fix the root cause. If systemic issues emerge, we extend parallel running until they\'re resolved. You never cut over until you\'re confident.
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.
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.
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.
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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