Each engagement is scoped from a defined problem, delivered to a formal specification, and built to be maintained by whoever comes next.
Most ERP consultants scope loosely, build to vague requirements, and deliver something that functions but cannot be maintained or extended. iDev operates on a specification-driven model: requirements formalized before development begins, implementations source-controlled and CI/CD-deployed, every deliverable auditable and repeatable.
NetSuite's out-of-the-box capabilities have a ceiling. Crossing it requires custom development — and most NetSuite developers are not software engineers. They are administrators writing scripts. The result is fragile, undocumented customizations that accumulate as technical debt and eventually make the ERP harder to operate than the manual processes it replaced.
Organizations whose NetSuite customizations are brittle, undocumented, or built by administrators rather than engineers. Organizations preparing for a platform upgrade or audit where custom code must be defensible.
NetSuite implementations fail or underperform not because of bad execution, but because of bad architecture. Decisions made early — data model design, workflow structure, integration patterns — compound over time. A poorly architected system works fine at go-live and becomes increasingly expensive to operate and extend as the business scales.
Organizations planning a new NetSuite implementation. Organizations inheriting a prior implementation and assessing what can be salvaged vs. rebuilt. Organizations whose current instance no longer maps cleanly to how the business operates.
Enterprise operations run across multiple systems. When those systems don't communicate reliably, the gaps get filled by humans — manual data entry, spreadsheet transfers, email handoffs. This is operational friction that scales linearly with business growth. Integration failures also create data inconsistencies that erode confidence in reporting and decision-making.
Organizations running multiple enterprise systems that require data synchronization. Organizations migrating to NetSuite from a legacy ERP. Organizations where manual data processes are creating operational risk or bottlenecks.
Enterprise data lives in ERP systems. The decisions that depend on that data — inventory positioning, revenue forecasting, operational capacity — are often made from exports into spreadsheets, detached from the live system. As data volumes and business complexity grow, this approach fails. The gap between system data and decision-maker intelligence widens.
Organizations whose ERP data is rich but underutilized for decision-making. Organizations facing forecasting or planning problems that spreadsheet models can't handle at scale. Organizations that want a technical assessment of what AI can actually do for their operations.
Organizations often have internal NetSuite developers who are capable but working beyond their depth — facing an architectural decision they haven't made before, inheriting a codebase they don't understand, or implementing a pattern that carries hidden risks. The cost of getting this wrong is high and deferred — it shows up months later as a system that can no longer be changed without breaking something else.
Organizations with internal NetSuite development capacity that needs external review. Organizations preparing for a platform upgrade who need to understand the risk profile of their customizations. Internal teams blocked on a problem that needs a senior technical perspective.
Describe the problem. I'll assess the architectural approach and propose a scoped engagement.