CFCX Work

Tag: NetSuite

  • Job Site Address Script for NetSuite (hypothetical)

    Job Site Address Script for NetSuite (hypothetical)

    The question is why this matters

    Project-based businesses often invoice from a corporate address while the work happens at dispersed job sites. The question is why that mismatch matters: tax calculations, shipping rules, and audit trails all depend on the actual work or delivery location. So what does this mean for teams using NetSuite? Without a consistent way to propagate a project’s job site address to invoices, tax accuracy and operational clarity suffer.

    This draft describes a hypothetical Job Site Address Script and associated customizations that automatically populate invoice shipping addresses from a project-specific job site record. Treat the design below as a systems-level blueprint — it is written as if the code exists, but remains intentionally hypothetical until you deploy and validate it in your environment.

    How the Job Site Address Script works

    The solution is organized into three script components and a small set of custom records/fields. At a high level the flow is:

    • User selects a Project on an Invoice.
    • Client script reads the Project’s linked Job Site Address and displays a formatted preview on the invoice form.
    • On save, a user event script writes the job site values into the Invoice shipping address subrecord so NetSuite’s native tax engine calculates tax by location.

    Script roles and responsibilities

    • User Event Script (Before Submit) — Sets invoice shipping address from the Project’s Job Site Address. Runs on create and edit so saved invoices always reflect the selected project.
    • Client Script (Page Init, Field Change) — Looks up the Project’s Job Site Address when the Project field changes and formats a preview into a display-only body field on the invoice.
    • Workflow Action Script — Invoked by a Project workflow to maintain bidirectional links between Job Site Address, Customer, and Project when the Project Address field changes.

    Required customizations (record and fields)

    At the core is a custom record type called “Job Site Address” (script ID: customrecord_cfcx_jobsiteaddress). It holds structured address elements and links to Customer and Project. Projects gain a lookup to that custom record and Invoices gain a display-only preview field.

    Key fields on Job Site Address

    • Attention, Addressee, Address Line 1/2, City, Zip — free-form text
    • State, Country — list/record links for consistent reference data
    • Customer, Project — list/record links for relationship maintenance

    Project and Invoice custom fields

    • Project: custentity_cfcx_projectaddress — lookup to Job Site Address
    • Invoice: custbody_cfcx_job_site_addr — long text preview of formatted address

    Deployment and execution notes

    Deploy the three scripts with clear execution contexts and conservative logging. Recommended deployments (hypothetical):

    • User Event Script: Execute as Administrator, Status=Testing, Log Level=Debug (then move to Released/Error in production)
    • Client Script: Status=Testing, Page Init + Field Change handlers
    • Workflow Action Script: Triggered by Job Site Address changes on the Project workflow

    Design decisions that matter

    • Write at save, preview at selection — Client script provides immediate visibility without modifying persisted data; user event applies authoritative change before submit so tax engine sees the shipping address.
    • Lightweight updates — When the user event script runs, it updates only the shipping address subrecord fields to minimize write scope and reduce row locking.
    • Non-blocking notifications — Use toast messages to inform users if a Project lacks a linked Job Site Address rather than preventing saves.

    Testing checklist and common scenarios

    Before moving this hypothetical solution to production, validate the following:

    • Create a Job Site Address with full address data and link it to a Project.
    • Create an Invoice, select the Project, and verify the preview field shows the correctly formatted address.
    • Save the Invoice and confirm the shipping address subrecord contains the job site values and taxes compute as expected.
    • Change the Project on an existing Invoice and verify the script replaces or clears the shipping address appropriately.
    • Test Projects with no Job Site Address to ensure the preview clears and a non-blocking notification appears.

    Troubleshooting and operational guidance

    If the address does not appear, first confirm the Project links to a Job Site Address and required fields are populated. For tax recalculation issues, verify NetSuite’s tax engine and tax code mappings for the country/state in question. Use the Script Execution Log to inspect runtime errors and confirm field script IDs match your instance.

    Common pitfalls

    • Mismatched field IDs between the script and account configuration — validate IDs in account before deployment.
    • Insufficient permissions — scripts running as Administrator mitigate this during testing; ensure service roles have appropriate access in production.
    • Formatting edge cases — strip leading punctuation and empty lines when building the preview to avoid ugly results in the long text display.

    Implementation patterns and variants

    This design is intentionally minimal: preview on the client, authoritative write on save, and a workflow action to keep relationships consistent. Variants include:

    • Auto-assigning a Project-level default shipping address for recurring billing scenarios.
    • Adding address validation (third-party or regex rules) before saving the Job Site Address record.
    • Exposing the address mapping in a report/dashboard for operations and tax teams.

    Ultimately, what this means in practice

    Ultimately, a Job Site Address Script like this removes a common source of tax and shipping error in project-centric invoicing. It gives invoice writers immediate visibility of the work location while ensuring NetSuite’s tax engine receives an authoritative shipping address at save time. The result is cleaner audit trails, fewer tax surprises, and lower operational friction.

    The takeaway is simple: treat the Job Site Address as first-class data tied to Project and Customer records, show it to users early, and write it authoritative at submit. Implement this pattern as a hypothesis, test in a sandbox, and iterate based on the edge cases your business surface.

  • How a Mass Delete Could Work in NetSuite

    How a Mass Delete Could Work in NetSuite

    Why a controlled mass-delete process matters

    The question is why we need a formal interface for deleting large numbers of NetSuite records. In practice, mass deletions are high-risk maintenance tasks: they touch many records, can cascade through dependencies, and are nearly impossible to reverse. So what does this mean for teams responsible for data hygiene and ERP stability? A controlled, auditable workflow reduces human error, enforces operational limits, and makes outcomes measurable.

    Everything below is presented as a hypothetical design for a “Mass Delete” capability. The description outlines how such a system could work — its components, controls, and patterns — so teams can evaluate and adapt the approach for their environments without immediate public deployment.

    How a Mass Delete could work

    At a high level, the system would provide a custom record used to declare deletion jobs, a lightweight UI to create and run those jobs, and a server-side worker to process the records safely. The workflow would be driven by a saved search (the selector), not by changing script parameters. This keeps the job declarative: the saved search defines the target set, the job record defines intent and safety options (e.g., dry-run), and an execution service enforces single-job concurrency and logging.

    Core components and responsibilities

    • Custom Deletion Job Record — captures Name, Saved Search ID, Dry-Run flag, Status, counts, execution log, and Initiator fields for auditability.
    • Suitelet Validator/Launcher — validates the request, checks for running jobs, enforces permissions, and triggers the Map/Reduce worker.
    • Map/Reduce Worker — loads the saved search in manageable batches, attempts deletions, and reports results back to the job record. This is where net-new batching and governance handling would live.
    • UI Helpers (UE/CS) — a User Event and Client Script pair add an “Execute Deletion Job” button on the record form and handle the client interaction to call the Suitelet.
    • Execution Log & Audit Trail — every run appends structured log entries to the job record (or attached file) with counts for Success / Failure / Dependency / Skipped and a link to the saved search for context.

    Safety and operational controls

    Design choices matter more than features when the operation is destructive. The following controls would be central:

    • Dry-Run Mode: simulate deletes and report what would be removed without performing any DML. Always recommended for initial runs.
    • One-Job-at-a-Time Enforcement: prevent concurrent deletion jobs to reduce contention and race conditions. The Suitelet can refuse to start if another job is active.
    • NetSuite-Safe Batching: delete in small batches that respect governance limits and lock windows. Batch sizes and yields should be tuned to environment SLA and governance calculations.
    • Dependency Detection: before deleting, the worker should check for child records or references and either delete dependencies automatically (if safe) or flag the row for manual review.
    • Permission Checks: only designated roles/permissions can create or execute job records. Deletion operations should require an elevated audit trail mapping to the initiator.
    • Automated Notifications: summary emails on completion or failure with links to logs and the job record.

    Implementation patterns and technical notes

    Several implementation patterns help make an operationally sound system:

    • Promise-based Error Handling: using modern SuiteScript (e.g., 2.1 style) simplifies retry logic, allows clean async work in Map/Reduce, and produces clearer logs.
    • Progressive Rollout: start with small saved searches (10–50 records) and increase volume after proven runs. Label test jobs clearly and require dry-run until approved.
    • Structured Execution Log: use JSON lines or a custom sublist to store per-record outcomes (id, action, error code). This makes post-mortem analysis and reconciliation tractable.
    • Governance-aware Yielding: the worker should check remaining governance and yield as needed rather than failing mid-batch.
    • Automatic Retry and Backoff: transient failures (timeouts, lock contention) should be retried with exponential backoff and a capped retry count.

    Example: a safe deletion scenario

    Imagine a team needs to remove a set of obsolete vendor bills. They would:

    1. Create a saved search that precisely targets bills flagged for archival.
    2. Create a Deletion Job record, mark it Dry-Run, and save.
    3. Click Execute on the job form. The Suitelet validates and launches the worker.
    4. The Map/Reduce loads the saved search, simulates deletes in batches, and writes a report listing candidate IDs and any dependency blockers.
    5. Review the report, clear dependency issues or adjust the saved search, then run the job without Dry-Run. Final logs include counts and a timestamped audit entry of the operator who initiated the run.

    Operational guidance and checklist

    • Always begin with Dry-Run and a small sample size.
    • Store job records indefinitely for audit and compliance needs.
    • Restrict execute rights to a small operations group and require change control for saved searches used in deletion jobs.
    • Keep a playbook for rollback, reconciliation, and stakeholder communication.

    Ultimately, how teams should use this idea

    Ultimately, a declarative, UI-driven mass-delete framework could reduce risk by moving destructive intent into records that are auditable, reviewable, and governed. It transforms an ad-hoc admin task into a process with clear controls: who requested the deletion, what the selection criteria were, and what the outcomes were.

    The takeaway is practical: if you need to purge data at scale, prioritize a design that enforces dry-run checks, single-job concurrency, structured logs, and dependency handling. Those patterns are the difference between a recoverable maintenance activity and a costly outage. Looking ahead, a staged pilot and clear permissions model would be the next pragmatic steps toward safe adoption.

  • Why Technical Design Documents Matter

    Why Technical Design Documents Matter

    Why TDDs matter — the question is why and what’s at stake

    The question is why clients should insist on Technical Design Documents (TDDs) before work begins. What’s at stake here is time, cost, system reliability and the ability to evolve a solution without rebuilding from scratch. First principles tell us that clarity up front reduces rework downstream; a TDD is the practical artifact that enforces that clarity.

    So what does this mean for clients? A TDD converts assumptions into decisions, unknowns into scoped risks, and vague requirements into a repeatable implementation plan. If a project starts without that conversion, the result is often scope creep, finger-pointing, or expensive late design changes.

    Why Technical Design Documents Matter

    A TDD serves three practical functions for client engagements: alignment, risk control, and operational continuity.

    Alignment

    A TDD is the contract of understanding between business stakeholders and delivery teams. It records accepted trade-offs, data models, integration points, and authorization flows. When stakeholders later question a design choice, the TDD is the single source that explains the why and the expected outcomes.

    Risk control

    Designs carry technical and delivery risk. A good TDD lists those risks, assigns mitigations, and sets acceptance criteria. That turns unknowns into project tasks rather than surprises discovered during user acceptance testing (UAT) or, worse, in production.

    Operational continuity

    Systems outlive individuals. When a client inherits a solution, the TDD is the operational memory: how interfaces behave, where configuration lives, and how to restore or change the system safely. Without it, maintenance requires reverse engineering.

    What a good TDD contains

    A concise, actionable TDD is not a speculative essay. It focuses on decisions and evidence. Use these sections as a practical template.

    • Scope and objectives: Business goals, in-scope/out-of-scope items, and acceptance criteria linked to measurable KPIs.
    • Context diagram: High-level systems map showing data flow and authoritative sources.
    • Interfaces and contracts: API endpoints, message formats, error handling, authentication, throughput expectations.
    • Data model and migrations: Key entities, authoritative fields, transformation rules, and an outline of migration strategy with rollback steps.
    • Process flows: Step-by-step sequence diagrams for primary use cases and failure modes.
    • Non-functional requirements: SLAs, performance targets, security controls, and compliance considerations.
    • Risk register and mitigations: Known unknowns, spike tasks, and decision triggers tied to timeline impacts.
    • Deployment and operational runbook: Release steps, monitoring signals, alert thresholds, and recovery procedures.
    • Acceptance tests: Concrete scenarios that verify behavior end-to-end.

    How to implement TDDs in client projects

    Implementing TDDs is a process change as much as a documentation practice. The goal is to make the TDD a working tool rather than a checkbox.

    Phase 1 — Plan and constrain

    Start with a short discovery (1–2 weeks) to capture constraints and showstoppers. Deliver a one-page intent document that becomes the backbone of the TDD. Constrain scope to what you can validate in the first increment.

    Phase 2 — Draft and validate

    Produce a concise draft TDD focused on decisions, not prose. Use diagrams and tables. Validate the draft in a workshop with stakeholders and engineers; record objections as decision backlog items. Each unresolved item should map to a spike with a hypothesis and timebox.

    Phase 3 — Lock and use

    Lock the document for the implementation phase with a clear change control process. Require that any deviation be recorded and reviewed. Make the TDD the entry point for developer onboarding, test-case authoring, and the runbook creation.

    Common implementation patterns and pitfalls

    Pattern: living artifact

    TDDs work best when treated as living artifacts — lightweight, versioned, and tied to the codebase or project tracker. Link the TDD to PRs and acceptance tests so changes are visible and traceable.

    Pitfall: over-documenting

    Too much detail wastes time and obscures decisions. Aim for the minimal content that allows a new engineer to implement and operate the solution. If a section isn’t needed for decision-making or operations, keep it out.

    Pitfall: late delivery

    Delivering the TDD after development starts defeats its purpose. Timebox the TDD work into the project cadence and make completion a milestone before broad implementation begins.

    Example: NetSuite integration TDD (brief)

    For a NetSuite integration, the TDD should identify canonical records, mapping rules for custom fields, error reconciliation strategy for asynchronous jobs, and the schedule for batch vs. real-time processing. It should include the exact SuiteScript or connector entry points, expected API quotas, and how to handle duplicate detection. Those specifics prevent common failures like mis-synced financials or broken automated postings.

    How to measure TDD effectiveness

    Track a few practical metrics: number of design-related change requests after TDD sign-off, defects traced to missing design decisions, and onboarding time for new engineers. Use these to refine the level of detail and the processes that produce the TDD.

    Ultimately, the TDD is not an academic exercise — it’s the instrument that converts planning into predictable delivery. It lowers cost by reducing rework, improves reliability by capturing failure modes, and preserves institutional knowledge.

    The takeaway for clients is simple: require a concise, decision-centered TDD as part of project governance. When you make the TDD a gate, projects start with shared assumptions, and delivery teams have a practical roadmap to implement, test, and operate the system.

  • Quiet Record / Building What Doesn’t Yet Exist

    Quiet Record / Building What Doesn’t Yet Exist

    Most work that matters doesn’t announce itself.
    It begins as a conversation — two people comparing notes, sketching possibilities between code and context, hoping something durable will form between them.

    Functional systems. Human pace. Quiet progress.

    Over the past two months, that’s what this has been.
    A steady rhythm of deliverables refined, retainers structured, and frameworks shaped not from templates but from intent.
    He writes code; I build systems that hold it.
    Between us, a business takes its first breaths — quietly, deliberately, one exchange at a time.

    There’s no headline moment in this kind of growth.
    Just the long arc of trust built through small completions —
    the right file name, the tested automation, the client who signs because what we presented worked. Some days it looks like progress. Other days, like patience.
    But in the aggregate, it becomes the shape of something real —
    a company capable of standing on its own.

    What I’ve learned again is that business development isn’t selling; it’s stewardship. It’s seeing potential before structure exists — and choosing to build anyway.

    This, then, is a quiet record of that work:
    the unseen hours, the alignment between developer and consultant, and the recognition that the foundation of every strong business is built in the spaces no one else sees.