CFCX Work

Category: Systems

  • 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.