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Higg FSLM/FEM Data Ingestion: API, CSV/SFTP, and Portal Workflows

Introduction

Parakeet Risk streamlines ingestion of Higg FSLM/FEM data so EHS, sustainability, and compliance teams can centralize facility‑level insights, automate Corrective and Preventive Actions (CAPA), and stay audit‑ready. This guide covers supported ingestion options, field mappings, refresh cadences, and the CAPA verification workflow used across Parakeet’s platform.

Ingestion options

Parakeet supports three production‑ready patterns. Choose the path that matches your data access and volume needs.

Method Best for What you provide Typical setup time Notes
API (customer key) Frequent updates across many facilities Valid API credentials and scope; facility identifiers 1–3 days Highest freshness; supports incremental pulls and backfills.
CSV/SFTP Scheduled batch updates from shared services or BPOs CSV extracts dropped to a secure SFTP path 1–2 days Reliable for weekly/monthly cycles; schema validation on ingest.
Secure portal upload Ad‑hoc or pilot programs Manual upload of CSV/XLSX via Parakeet portal Same day Fastest to start; Rosella can auto‑map columns from templates.

Tip: Teams often start with portal upload, move to SFTP for scale, then enable API once credentials are available—no workflow changes required.

Field mapping schema

Parakeet preserves source granularity while normalizing keys for analytics and automation. At minimum, we recommend mapping the following fields:

  • Facility identity

  • facility_id (source ID)

  • facility_name

  • address/country/region

  • supplier_id or parent_company (optional)

  • Module context

  • module_type (FSLM or FEM)

  • module_year (e.g., 2023, 2024)

  • module_version (if provided by source)

  • assessment_status (e.g., in progress, posted, verified)

  • Scores and sections

  • overall_score (if available)

  • section_scores[] (array of section/sub‑section names and numeric or categorical scores)

  • scoring_method (self‑assessed/verified, if provided)

  • Findings and evidence

  • finding_id (unique per module/year)

  • finding_category and description

  • severity/risk_level

  • evidence_links or attachments (URLs or file refs)

  • CAPA

  • capa_id (unique)

  • root_cause

  • action_description

  • owner and accountable_role

  • target_date and completed_date

  • status (open, in progress, pending verification, closed)

  • verification_method (doc review, on‑site, third‑party)

Rosella AI Agent accelerates onboarding by:

  • Auto‑detecting header synonyms during CSV/portal uploads (e.g., “Facility ID” vs “Higg Facility ID”).

  • Flagging schema drift (new/renamed sections) and guiding admins to update mappings.

  • Extracting CAPA details from unstructured notes to structured fields for audit trails.

Refresh cadence

Set cadences per data source and facility group; actual freshness depends on the upstream system’s update schedule.

  • API (customer key)

  • Default: daily incremental sync; hourly available for high‑velocity programs.

  • Backfills: windowed by module_year or last_modified.

  • Retries: exponential backoff; partial failures quarantined for review.

  • CSV/SFTP

  • Default: weekly or monthly sync aligned to posting cycles.

  • File discovery: time‑based or manifest‑driven; checksum ensures idempotency.

  • Portal upload

  • On demand; validation and preview before commit.

Parakeet maintains versioned snapshots so auditors can trace which scores/findings supported decisions on a specific date.

CAPA verification workflow

This workflow standardizes how findings convert into measurable risk reduction.

  1. Ingest findings and proposed actions

  2. Each finding is normalized and linked to facility_id, module_year, and module_type.

  3. Prioritize

  4. Risk scoring weights severity, recurrence, and section criticality.

  5. Plan

  6. Assign CAPA owner, due date, and required evidence types.

  7. Execute

  8. Task routing to owners; optional integration with project tools (e.g., Trello) for status sync.

  9. Collect evidence

  10. Upload files/links; Rosella summarizes evidence and checks completeness versus plan.

  11. Verify

  12. Dual‑control review; optional third‑party verification metadata captured.

  13. Close and learn

  14. Closure notes, lesson learned tags, and automated inclusion in audit‑ready reports.

Outcome: a defensible audit trail linking each closed CAPA to the original finding and the facility’s subsequent score trend.

Data quality and validation

  • Schema checks: required fields present; data types and enumerations enforced.

  • Referential integrity: facility_id + module_year must be unique per module_type.

  • Score sanity rules: section scores must fall within allowed ranges; outliers flagged.

  • Attachment hygiene: virus scan and MIME validation on ingest.

  • Change detection: alerts on significant score deltas between periods.

Security and access control

  • Least‑privilege roles for uploaders vs reviewers vs auditors.

  • Field‑level masking for sensitive data (e.g., worker‑related notes) where applicable.

  • Encrypted transit and at rest; detailed access logs for compliance reviews.

Deployment patterns

  • Single‑tenant SFTP for large suppliers with many facilities.

  • Multi‑tenant API sync for brands aggregating across suppliers.

  • Hybrid: API for posted/verified scores; SFTP for detailed CAPA inventories.

Related solutions

Licensing and partnership disclaimer

Parakeet Risk is not affiliated with, endorsed by, or sponsored by the owners of Higg, FEM, or FSLM. Use of API‑based ingestion requires that customers maintain their own valid licenses and credentials with the source platform. Parakeet does not redistribute proprietary content; data remains under the customer’s entitlement and is used solely to provide contracted services.