Data Governance & Quality
Automated pipeline quality gates, source-to-target lineage, and KPI controls so every team plans from one trusted number.
Life Sciences
In life sciences, a single unmapped specialty pharmacy code, duplicate 867 shipment record, or misapplied chargeback rule can throw off brand forecasts and gross-to-net accruals. We build automated validation and lineage controls across every feed.
What we factor in
- Multi-partner specialty pharmacy feeds
- Wholesaler 852 and 867 reconciliation
- Gross-to-net contract and rebate rules
- NDC, pack, and account hierarchies
- Audit-ready regulatory lineage
- Historical restatements and cleanups
In-pipeline quality gates
Automated freshness, completeness, and schema checks
Every specialty pharmacy, hub, and wholesaler feed passes through automated pre-load rules checking row counts, expected date ranges, NDC check digits, and partner file completeness before touching warehouse tables.
What it gives you: Block corrupted or partial partner submissions automatically before forecasts run.
Quarantine and exception routing
Hold bad records without halting the pipeline
Records with unmapped account IDs, negative quantities, or out-of-bounds pricing are routed to a dedicated quarantine table with automated alerts, allowing clean records to load on schedule while exceptions are resolved.
What it gives you: Keep S&OP timelines on track while maintaining 100% visibility into data anomalies.
Gross-to-net & revenue reconciliation
One number across commercial and finance
We codify the exact business rules connecting ex-factory shipments, wholesaler inventory changes, chargebacks, 340B, Medicaid, and commercial rebates so finance and brand planning query the exact same net definitions.
What it gives you: End executive review debates over why commercial and finance numbers differ.
Source-to-target data lineage
Field-level traceability from raw file to KPI
Every transformation from the raw SFTP drop file through de-identification, cohort aggregation, and the RoadMap GPS 360 forecast table is documented and tagged with batch IDs and timestamps.
What it gives you: Answer internal audit, compliance, and board questions with complete lineage back to the source file.
Master data and cross-walk governance
Prescriber, account, and payer master alignment
We maintain governed cross-walk tables linking DEA, NPI, HIN, and partner-specific account identifiers to a single canonical customer and territory hierarchy, with versioned effective dates when territories realign.
What it gives you: Prevent territory realignments or account ID changes from breaking historical trend lines.
Historical data cleansing for modeling
Outlier tagging, stockout imputation, and restatements
Before standing up a new demand model, we audit historical series for one-time channel buy-ins, supply allocation periods, and reporting gaps so statistical baselines learn from true demand rather than data artifacts.
What it gives you: Improve baseline forecast accuracy immediately by feeding the engine clean history.
Consumer Goods & Retail
When sales looks at gross shipments, marketing looks at syndicated POS, and supply chain looks at net orders in cases, S&OP meetings stall over whose spreadsheet is right. We govern the pipelines, hierarchies, and KPI rules so every team works from one number.
What we factor in
- POS vs. shipment reconciliation
- Cases, eaches, and currency conversions
- UPC, SKU, and pack transitions
- Retail banner and DC hierarchies
- Outlier and stockout history cleaning
- Role-based override governance
Automated POS & ERP validation
Pre-forecast pipeline quality controls
Pipelines automatically check incoming ERP shipments and NielsenIQ/Circana POS files for missing retail banners, duplicate invoice lines, unit-of-measure mismatches, and sudden volume spikes before triggering batch forecasts.
What it gives you: Trust that weekly baselines in RoadMap GPS and TrailBlazer ran on verified inputs.
Unified KPI & business glossary
Governed definitions for cases, dollars, and net demand
We establish and enforce one calculation for gross sales, net sales, trade spend, incremental promotional lift, and service level inside the warehouse so every dashboard and export reflects the same logic.
What it gives you: Eliminate conflicting spreadsheet formulas across sales, marketing, finance, and supply.
Product lifecycle & SKU chaining
Predecessor-to-successor mapping rules
When packaging updates, gram weights change, or a new UPC replaces an existing item, governed supersession tables stitch the historical demand series together cleanly without double-counting overlap weeks.
What it gives you: Preserve years of seasonal history when items transition to new SKU numbers.
Hierarchy & master data stewardship
Automated unmapped-item and customer alerts
Whenever a new SKU or ship-to customer appears in the ERP without a corresponding planning hierarchy assignment, the governance layer flags the steward immediately and assigns a default rule so nothing drops from totals.
What it gives you: Guarantee that SKU and account rollups always equal 100% of corporate totals.
History scrubbing & stockout adjustment
Distinguishing demand drops from supply shortages
Historical weeks where shipments fell due to warehouse stockouts or port delays are flagged and adjusted so statistical models do not repeat past supply failures as next year's seasonal trough.
What it gives you: Stop past stockouts from biasing future forecasts downward.
Change control & override audit trails
Timestamped accountability for every adjustment
Every master-data edit, business-rule update, and manual forecast override is logged with user ID, timestamp, reason code, and before/after values, supporting full Forecast Value Added (FVA) governance.
What it gives you: Know who changed the plan, when, and whether the change improved accuracy.
Quality control built directly into your data pipelines
Data quality cannot be an afterthought performed manually in Excel after a report looks wrong. RoadMap engineers automated quality control gates directly inside every ETL/ELT pipeline we build, inspecting data at four distinct checkpoints before it ever reaches a forecast model or executive dashboard:
| Quality Gate | What We Check Automatically | Action When an Issue Is Detected |
|---|---|---|
| 1. Arrival & File Integrity | SLA timeliness, file checksums, PGP signature verification, byte-size bounds, and expected row counts | Alerts the data engineering on-call rotation and triggers automated partner re-poll or retry |
| 2. Schema & Format Validation | Column names, data types, date formatting, required non-null keys, and primary-key uniqueness | Rejects malformed schema drifts in staging before production warehouse tables are touched |
| 3. Referential & Master Data Alignment | Every NDC, UPC, SKU, customer ship-to, and payer ID checked against governed master dimension tables | Routes unmapped codes to a steward exception queue while holding or mapping records per business rules |
| 4. Statistical & Business-Rule Plausibility | Period-over-period volume z-scores, unit-of-measure conversion bounds, negative inventory checks, and price-to-gross ratios | Flags statistical outliers for review so a one-time data spike does not corrupt baseline parameters |
From competing spreadsheets to one governed number
Technical validation is only half of data governance; the other half is organizational alignment. When commercial, supply chain, and finance teams each maintain their own offline hierarchy mappings and KPI formulas, leadership reviews spend more time reconciling spreadsheets than making decisions.
We work with your stakeholders to establish and codify:
- A single canonical hierarchy: Shared product, brand, customer, channel, and calendar dimensions stored in your cloud or on-premises warehouse and consumed directly by RoadMap GPS, RoadMap GPS 360, and TrailBlazer.
- Documented source-to-target lineage: Clear documentation showing exactly which ERP tables, CRM fields, and partner SFTP feeds populate each metric.
- Role-based ownership and sign-off: Defined workflows for who owns master data mappings, who can adjust forecast assumptions, and when each planning cycle locks.
Frequently asked questions
What is data governance & quality?
Data governance and quality establishes the automated validation rules, source-to-target lineage, and master data controls that make planning numbers trustworthy. RoadMap Technologies embeds quality checks directly inside your data pipelines, reconciles product and customer hierarchies, and standardizes KPI definitions so finance, commercial, and supply teams work from one governed source of truth.
How do automated quality gates protect our demand forecasts?
Quality gates inspect incoming ERP, CRM, and partner files in staging before batch forecasts run. By catching missing retail banners, unit-of-measure mismatches, unmapped NDC/SKU codes, and one-time data spikes upfront, they prevent bad inputs from distorting statistical baselines.
How do you handle unmapped SKUs or new customer accounts that appear in the ERP?
Our governance pipelines cross-check every incoming transaction against master dimension tables. New or unmapped items and ship-to accounts trigger an automated steward alert and apply a governed default rule so rollups always equal 100% of company totals.
What is source-to-target lineage and why does it matter for audits?
Source-to-target lineage tracks every metric on an executive dashboard or regulatory report back through each SQL or Python transformation to the exact raw SFTP file or ERP table, complete with batch IDs and timestamps.
Can you clean and restate historical data before we launch a new forecasting tool?
Yes. We audit historical series to chain superseded SKUs, impute or flag historical stockout periods, remove duplicate transactions, and align fiscal and 4-4-5 calendars so your forecasting engine starts with clean history.
Tell us about your data
We route you to the right data engineer, scope the work, and build with security in mind from the first conversation.