Where We Focus
The SIGNAL™ framework,
applied where it matters.
Not every engagement starts with a full enterprise diagnostic. Most start with a single domain where the data is already lying — and leadership knows it. We apply the same six-dimension framework to the specific business function that's bleeding value.
POS & Transactions
Point of Sale & Transaction Integrity
POS-to-ERP data reconciliation, omnichannel transaction accuracy, real-time vs. batch discrepancies that distort revenue reporting.
Sample Finding
"Online returns processed in-store were reconciling to a different GL account than store-origin returns. The $3.2M variance had been masked by a monthly manual adjustment for two years."
Recommendation
Unify return transaction taxonomy across POS and e-commerce OMS. Eliminate the manual journal entry by fixing the integration mapping at source.
Retail
Consumer Goods
Inventory & Assortment
Inventory & Assortment Accuracy
Inventory truth across channels, demand signal distortion, planogram-to-actual gaps, and the phantom stock that inflates availability metrics.
Sample Finding
"14% of SKUs showed 'in stock' in the inventory system but were physically absent from the shelf. Demand planning was forecasting against phantom availability."
Recommendation
Implement cycle count reconciliation triggers tied to POS velocity. Flag zero-movement SKUs with positive inventory for physical verification.
Retail
Consumer Goods
Manufacturing
Supply Chain
Supply Chain & Procurement
Supplier data quality, procurement-to-payment reconciliation, multi-tier visibility gaps, and the integration seams where spend data gets lost.
Sample Finding
"Three separate procurement systems were classifying the same supplier under different vendor IDs. Spend analysis was understating the relationship by 40%."
Recommendation
Consolidate vendor master across procurement platforms. Establish a single supplier identity layer with cross-reference mapping to all downstream systems.
Manufacturing
Consumer Goods
Life Sciences
Commercial & Marketing
Commercial & Marketing Intelligence
Campaign attribution integrity, customer data unification, marketing mix model reliability, and the gap between what the dashboard says and what actually drove the number.
Sample Finding
"Marketing attributed $18M in pipeline to a campaign series. Sales attributed $11M of the same pipeline to direct outreach. Both teams were reporting to the board as if the numbers were additive."
Recommendation
Implement a shared attribution model with agreed-upon rules for multi-touch credit. Reconcile marketing and sales pipeline weekly against a single source of record.
Retail
Consumer Goods
Life Sciences
Revenue & Finance
Revenue & Financial Close
Revenue recognition discrepancies, intercompany reconciliation, forecast-to-actual variance, and the multiple versions of the revenue number nobody will reconcile.
Sample Finding
"Finance, Sales, and Operations each reported a different Q3 revenue number. The delta was $7.4M. The gap lived in how each system handled channel partner credits and timing."
Recommendation
Establish a single revenue recognition event in the ERP as the system of record. Align CRM and ops reporting to pull from the same ledger posting, not their own calculations.
All Industries
Regulatory & Compliance
Regulatory & Compliance Data
Data lineage for audit, batch record integrity, adverse event reporting accuracy, and the compliance infrastructure that exists on paper but breaks under examination.
Sample Finding
"Batch records passed internal QA but the integration between the MES and ERP was dropping timestamp metadata. Under FDA audit, 23% of records could not demonstrate unbroken chain of custody."
Recommendation
Add integration-level validation for mandatory metadata fields. Implement automated reconciliation between MES and ERP batch records with exception alerting.
Life Sciences
Manufacturing
