We cannot trust the numbers
Two teams report the same metric and get different answers, and no report settles it.
What is actually going on
The disagreement is upstream of the report. Both sides are computing a defensible figure from different rules, different grain, or different source systems, so building another dashboard adds a third version rather than resolving the first two. What settles it is one written definition per business concept, with an owner, enforced where the queries run.
Who usually owns this
CFO, Analytics director, CDO
How people describe it
- "why do sales and finance report different revenue"
- "standardize KPI definitions across departments"
- "remove duplicate customer records across systems"
What resolves it
- Semantic Layer Engineering Consulting. We build and certify the semantic layer that defines your metrics once so every tool and AI agent computes them the same way. Warehouse-native and governed.
- Master Data Management Consulting. Master data management consulting: identity resolution, golden records, survivorship, and stewardship. One trusted record of every customer, product, and supplier.
- Data Governance Consulting Services. Data governance consulting for metric certification, data catalog rollout, ownership models, lineage, and AI ready compliance. Senior led, fixed scope.
- Data Cleaning and Preparation Services. Profiling, deduplication, standardization and validation for the data your analytics and AI depend on, with rules that keep it clean after we leave.
- SAP Data Quality & Governance. SAP data quality and master data governance: deduplication, cleansing, and governance for customers, vendors, materials, and finance data, so your S/4HANA move starts clean.
Read up on it first
- Why Sales and Finance Report Different Revenue. Start here. Sales says $14.2M, finance says $12.8M, and both are right. The gap comes from five rules nobody wrote down: timing, grain, scope, adjustments and currency. Here is how to find which one is producing your number, and why a fourth dashboard makes it worse.
- Fix KPI Definitions or Rebuild Data Pipelines?. Choosing an approach. Both diagnoses look identical from the executive seat, and they cost different amounts by a factor of three. There is a half-day test that tells you which one you have, and most companies skip it and buy the expensive answer.
- What a Reconciliation Engagement Delivers. Scoping the work. Six artifacts, and if the proposal in front of you does not name all six it is a dashboard project with a reconciliation title. The deliverables, the acceptance criteria to write into the contract, the residual running cost, and what to ask before signing.
Proof
Five ARR definitions reduced to one certified figure
We identified and fixed a $2.1M discrepancy in ARR by standardizing all teams on one certified metric layer. This cut board reporting prep from three days to four hours. At the next board meeting, the CFO presented a single ARR figure backed by full data lineage. The metric layer also served as the core data source for the Series C data room.
- $2.1M, ARR discrepancy resolved.
- 3 days to 4 hours, Board reporting preparation time.
- 5 to 1, ARR definitions consolidated to single certified source.
- Series C, Metric layer used as data room foundation.
Getting it approved
Other problems
What is actually going on
Who usually owns this
How people describe it
What resolves it
Read up on it first
Getting it approved
Three pieces, in the order the question usually arrives. Each one is evidence-led and names its sources.
Whoever signs this off is asking a different question from the one you are asking.
is the worksheet for that conversation. Yours whether or not you hire us.