The data underneath is not ready
Every project stalls on the same thing: the data is in several systems, nobody owns it, and none of it agrees.
What is actually going on
Analytics and AI both sit on a layer that was never built deliberately. Systems were bought by different departments at different times and none were designed to agree. Consolidation is rarely the answer on its own. Integration plus a modelled layer is, because the systems can stay where they are if one trustworthy view sits above them.
Who usually owns this
CIO, Head of data, CRO
How people describe it
- "combine data from multiple business systems"
- "single source of truth for business reporting"
- "detect broken data pipelines before reports update"
What resolves it
- Data Foundation. Fix your data layer before your dashboards or AI models. We build semantic models, certified metric definitions, and data quality frameworks.
- Data Strategy Consulting. Data strategy consulting that produces a sequenced, costed plan tied to decisions the business cannot make today, not a maturity score and a three year roadmap.
- Data Analytics Consulting. Senior-led data analytics consulting: metric certification, semantic modeling, and BI builds in Tableau and Power BI. One trusted number for every team.
- Data Engineering Consulting. Data engineering consultants who build ingestion, modeling, and orchestration that reconciles to source, alerts on failure, and is handed over with runbooks.
- Microsoft Fabric Consulting Services. Microsoft Fabric consulting: F-sku capacity sizing, OneLake architecture, Synapse to Fabric migration, Power BI Copilot enablement, governance-first rollout.
- Snowflake Consulting. Expert Snowflake consulting for semantic layer design, warehouse cost optimization, and BI migration. Senior-led engagements with defined milestones.
- Real-Time Data Observability. Autonomous monitoring for your data pipelines and tables: freshness, volume, schema, and distribution checks that catch issues before they reach a report or AI model.
- Data 360 Consultant. Data 360 consulting for unified customer profile architecture. Salesforce Data Cloud, Adobe RT CDP, Tealium, warehouse native CDPs, and governance.
- Self-Serve Data Portals Consulting. We design governed self-serve data portals so non-technical users get trustworthy answers without filing a ticket. Built on certified metrics and access controls.
- Data Stack Consolidation Consulting. Data stack consolidation that pays for itself. We audit your analytics tools, retire the redundant ones, cut monthly licensing spend, and prevent future sprawl.
- SAP Data Readiness & Migration. SAP data readiness and migration for ECC to S/4HANA. We assess, blueprint, clean, and migrate your data with reconciliation you can prove. Built for the mid-market.
Read up on it first
- Why Acquired Companies Cannot Report Comparably. Start here. Six things an acquired entity does differently, and not one of them is an error. Only 27% of limited-success acquirers are very confident their reported synergies are real and auditable, against 62% of successful ones. The gap is not deal quality. It is whether the reporting was built to be checked.
- Centralize Reporting or Standardize ERPs First?. Choosing an approach. In seven consolidation engagements the source systems were kept in every one and the comparable layer was built above them. Four conditions that really do force the ERP work first, four arguments that look like conditions and are not, and why federating ownership beat centralising it.
- What to Include in a Multi-ERP Reporting Scope. Scoping the work. Six mapping artifacts, each with a named signer, and they are the actual deliverable. A scope that names a platform and not these six is a platform project. Plus the eight acceptance criteria, the residual run cost that landed near a quarter of the prior cost in three engagements, and what to ask before signing.
Proof
Four core banking systems into one platform
We launched the unified member platform in week 20, cutting annual data costs from $1.3 million to $310,000. We enabled same-day cross-system member analytics, which improved decision-making speed. Six weeks after launch, the board approved the next acquisition, directly referencing the unified member view as a critical factor.
- $1.3M, Annual data cost savings.
- 4 to 1, Core banking systems unified.
- 3 days to same-day, Member analytics availability.
- 20 wks, Full platform delivery.
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.