DemoPortfolioMeridian Supply Co

Assessment · 6 November 2026

The Truth Score

Can the data be trusted? · Meridian Supply Co

52 / 100
Band C · Significant Work Needed

Core data capabilities in place but significant work is needed. Targeted remediation required before AI adoption (Band C).

Leverability

What can the data actually run?

0
Deploy now
5
Needs work
1
Blocked
BlockedPricing optimisationConnectivity (34)
Needs workLead scoring / next-best-actionCompleteness (58)
Needs workDemand & sales forecastingConsistency (54)
Needs workChurn predictionConnectivity (34)
Needs workKnowledge / document AI (RAG)Provenance & Origin Coverage (44)
€1,783,420/yrmodelled cost of inaction, roughly €5,350,260 of value drag over a typical three-year hold if the gating data gaps go unaddressed.

The finding that lands

Counts computed from the data
CriticalPipedrive ↔ SAP

4,308 customers exist as two different companies across Pipedrive and SAP.

€5,318,520 of revenue can't be reconciled

The same account is recorded under different names, IDs or addresses in each system. Each one is clean in isolation, so every single-system audit passes them.

Broken for AI: Any AI keyed on customer identity (pricing, churn, lifetime value, next-best-action) trains on a contradiction and ships confident, wrong answers.

CriticalPipedrive ↔ SAP

10,370 of 50,400 customers in Pipedrive have no matching record in SAP.

€5,318,520 of revenue sits in a cross-system blind spot

Forecasting and revenue AI can only see half the picture, so projections are built on a partial book.

NotableBambooHR ↔ Pipedrive

1,814 internal employees from BambooHR are sitting in the Pipedrive contact list.

1,814 records mislabelled as customers

Segmentation, scoring and outreach AI treat employees as prospects, polluting every model trained on the list.

Use Case Readiness

Whether the data can run each standard AI use case, and the gap to close.

0 of 6 relevant use cases ready · tuned to Distribution

Are you ready for the tools you're evaluating?

0 of 8 ready on today's data

Name the AI tools on your shortlist and we score whether your data can actually feed each one. Independent by design: we sell none of them. Tools marked External data depend on inputs we do not read (call recordings, web or intent events), so we score the structured prerequisites and say so.

ToolVerdictFix first
HubSpot AI Predictive Lead Scoring and Breeze
CRM / Predictive Lead Scoring
ConditionalClose the flagged data gaps first
Celonis
Process Mining and Execution Management
ConditionalClose the flagged data gaps first
Clari
Revenue Intelligence
Not readyClose the flagged data gaps first
Gainsight
Customer Success / Health Scoring
Not readyClose the flagged data gaps first
MadKudu
Predictive Lead Scoring
Not readyClose the flagged data gaps first
Sift
Digital Trust and Fraud Prevention
Not readyClose the flagged data gaps first
Gong
Conversation Intelligence / Revenue Intelligence
Not readyConnect Core input is recorded and transcribed sales calls, meetings and emails, captured through telephony/video/email integrations, not from any CRM/ERP/HRIS export DataTruth reads
6sense
ABM / Predictive Intent
Not readyConnect Core signal is third-party intent and anonymous web behaviour from the 6sense Signalverse, plus a website tracking tag, none of which appears in a CRM/ERP export

In a live assessment these verdicts are measured from the company's own systems, across 30+ tools including the ones on your list.

What it costs to wait

Conservative estimate, built line by line from observed data

Capital at risk, this year (estimate)

€1.3-2.4M

The assessment is €20,000. The single largest line alone is worth €1,170,074. This is insurance, not a report.

How we get to this number

Revenue leakage from unreconciled systems

€1,170,074

Observed: €5,318,520 of revenue across 10,370 accounts has no match between Pipedrive and SAP

Rate: x 22% leakage (collection slippage, attribution loss, double-billing), the low end of the 20-35% range

AI initiative at risk of stalling

€406,080

Observed: Truth Score 52 (Band C), 48 points below AI-ready

Rate: x 1.8% of revenue, scaled by the readiness gap (most stalled GenAI fails first on data quality)

Wasted spend on duplicate / contaminated records

€105,026

Observed: ~7% of 50,400 contacts are duplicates or internal records

Rate: x €7.40 cost-per-contact x 4 touch cycles a year

Manual reconciliation & rework

€80,640

Observed: 32-point accuracy gap across 280,000 records

Rate: x ~€0.90 per record of analyst time stitching systems by hand

Governance & compliance exposure

€21,600

Observed: 36-point governance gap: ownership, lineage and audit trail

Rate: data-governance & audit-trail readiness for AI regulation, capped conservatively at €60K

Every rate is deliberately conservative and yours to change. Dial them to your own numbers and the total moves with you. The point is the observed finding, not the decimal.

The findings above are observed facts in the data. The euro figures are modelled estimates from those facts. On a real engagement every number is computed from your actual records, with the working shown. Demo figures are illustrative.

The evidence behind the verdict

Six-pillar breakdown

Click a pillar to open the engine

How it compares

Positioned on the Distribution reference model - a calibrated cross-sector baseline. Live peer benchmarking activates as real assessments accumulate.

Top 42%

+3 vs reference median

P25 · 40median 49P75 · 58
this company · 52

Pillars vs sector median

Accuracy
Top 19%+15 vs 53
Completeness
Top 32%+8 vs 50
Governance
Top 24%+12 vs 52
Consistency
Top 38%+5 vs 49
Connectivity
32nd percentile-8 vs 42
Provenance & Origin Coverage
Top 48%+1 vs 43

Continuous monitoring

Every snapshot retained since onboarding · trend, not just point-in-time

▼ 11 pts - €86K of annual data-risk re-opened

63 → 52

JanJun (now)

What moved over the period

Accuracy73→68-5
Completeness63→58-5
Governance72→64-8
Consistency58→54-4
Connectivity39→34-5
Provenance & Origin Coverage49→44-5

Truth Score fell 11 points over the last two quarters - monitoring flagged the regression for review.

The roadmap: what to fix first

1

Resolve cross-system identity: 1,240 customers are recorded as one city in Pipedrive and another in SAP - clean in both, broken for AI.

connectivityEffort: High8-12 weeks
Work the fix list and re-score

Board-ready deliverable

Download a sample IC board pack built from this assessment.

Buying this company? See the M&A diligence verdict

Proceed, fix, or walk, with the time-to-AI-ready and remediation cost, the buyer's view of Meridian Supply Co.

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