Pre-acquisition AI-readiness diligence

Saoirse Manufacturing

Manufacturing · 610 employees · target under evaluation

Full assessment

690,000

Records analysed

4

Connected systems

2

AI blockers found

Capital at risk if acquired as-is: €1,742,411/yr - the data exposure the buyer inherits on day one, before the value-creation plan even starts.

The finding that lands

Counts computed from the data
NotableMicrosoft Dynamics ↔ SAP

2,799 customers exist as two different companies across Microsoft Dynamics and SAP.

€4,294,588 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.

Worth fixing before you scale AI: Any AI keyed on customer identity (pricing, churn, lifetime value, next-best-action) trains on a contradiction and ships confident, wrong answers.

HighMicrosoft Dynamics ↔ SAP

7,237 of 124,200 customers in Microsoft Dynamics have no matching record in SAP.

€4,294,588 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 ↔ Microsoft Dynamics

1,987 internal employees from BambooHR are sitting in the Microsoft Dynamics contact list.

1,987 records mislabelled as customers

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

ProceedM&A Due Diligence verdict

AI-ready target - the data supports the thesis.

Saoirse Manufacturing's data can support AI initiatives now, with light hardening.

How good is the data?

78/ 100 · B

Are they AI-ready?

Yes

Data supports AI initiatives today.

How long & how much?

3 weeks

€18K-€48K remediation

Conditions to proceed

  • Establish a shared customer key between SAP and Dynamics - 9% of accounts do not reconcile across the two.

Deal & price consideration

No data-driven price adjustment indicated. Allow €18K-€48K for hardening to protect the AI thesis.

Strengths: Accuracy, Completeness, Consistency, Governance already at an acceptable level.

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