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What digital due diligence often gets wrong
It is easy to overvalue the front stage: ERP installed, polished dashboards, several AI licenses, or a convincing management narrative. None of that guarantees the operation is actually instrumented or that the data supports decisions under pressure.
Useful due diligence has to cut through that visible layer and read how the company works when nobody is presenting slides.
The framework's four layers
The framework structures the assessment into four layers: systems, process, data, and adoption. Only by reading all four together do you get a less decorative view of digital maturity.
- Systems: what tools exist and how they integrate.
- Process: where execution really lives and how much manual exception it absorbs.
- Data: quality, traceability, and usability of history.
- Adoption: who uses what, with what discipline, and how much key-person dependency remains.
The common gap between systems and process
A company can look digital because it has enough software and still run on manual handoffs, parallel spreadsheets, and off-system corrections. That gap is one of the biggest distortions in valuation.
When it exists, the technology thesis depends less on buying more tools and more on redesigning flows and ownership.
What questions uncover real risk
Useful questions are not 'do you have a CRM?' but 'how do you reconstruct an order with an incident?', 'what happens if the person who reconciles the close is absent?', or 'how long does it take to produce reliable evidence for an audit or committee?'.
Those questions move the discussion from narrative to mechanism.
How to use the data room checklist
The checklist should not become indiscriminate inventory. It should structure what to request so each layer can be validated with minimal noise: system maps, SOPs, report samples, logs, reconciliation evidence, and real ownership.
In private equity, speed matters. That is exactly why it is better to request less, but request what can actually change the thesis.
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