A simple test: ask how many active customers you have, and count how many different answers come back. In most established companies the CRM says one thing, billing says another and a spreadsheet says a third. Nobody is wrong. The systems just never agreed.
I fix that at the source. I consolidate customer, order and revenue data into one central database that every system reads from and writes to, then build the reporting leadership needs on top of data that is actually consistent.
What you get
- A data inventory. Every place the business stores data, who owns it and where the copies disagree.
- One source of truth. A central database with reconciled records for customers, orders, subscriptions and revenue.
- Two-way sync. The CRM, billing and other systems kept consistent with the core automatically, not by export and import.
- Reporting leadership can use. Dashboards and exports built on the consolidated data, including accounting-ready reconciliation.
- Access control and audit logging. A record of who can see what, and who changed what.
- AI-ready groundwork. Clean, connected data that an AI project can be built on.
How the engagement runs
- Inventory. Map every data store and every spreadsheet that has quietly become a system.
- Reconcile. Decide which system is right for each kind of record, and resolve the conflicts.
- Consolidate. Build the central database and migrate the reconciled data into it.
- Connect. Wire the remaining systems to the core so they stay in sync.
- Report. Build the dashboards and exports on top, and retire the manual reports they replace.
Proof
At Epic Golf Club, member data lived in three places that never agreed: the WordPress database, the app's database and HubSpot. Staff could not answer who was an active member without cross-referencing spreadsheets. I unified the three into one central database, with HubSpot and Stripe in automatic two-way sync, so membership records, payment methods and subscriptions are consistent everywhere.
At Mr Target, data that had spread across the storefront, an internal app and Zoho CRM became one synchronized source of truth, with website and Amazon orders flowing through the same pipeline.
Frequently asked questions
Do we need a data warehouse?
Often not at first. Many companies need their operational systems to agree before they need a separate analytics layer. One well-designed central database, kept in sync with the tools around it, answers most reporting questions.
Why does this matter for AI?
AI is only as good as the data it can reach. If your systems disagree on the basic numbers, an AI tool will reflect that disagreement. How to Keep Your Business from Falling Behind in the AI Race explains why the data work comes first.
Can we keep the tools we already use?
Usually, yes. Consolidation does not mean replacing everything. At Epic Golf Club, HubSpot and Stripe stayed in place and now sync with the core automatically.
How do we know this is our problem?
Reports assembled by hand, duplicate data entry and numbers that differ between systems are the usual signs. The scorecard takes a few minutes and gives you a plain read.