The Challenge:
A regional golf and hospitality operator came to Liv Data in the aftermath of a failed systems migration. The platforms intended to run the business had instead left leadership with financial numbers they could no longer trust, and a finance function that was, in practical terms, broken.
The immediate priority was stopping the damage. The longer-term priority was getting the underlying systems working correctly so the problem wouldn’t recur.
How Liv Data Helped:
Liv Data addressed both problems in sequence: stabilize the books first, then fix the systems that had caused the instability.
Immediate Stabilization
- Took over full-cycle accounting operations, including bookkeeping, general ledger, accounts payable and receivable, month-end close, and management reporting with real variance commentary rather than raw figures
- Cleaned up the records left behind by the failed migration, reconstructing a reliable financial picture
Systems Migration
- Planned and executed a structured migration from QuickBooks Desktop to QuickBooks Online on an eight-week timeline
- Conducted a pre-migration data integrity review and a chart-of-accounts clean-up so errors from the prior system did not carry forward
- Migrated customers, vendors, and transaction history, followed by a full parallel-processing period to validate the new platform against the old before cutting over
- Ran staff walkthroughs so the internal team could operate the new platform with confidence once Liv Data’s direct involvement wound down
The Outcome:
- The business moved from a failed implementation and untrustworthy numbers to a stable, fully reconciled finance function
- The new platform runs on documented processes rather than institutional knowledge held by a single person
- Financial records are audit-ready, replacing the disorganized state left by the failed migration
Why It Worked:
Stabilizing the books before attempting the systems fix meant leadership had reliable numbers to work from throughout the transition, rather than trying to migrate platforms while still operating on data nobody trusted. Sequencing the recovery this way — stop the bleeding, then fix the underlying cause — avoided compounding one unstable process with another.
