Making the financial close understandable before automating it.

The close process depended on spreadsheets, financial systems, approvals, recurring exceptions and knowledge held by experienced employees. Before automating anything, Orgni made that whole operation understandable.

A fragmented operation

Every month, this mid-market finance team spent five gruelling days on close. The mechanics lived in spreadsheets and ledgers; the understanding lived in people. Which exceptions recur, who approves what, which corrections are routine and which are warnings - all of it was trapped in experienced employees' heads and reconstructed from scratch each month.

The team was capable. The problem was that the close, as an operation, was not understandable to anyone or anything outside the people who ran it. Automation attempted on top of that fragmentation would have been brittle.

Building the organisational model

We turned on financial operations in Orgni, plugged into the firm's ERP and banking data feeds. But the first step was not automation. It was representation: Orgni modelled the close as a live picture of responsibilities, dependencies, controls, deadlines and historical decisions.

• Responsibilities. Who owns each reconciliation, review and sign-off.
• Dependencies. Which inputs each step waits on, across ledgers, feeds and teams.
• Controls and rules. The thresholds, approvals and policies that govern the close.
• Decision history. How previous exceptions were investigated and resolved.

What became possible

Once the operation was mapped, the team introduced automation into parts of the process. Transactions are matched across ledgers and bank feeds automatically. Discrepancies are flagged with context about what changed and how similar cases were resolved before. Missing inputs and bottlenecks are identified for review.

The team reviews, approves and signs off - instead of rebuilding the close from scratch each month.

The numbers

A foundation for continued improvement

Month-end close now completes overnight, and accuracy has improved, because exceptions are reviewed systematically rather than by whoever happens to notice. The mapped responsibilities, dependencies and decision history give the team a structured basis for continued improvement.

The work went beyond an isolated automation: it documented how this close operates, creating a reference for the teams involved and future process changes.

"We used to dread the last week of every month. Now close just happens. The team is working on things that actually require their expertise."- CFO, financial services firm