How CloudWatch reduced financial close time by 73% and eliminated reporting errors with automated visualization.

The monthly reporting crisis

Month-end close at CloudWatch had become a running joke in the worst possible way. Starting on the last day of each month, the finance team would begin a marathon process that consumed the first week of the following month. Eight people worked overtime pulling data from Salesforce, NetSuite, their data warehouse, three legacy systems, and two Excel spreadsheets that nobody wanted to touch.

Once the data was assembled, the real pain began. Someone had to manually create 40+ charts for the board presentation, each one requiring careful formatting to match the previous month's style. Copy the data, paste it into Excel, adjust the axes, fix the colors, export to PowerPoint, repeat. A single typo or formula error could invalidate hours of work.

The CFO's nightmare was discovering errors after the board meeting. It had happened twice in the past year—a chart showing incorrect trends because someone had sorted data the wrong way. The embarrassment was bad enough, but the loss of credibility was worse. The board started questioning every number, even when they were correct.

Discovering automation

The breaking point came during a particularly brutal close cycle when a senior financial analyst gave notice. In her exit interview, she was blunt: she did not join CloudWatch to be a human copy-paste machine. The CFO realized he was not just dealing with an efficiency problem—he was facing a retention crisis in a tight labor market.

A peer CFO at a portfolio company mentioned they had automated their entire reporting process using Lumis. The CloudWatch CFO was skeptical but desperate enough to schedule a demo. Watching their own financial data transform into board-ready visualizations in under five minutes was the convincing moment. The implementation decision took less than a week.

Building the new workflow

The implementation focused on their most painful process first: the monthly board package. CloudWatch's team worked with Lumis to connect directly to all eight data sources, eliminating the manual export steps. They built templates for each standard chart, encoding the formatting rules and validation logic that had previously lived in people's heads.

The breakthrough came from the automated validation features. Lumis flags data inconsistencies, unusual trends, and potential errors before generating final charts. When revenue numbers do not reconcile between systems, the AI surfaces the discrepancy immediately instead of letting it hide in a chart until the board meeting. The CFO sleeps better knowing there is a safety net catching problems he would never catch manually.

The transformation in practice

The first automated month-end close took twelve hours instead of five days—an immediate 73% time reduction. By the third month, they had optimized the process down to under eight hours. One financial analyst now handles what used to require eight people working overtime, and the work happens during normal business hours.

The error rate dropped to zero. Not reduced—eliminated. With no manual data entry or chart creation, there is no opportunity for copy-paste mistakes or formula errors. The validation rules catch data inconsistencies at the source, before they become presentation problems. The board now receives reports on the second business day of each month instead of day five or six, and the CFO presents with complete confidence.