Maybe you’re pulling reports from three different platforms, trying to reconcile numbers that don’t quite match. Maybe you’re manually copying and pasting from multiple spreadsheets, hoping you didn’t introduce any errors along the way. Or maybe you’re waiting on IT to clean up, prep data, and merge datasets before you can even start analyzing trends. At any rate, you need answers—but you have unclear data.

If this sounds familiar, you’re not alone. For many organizations, the biggest data challenge isn’t a lack of information; it’s the sheer effort required to piece it all together. That effort is costing you more than you think.

The hidden costs of manual data compilation

Bad data don’t always mean incorrect numbers. Sometimes, the problem is simply how the data are collected, stored, and combined. When teams rely on manual aggregation and reconciliation, it can lead to:

Wasted time: Analysts, finance teams, and operations managers spend hours pulling data from different sources, fixing format inconsistencies, and verifying accuracy instead of analyzing insights.

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