When setting up your project in RunSmart, you have the option to pull in up to 10 years of historical financial data. Here’s why we make that available—and how it helps improve the accuracy of your forecasts and insights.

The more historical data we have, the better we can understand your business’s financial trends over time. Long-term data helps identify patterns such as seasonal fluctuations, recurring revenue cycles, or cost behaviors that may not be obvious in just a year or two of records.

While having access to long-term data is valuable, our forecasting engine is designed to focus more on recent trends. This helps ensure your forecasts reflect your business’s current direction, rather than being overly influenced by outdated information. For example, if your business has grown significantly or changed its model in the past few years, our system will prioritize that recent activity when generating projections.

You can choose how many years of data to import—from 1 year up to 10 years—based on what’s most relevant to your business. While you can’t skip over specific years or exclude individual time periods, selecting a shorter range lets you avoid including years that may not reflect your normal operations—such as periods affected by major world-wide disruptions, rare market conditions, or one-time events that significantly altered your business’s performance.

If you're unsure where to start, we generally recommend including at least 3 to 5 years of data (RunSmart requires at least two years). This provides a solid foundation for trend analysis and forecasting, while still keeping the focus on the most relevant information.