After building your financial reports you will now want to understand best practices for interpreting the results.
Any financial budget will have a forecast associated with it, given the budget hasn’t already been exceeded. This forecast is based on a data science model that interacts with your own budget and spend data. The machine learning model looks at the historical spend attached to the budget. From that historical spend, it generates a prediction for future spend within the budget period. From this information, Brightflag generates a custom forecast and a predicted date-of-overrun (if relevant) with a 95% confidence interval.
The model needs approximately 6 months of spend data to generate these results. Where there is insufficient data to generate model results or modeled uncertainty is high, the message No Forecast Available will display.
This is the total of all matter-level budgets you have set. Only matter budgets that are set by month or by quarter will be considered (as they are timebound).
Leveraging the results:
Share these forecasts with your financial team to get their input. If your budget is predicted to overrun, discuss the findings with each department lead within your legal function. To learn more about this, contact your company’s dedicated Brightflag Customer Success Manager to gain guidance on the next steps.