How can you determine the appropriate level of detail for forecasts?

1 Know your purpose

The first step to determine the level of detail for forecasts is to understand the purpose and audience of your forecasts. Different stakeholders may have different expectations and needs for the information you provide. For example, senior management may want a high-level overview of the key drivers and trends, while operational managers may need more granular and specific data to make decisions. Therefore, you should align your level of detail with the objectives and scope of your forecasts, and communicate them clearly to your audience.

2 Use relevant and reliable data

The second step to determine the level of detail for forecasts is to use relevant and reliable data sources and methods. You should select the data that best reflects the factors that influence your financial outcomes, such as sales, costs, cash flow, market conditions, etc. You should also ensure that the data is accurate, consistent, and timely, and that you have enough historical data to establish patterns and trends. Moreover, you should choose the forecasting methods that suit your data characteristics and assumptions, such as regression, time series, scenario analysis, etc.

3 Consider the trade-offs

The third step to determine the level of detail for forecasts is to consider the trade-offs between simplicity and complexity. On one hand, you want your forecasts to be simple enough to understand and communicate, and to avoid unnecessary noise and uncertainty. On the other hand, you want your forecasts to be complex enough to capture the dynamics and variability of your data, and to account for potential risks and opportunities. Therefore, you should weigh the costs and benefits of adding or removing details, and test the sensitivity and accuracy of your forecasts.

4 Review and update regularly

The fourth step to determine the level of detail for forecasts is to review and update them regularly. Forecasts are not static, but dynamic, as they reflect the changing conditions and expectations of the business. Therefore, you should monitor the actual performance against your forecasts, and identify any deviations or errors. You should also update your data and assumptions, and adjust your level of detail accordingly. By doing so, you can improve the quality and reliability of your forecasts, and learn from your feedback.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?