How do you create a budget and track it effectively?
Efficiency question :
Creating a budget from historical data quickly becomes complex when the chart of accounts contains a large number of accounts or varies from one organization to another.
The objective is to use historical actual data to establish rules for projecting future results. Rather than applying a calculation method individually to every general ledger account, a more efficient approach is to group accounts with common characteristics and apply calculation rules by account family.
This structure makes it possible to automate a significant part of the budgeting process and subsequently facilitate monitoring between budgeted data and actual results.
Key considerations:
General ledger accounts can be grouped into different categories, including assets, liabilities, revenue, expenses, depreciation, as well as accounts related to income tax, tax remittances, and cash flow.
These account families do not necessarily behave in the same way when projections are prepared. To create a budget efficiently, calculation rules should therefore be established for the different account families rather than applying a single formula to the entire chart of accounts.
This segmentation is one of the foundations for efficiently automating a budgeting process.
Challenges:
The challenge becomes greater when the historical data required for projections is unavailable or when the model must incorporate data from several companies.
In a multi-company environment, charts of accounts are not necessarily identical. A mapping table must then be created to group the different accounts into a common structure before budget calculation rules are applied.
The quality of the model therefore depends both on the projection rules and on the ability to structure the historical data used as the basis for calculations.
Technology:
For this type of budgeting model, calculations can become too large and the historical dataset too extensive to perform all processing efficiently directly in Excel worksheets.
One approach is to use Power Query differently from its usual role. Rather than using it only as a data integration, transformation, or loading tool, Power Query can serve as an external calculation engine for the model.
Calculation rules can therefore be applied in bulk to historical data and the different account families before the required results are returned to the budget report.
Developer's advice:
To automate a budgeting process efficiently, start by structuring the actual historical data and determining the calculation rules that must be applied to each general ledger account family.
This approach builds projections from a common logic rather than multiplying individual formulas for every account.
For models containing a significant history and a large volume of calculations, favor a model in which Power Query performs the processing rather than carrying out all calculations directly in Excel worksheets.
This architecture concentrates calculations in Power Query and reserves the worksheets for presenting and using the results.