An allocation model is commonly used in a planning and budgeting process. A simple allocation model distributes an amount, such as expenses, to different segments of a business. The segments can be cost centers, departments, sales teams, etc. An example of a simple allocation model is an IT allocation model which allocates the total IT expenses among cost centers. This type of model requires a total amount (of expenses) and allocation percentages to calculate allocated amounts. Please see an example below.

PreAllocation and Post-Allocation Tables

The pre-allocation table specifies an account, cost center and total amount. In the post-allocation table, an allocated amount is equal to the total amount (pre-allocation) times an allocation percentage. This calculation is repeated each cost center.

Another calculation that we have not discussed in the post-allocation table is the allocation percentages. There are many ways to calculate the allocation percentages. The most common method is to calculate the percentages based on a set of values across allocated segments. In the example above, the segments are cost centers. Headcount is generally used in the IT expense allocation. An allocation percentage is equal to the headcount of a cost center divided by the total headcount.

Headcount and Allocation Percentage Table

We have talked about a simple allocation model and this type of model can be built in a spreadsheet if the spreadsheet can handle the volume of data. If an allocation model is much more complex, spreadsheet is no longer a viable option. Planning Analytics (PA) is a great platform for building a planning and budgeting model and it accommodates a large and complex allocation model. PA has the ability to process a lot of data in a short amount of time. The platform is also very flexible, so it allows the full customizations of our allocation model. To demonstrate this point, we will add two more features to our simple allocation model. These features can easily be built in Planning Analytics.

The first feature that we want to add is the ability to select the period from which we will pull the headcount. We can use the headcount number from the prior period, prior quarter, or even the end of year last year. A drop-down selector can be added to our model to allow the user to select the appropriate headcount period for the current planning. If the headcount numbers fluctuate a lot in the prior months, we can also use an average of the last three months to make the allocation percentages more realistic.

Another feature that is useful is the ability to change the allocation base. Although headcount is an appropriate base for the IT expense allocation, headcount may not be appropriate for advertising expense allocation. We may want to change the base to the percent of revenue when we allocation advertising expenses. These are the sample features that we can add to the allocation model in Planning Analytics. The model will start to be complicated quickly when we add more features to our allocation model. These features apply to all forecast periods and all account and cost center combinations. Nevertheless, they will not cause a performance issue when they are properly implemented in Planning Analytics.

The allocation model with additional features with drop-down selectors

In summary, an allocation model ranges from a simple model to a complex one. Planning Analytics is a platform that can handle complex allocation models with ease. Many features can be added to accommodate the business needs. The flexibility and the ability to process a large set of data make Planning Analytics an ideal platform for an organization which grows quickly. There are other allocation models that are not covered in this article like a multi-step allocation model. However, we can still build it in Planning Analytics without an issue.