Bottom-Up ForecastingDefined along with Formula & How to Calculate
A business’s operations do not end along with the end of the year.
They perpetuate until such time when the business terminates itself.
As such, as a business owner, you’ll always have to keep in mind your business’s future.
You should want it to stay alive for as long as possible.
Wouldn’t it be a waste if all your hard work in forming and maintaining your business would just unexpectedly go down the drain?
It’s good practice to create a budget for your business’s future financial performance.
You can do it in quarters, or a year, or maybe even several years.
Some budget plans cover five years of future operations.
These budget plans will be the basis on which future financial performance will be gauged.
Of course, you want your business to grow, so your projection for its future performance should exhibit growth too.
Make sure to show this desire for growth in your budget plan.
There are several ways to create such a plan, one of which is employing a method we refer to as bottom-up forecasting.
In this article, we will be learning what bottom-up forecasting is.
How can you apply it to your business?
And what are the steps for doing bottom-up forecasting?
By the end of this article, we should be able to answer these questions with the knowledge that we will acquire from reading it.
What is Bottom-Up Forecasting?
Bottom-up forecasting is among the methods of estimating future sales performance (i.e. revenue).
It starts by looking at the micro-level (e.g. volume of products, customer demand) going up to the macro-level (e.g. total revenue), hence bottom-up.
In a way, it’s like trying to understand how a complex system, like a car, works by looking at its most basic parts (e.g. wheels, engine, etc.) rather than looking at it as a whole.
For example, bottom-up forecasting will start with estimating the sales volume of each product that the business offers.
Next is determining the average sales revenue.
It could be for each product line, or it could be for all of the products as a whole.
From there, the average sales revenue figure will be multiplied by the projected sales volume.
Doing so will result in the total projected revenue.
Other micro-level factors can also be considered aside from the usual sale volume of each product or product line.
These include the geographic region, customer demographic, sales channel, etc.
All in all, these micro-level factors add up to project a business’s potential revenue.
To further understand bottom-up forecasting, let’s take a closer look at its potential components.
Essentially, there are two inputs for bottom-up forecasting: price and quantity.
The quantity input refers to projected sales volume.
It could be the average volume of units of goods expected to be sold, or it could be the average volume of services expected to be ordered and delivered.
If the business offers both goods and services, then it will be both.
We can group the quantity input of the business’s products depending on some factors.
For example, we can group together similar products or services that have the same average price.
We can also group them depending on their target demographic, sales channels (i.e. stores), etc.
Of course, we can just list the quantity on a per-product basis.
This will give a more detailed projection but has the downside of being limiting and time-consuming.
The price input refers to the expected sales price that the business will charge on its products or services.
The simplest way to determine the price input is to base it on historical pricing (i.e. sales price on previous years’ income statements) and then apply any factors that can increase it such as inflation or deflation.
If the business consistently gives out promotions and discounts, their effects on the average sales price should be considered.
Promotions and discounts decrease the sales price after all (in exchange for a higher sales volume).
You can set the price input on a per-product basis.
However, if there is a large number of different products or services, setting a price for each of them can become too cumbersome.
For such a scenario, you can employ certain methods such as the following:
For the price of goods (products)
- Average selling price – you can calculate the average selling of all the business’s goods. This mostly applies if all of the business products are similar. Alternatively, you can group similar products and then calculate the average selling price of each group.
- Average order value – some pricing models are based on a per-customer basis. This usually applies to businesses that sell personalized products. So, the sales price may vary from order to order. In such a case, you can use the average price per customer order.
- Average revenue per store – this method applies to businesses that have multiple physical and distinct stores. Simply calculate the average sale price of each store and then you have your price input.
For the price of services
- Average fees per customer – the business may provide different services to different demographics. As such, the price will vary depending on the type of customer that the business is serving. For example, a certain service may only be available to customers that are at least 18 years old. In such a case, you can calculate the average price per certain customer demographic
- Average hourly billing rate – a business may bill its customers an hourly rate. You can use the average hourly rate as the price input for the business’s services.
- Average contract value – a business may bundle its service on a contract basis. Thus, it’d be more appropriate to use the average contract value rather than the price of each service.
How to Use Bottom-Up Forecasting
We can list down the how-to of bottom-up forecasting in three major steps: determining the quantity input (sales volume), determining the price input, and finally determining the projected revenue.
To make it more understandable, let’s have an example.
The Ruby company is currently offering five brands of products.
These are brand red, brand blue, brand yellow, brand green, and brand violet.
Its management expects that it will be offering only these products for the following three years.
Brand red, brand blue, and brand yellow are standard products that target a general audience.
On the other hand, brand green and brand violet are luxury products that target a certain demographic.
Step 1 – Determining the quantity input (sales volume)
The first step of bottom-up forecasting is usually determining the projected sales volume.
In this case, the Ruby company has five brands of products.
Our task is to determine the sales volume of each product.
Looking at the Ruby company’s most recent financial statements, we gather the following:
- Brand Red has a sales volume of 100,000
- Brand Yellow has a sales volume of 88,000
- And Brand Blue has a sales volume of 113,000
As for the luxury products:
- Brand Green has a sales volume of 44,000
- While Brand Violet has a sales volume of 31,000
The management expects that the sales volume of the stand products (Brand Red, Brand Yellow, and Brand Blue) will annually increase by 20% over the next three years.
As for the luxury products (Brand Green and Brand Violet), management expects that their sales volume will annually increase by 8%.
With the above information, we can create a table that shows the project sales volume of each brand of product:
Step 2 – Determining the price input
The next step is to calculate the sales price of each unit of product sold.
We can do this on a per-product basis, but for the sake of simplicity, we will be using the average price of the two groups of products (stand and luxury).
From researching the Ruby company’s financial records, we gather the following:
- The average sales price of a standard product is $3
- The average sales price of a luxury product is $12
Additionally, the management decided that any price increase will only consider the annual inflation as the sole factor.
For the next three years, the management expects that annual inflation will be 3%.
With this additional information, we now have our price input.
Let’s update our table to reflect that:
Step 3 – Determining the projected revenue
The last step of bottom-up forecasting is to calculate the projected revenue.
We simply need to multiply the quantity input (sales volume) by the price input (average sales price per unit).
Let’s update the table to reflect this step:
And there we have it. Do note that this is a very simple example.
Bottom-up forecasting can get quite complicated depending on the level of detail that you want to include in it.
For example, you want to include assumptions for refunds, returns, exchanges, etc.
You may also want to add an allowance for unforeseeable events.
The more detailed you want your forecasting to be, the more complicated it becomes.
Also, keep in mind that bottom-up forecasting can only be as accurate as the inputs you use for it.
As such, it’s preferable to base your projected inputs on historical data such as what you can find on your previous or current financial statements.
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