If you are like most sales teams, you determine your monthly sales goals by taking your yearly goal and dividing it by twelve. If you give a rep a yearly target of $1.2 million, then you tell them they need to get at least $100,000 in each month.
But is that accurate? Are your sales in July the same as they are in December?
While some companies experience relatively stable sales throughout the year, the majority experience some sort of seasonality. Certain months or quarters of the year have traditionally higher or lower sales volume.
When doing your sales forecasting, it’s important to include seasonality. You want to set realistic quotas for your sales team. You also want to be able to give accurate forecasts to your operations team for order fulfillment.
Calculating Sales Seasonality
To forecast your sales with seasonality, you need to first start by understanding your seasonality. This requires looking back in the rearview mirror to understand past patterns of busy and slow periods.
To start, grab your historical sales for the last three to five years. You can do this by month, or by quarter, depending on how you track quotas. I’ve found that having three to five years of data is helpful. Anything less, and you can’t get meaningful trends. Anything more, and you may grab previous trends that no longer exist.
Plot that data in a table, with the monthly totals and a year end total.
Once you have your historical sales data set, you can perform some basic seasonality calculations.
You’ll create a new table, with your monthly (or quarterly) average for each year in the first row. This can be done by referencing the yearly total in the previous table, and divide it by 12 (or 4 for quarterly).
Then, you’ll calculate each month’s seasonality factor by dividing each month’s sales number against the monthly average for every given year. When plotted, you’ll see a table that shows the relative difference in sales for each month against the average for that year. Anything above 100% is an above average month, anything less than 100% is below average.
The final step is to average the monthly rows for the seasonality factor. This average of seasonality for each row will show you the average seasonality factor each month (or quarter).
You’ll see in the example above that there is some seasonality at play for their sales:
- September is usually a lower sales month. On average, September sales are 90% of the average month for the year (with 2019 being an exception).
- The summer months of June, July, and August are their busier months. They tend to be at or above average sales then.
- The holidays, or end of Q4, tends to be slower as well. With 91%, and 96% of sales average in November and December.
By graphing this data, you’re able to visualize seasonality for your sales. A line or bar graph can help you see how seasonal trends happen throughout the year.
Sales Forecasting to Seasonality
Now that you know the seasonality of your sales, you can begin to use this information to better forecast your sales. This will allow you to better understand goals for your sales team, as well as set reasonable expectations for when work will come in.
Forecasting with seasonality is actually quite simple. All you have to do is apply your new seasonality factors to your sales forecast.
For the sake of demonstration, let’s pretend that our example company above was forecasting sales of $13,500,000 in 2021. This would mean that their average monthly sales would be $1,125,000.
But we know based on the seasonality data that we wouldn’t want to expect $1,125,000 each month. So instead we’ll apply our seasonality factor for each month. This is done by multiplying each month’s seasonality factor by the average month.
With a seasonally adjusted forecast, you can see in the table above that an on-target month in January would be about $1,070,000, whereas an on-target month in June would be $1,245,000. To make goal setting easier, we can also sum up the months into quarters.
Managing Sales to Seasonality
As a sales person, it’s important that you understand your sales seasonality. It could change how you set quotas, when you run marketing campaigns, and how your operations team schedules workload.
I’ve personally used seasonality data as a way to adjust forecasts for quarterly sales. It’s helped me to set appropriate expectations with sales teams, and define what on-target numbers should be based on the time of the year.
At the same time, there is going to be natural variability in any business process. So you need to manage appropriately based on your data and specific knowledge of additional factors.
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