Naïve forecasting is one of the simplest demand forecasting methods often used by sales and finance departments. It uses the actual observed sales from the last period as the forecast for the next period, without considering any predictions or factor adjustments. Though simple, it can work remarkably well for business. But it doesn’t account for the changing market conditions or seasonality, factors that can substantially affect demand.
How is a Naïve Forecast calculated?
Naïve forecasts can easily be calculated using spreadsheets. You can start by entering actual sales data for a certain period of time, say monthly sales numbers for the past two years. Use this data to enter forecasts for each period by choosing the actual sales data from the past period.
Since the naïve forecasting method isn’t accurate and doesn’t account for many factors, it’s essential to calculate the error in forecasting or the deviation between the forecasted and actual sales. You can calculate the percentage variance between your actual and forecasted sales in the spreadsheets by using the formula –
IF (Actual Sales = 0, 0, (Naive Forecast/ Actual Sales)-1)
If the variance between actual and forecasted sales is positive (e.g., 9.05%), it means that your actual sales were greater than the forecasted numbers. This is often a preferred situation for sales professionals, allowing them to under promise and over deliver. On the other hand, if the variance is negative (e.g., -9.05%), it indicates that your forecasted sales were greater than the actual sales for a given period or that you sold less than the last period.
A variance of less than or equal to 10% isn’t considered problematic, but if the numbers are bigger (e.g., 41% or -41%), it can indicate bigger problems like a stockout or overstock.
Seasonal Naïve Forecasting
If you monitor sales data over the years, you will start noticing a pattern or trend in how your sales numbers fluctuate across seasons. A business that manufactures sweaters might experience high sales numbers between October and January and low numbers from April to July. On the contrary, a business that manufactures sundresses might see the opposite trend.
Seasonal naïve forecasting is the process of generating better sales forecasts by accounting for seasonal change. Similar to the naïve forecasting method, this method considers the last actual sales from the same season as the forecast for the coming season – like considering the sales numbers for February last year as the forecasted sales for February in the current year.
Though it isn’t entirely accurate, seasonal naïve forecasting can help you better prepare for your sales, especially if you experience an extreme change in demand for a particular season every year.
The problem with Naïve Forecasting
Though it is simple to calculate, naïve forecasts aren’t always the most accurate. As we mentioned before, the naïve method of forecasting doesn’t account for any significant factor that might affect your demand.
Consider the percentage variance between your actual and forecasted sales that we discussed before. Suppose you get a high variance, like 41%, which would mean that you sold over 41% more products than you forecasted. Now, considering that you only held 41% more products in your inventory, there is a probability that you might have sold more had your inventory not run out. Similarly, a variance of -41% would mean that you sold less than forecasted, leading to overstocking in your inventory. You would have to pay extra to hold the excess inventory, and if you sell perishable products, it might also mean deadstock or inventory loss.
In today’s dynamic markets, where demand fluctuates rapidly, naïve forecasting can lead to loss. A sudden bump in demand for a small period can cause you to overestimate your demand and lead to a loss in the next period. Similarly, a sudden drop can cause stockout and lead you to lose sales and often customers. Moreover, it can be hard for demand planners to determine factors affecting the sales, which might help them improve.
Accurate Demand Planning
When it comes to planning your demand accurately, there are many factors to consider. Though you can plan your demand manually, it can be time-consuming, inefficient, and error-prone. It is recommended you use demand planning software to plan your demand better.
TransImpact offers accurate demand planning software that lets you forecast and plan your demand for up to five years. It uses 250+ forecasting algorithms developed over the years to forecast your demand with up to 99% accuracy. It creates the forecast based on your past sales data, seasonality analysis, and market analysis and accounts for all the factors that affect your demand.
You can use the forecast to better plan your inventory and ensure you have the right inventory, in the right place, at the right time. You can avoid losing sales and wastage associated with unplanned demand.
Though naïve forecasting is a helpful demand and sales forecasting technique, it is laced with issues that can lead to loss. These problems can be avoided by using demand planning software for your business.
Get in touch to know how you can benefit from our demand planning software.