How to Manage Seasonality of Demand to Increase Forecasting Accuracy

2 min read

Tags: Blog, Demand forecasting, Inventory management, Purchasing & replenishment

Daniel Fritsch   October 20 2014

Manage Seasonality of Demand Forecasting

Seasonality, as it relates to inventory management, is defined as a certain time series with repetitive or predictable patterns of demand. Seasonality is typically measured by the quantity of interest for small time intervals, such as days, weeks, months or quarters.

Almost every manufacturer or distributor can expect to have seasonal fluctuations in their demand. Everything from peak holiday sales activity to droughts in sales due to seasonal weather changes can influence what demand the market will have for your products.

While it is extremely important to account for how seasonal changes affect demand, it may be possible for your organization to go beyond your normal inventory demand forecasting processes to give your business a much needed competitive advantage.

Understanding how seasonal factors affects customer purchasing habits helps businesses position themselves to take advantage for variations in demand. Knowing demand patterns can help an organization strategically optimize their inventory levels to avoid inflating carrying costs, but also ensuring that customer demand is easily serviced through having inventory on hand when needed.

Being able to free up working capital that is usually sunk into excess inventory while increasing service rates could have drastic effect on your profitability. With regard to forecasting, seasonality refers to the portion of demand fluctuation accounted for by a reoccurring pattern. This is identified by the demand pattern repeating systematically over time.

Remember that if seasonality is used on an item, the demand should be adjusted before used in the forecast calculation. Best practice is to keep seasonal demand and other variable factors separated from your base demand calculations in order to keep the data clean and easy to use for forecasting going forward. Below is an example of the different demand factors that can impact or inflate your normal base demand.

Demand Forecasting Influencers Graph
Factors That Can Affect Base Demand Forecasting

The orange bar graph represents the average based demand an organization should carry to meet customer demand. The other factors are additional influencers on demand, but are not typically constant across any given period and can vary dramatically. Factors like market trends, market knowledge, sales and marketing projections and seasonality of demand inputs are all separated for each and every product, to ensure the integrity and accuracy of the forecasts.


Learn More:

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