Why is Last Year’s Seasonal Index Not Applicable Now?

Is Your Demand Forecasting Solution Leading to Profits?

A seasonal index, or seasonal multiplier, is a figure that is used to adjust a demand forecast. It either raises it or lowers the forecast for a period of time. The result of the calculation (product base forecast x seasonal index) can be used to determine the inventory needed to support sales during that time. A holiday like Memorial Day, a season like spring, or an event like the Super Bowl is often better serviced by applying a seasonal index across the year.

The Problem with Seasonality

The problem with Seasonality is that it is subject to change. Therefore, a current fiscal year may not align with your seasonal index. For instance, the Memorial Day holiday: this year (2024) will be on May 27, while last year (2023) it fell on May 29. For the inventory to be ordered correctly, the current year’s fiscal week seasonal index values must be adjusted.

Seasonal Index Peak Weeks May Be Wrong

Seasonal indexes are often set up into 52 weekly buckets that utilize two or three years of history. The seasonal index formula is: (period sales / total year sales) * number of periods.) However, a seasonal index used in 2024 for a holiday like Memorial Day based on a 2023 seasonal index would have the peak sales in a different fiscal week due to the differing dates of the Memorial Day holiday.

Seasonal Sales Can Create Inaccurate Demand Forecast

The demand forecast engine creates a demand forecast based on the data passed into the algorithms. As the Memorial Day holiday occurs at different times each year, the demand forecast will be affected. Therefore, if the wrong data is included in the sales history the demand forecast will be too low or too high depending on the timing of the holiday. Moreover, when an incorrect base forecast is multiplied by a seasonal index the potential for errors can be significantly higher. The result? Lost sales, missed service goals, lower gross margin, and higher safety stock.

Seasonality Impacts Lead Time

Product lead time is defined as the time needed from when a purchase order is placed until the goods are available to pick, ship, or sell. Seasonality impacts lead time; When you combine poor lead time management with inaccurate demand forecast, you may find that the Memorial Day picnic merchandise is expiring on the shelf before it is sold.

Don’t Fall Victim to History

We are here and ready to help. Contact us for a free consultation about your forecast accuracy and inventory management opportunities. You can also request a free demo and learn how our software solution can improve your business in 90 days.

• About
• Latest Posts

Stuart D

Stuart Dunkin is a strategic visionary who leads by calling on his broad range of experience as a former retail executive as well as a consultant for top retailers and for the E3/JDA software company. He founded Data Profits to solve a real-world problem plaguing retailers today – the disjointed relationship between supply chain data, people and business goals. He has experienced first-hand the challenges and frustrations that occur when decisions are made based on wrong data, which often leads to the wrong actions being taken with crippling results like overstock, out-of-stock, and increased working capital.
Stuart graduated from Auburn University, with bachelor of science in business administration.

Latest posts by Stuart D (see all)

• Demand Forecasting: The Ultimate Secret for Your Organization’s Success - August 7, 2024
• How to Avoid Carrying Cost Mistakes in Inventory Optimization - June 10, 2024
• 3 Common Forecasting Software Issues and How to Fix - May 20, 2024