Prep your stores to weather seasonal and holiday demand swings with data-based forecasting.

As schools begin to let out across the U.S. and the first days of summer quickly approach, it’s important to remember to prep your inventory for your busiest months of the year. According to NACS, convenience store sales are highest during the summer. This increase in business can be attributed to an increase in the hours of daylight, outdoor activities and travel. It also provides you with the potential to capitalize on two of the largest holidays of the year – Memorial Day and Independence Day. With seasonal and holiday influences set to cause large swings in inventory demand for c-stores, prepping your store to weather the impending consumer wave and continue delivering exceptional customer experiences is essential.

Know what to stock

Knowing what to have on hand can be difficult. From gas to in-store products, demand during peak season can vary widely. That’s where forecasting comes into play. Forecasting is a method of ordering and inventory management that c-stores can use to help maintain adequate stock levels that prevent both over and under stocking. By utilizing forecasting during periods of demand change, such as seasonal and holiday events, you can make necessary adjustments measured against the normal inventory baseline you have for your stores.

In order to accurately forecast for your stores, you’ll need to supply data to produce actionable results. Data is the key to accurate forecasting. Similar to manual scheduling, best-guess ordering and inventory management is inefficient and error prone. Forecasting allows you to analyze years of sales, seasonal, holiday, and promotional data, providing the accurate information you need to keep the items your customers want on the shelves.

Factors to consider in forecasting

Before you can run, you’ll need to learn how to walk. In order to begin using historical data to accurately forecast consumption this summer, you first have to establish a base forecast. A base forecast is a weekday-specific average of specific transactions for an item, based off historical data. So, what factors impact your base forecast?

The weeks you consider. In forecasting, the weeks you choose to forecast against affect how fast your forecast responds to change. For example, the more weeks your forecast considers, the slower the change to your forecast.

Excluding the highest and lowest volume sales for items. To ensure the most accurate forecast, you can exclude the highest and lowest volumes of sales for items in your historical data. By removing both extremes, your forecast will generally be more accurate because you’ve removed abnormal/volatile sales days.

The transactions you include. Your transaction history paints the picture for your normal sales of each item. Consider including sales, adjustments, transfers and more, to provide yourself with the most accurate picture, including items without historical data. News items should be determined based on an educated guess using the limited data you have available for the item. For the first week, the safest action you can take is to forecast using the highest sales for any available day. It’s best to err on the side of caution with new items. Try not to underestimate your potential sales.

How to forecast for seasonal and holiday changes

While there are several types of forecasting methods, two, in particular, will help you navigate demand changes in the upcoming months. The first, seasonal forecast, allows you to adjust consumption projections for inventory items when a specific time of year has a large impact on consumption, such as the summer months. At times, the overall consumption trend can change at a pace faster than your current year average anticipates. That’s where historical trend analysis comes in. In this case, if the overall trend is recurring year over year, you can use the difference between sales and projected sales from prior years to adjust the current year’s forecast.

By measuring how far prior year forecasts differed from prior year actuals, your inventory management software should be able to adjust the current year forecast to a more accurate reflection of the current year’s demand and the current seasonal trend.

The second type of forecast is a sales forecast event, which is anything that dramatically shifts demand when there is no indication of the event in the historical data. These situations are typically tied to some kind of social or promotional event, such as a national holiday like Memorial Day or Independence Day. A sales forecast event allows you to adjust consumption forecasts looking forward and reduce the historical impact of the event looking backwards. That means, for future forecasts on that item, you need to adjust the inventory up or down, depending on the effect that event had on sales (high sales due to the event, or low sales due to the event). Looking backwards, it’s important to remove the social or promotional event when calculating an item’s typical average consumption since the event puts the consumption and inventory count in abnormal ranges.

Accommodate for the upcoming summer season and summer holidays by removing the guesswork from your inventory management. Use the data at your fingertips to prepare for these upcoming changes. With forecast ability, you’ll know the modifications needed for your inventory levels to accurately prepare for any demand shift.

Did You Know: Your Source for PDI News provided by PDI, the leader in enterprise management software for the convenience retail and petroleum wholesale markets.