The newly released report ‘Growing and Sustaining Competitive Advantage in Grocery Retail’ finds that nearly three-quarters of grocery retailers that took part in the study operate both brick & mortar and online shopping channels. However, 71% admit they don’t produce separate forecasts for each channel.
These results are worrying. Accurate forecasting is at the core of increased operational efficiency as it is key to accurately match resources, such as stock and personnel, with demand. And, for the forecasts to be reliable, it’s extremely important to do them for each channel separately.
Right amount of stock
A basic forecasting requirement is that retailers need to link online sales to the right fulfillment channel. For example, online orders that are picked in a regular store need to be included in the demand forecast driving replenishment to that store, even though the actual sales transactions belong to the online channel.
Simply lumping regular store sales together with online orders to form the basis for forecasting does not suffice.
However, simply lumping regular store sales together with online orders to form the basis for forecasting does not suffice. On many occasions, online orders follow a different sales pattern compared to regular store sales. We have, for example, noticed that easy price comparison online often drives even more pickup for promotions. Also, for major holidays, the timing of purchases may differ between physical stores and online; for example, online customers place large orders in advance of the holiday, whereas physical stores see a lot of last-minute dashes for products people have forgotten to buy. This means that separate forecasting of online sales is needed to accurately account for the sales channels’ varying demand patterns.
Right amount of personnel
In traditional brick-and-mortar grocery retail, store personnel form the largest operational cost, amounting to around 14 % of sales. When sales take place online, the retailers need to perform the order picking, which regardless of where the orders are picked is extremely labor-intensive, as the products need to be handled unit by unit, instead of in case packs.
This means that omnichannel grocery retailers need to be able to forecast picking volumes and their timing very accurately to be able to fulfill the lead-time promises made to their customers, without excess labor costs.
Through smart optimization of the timing of work tasks, retailers can, for example, move personnel from the checkouts to order picking when business is slower in the store. Planning for this in advance enables excellent service whilst keeping costs in check.
Forecasting is not only needed for optimizing inventories, it is also required for optimizing operations.
So, forecasting is not only needed for optimizing inventories, it is also required for optimizing operations. This means that we need to move from day-level sales forecasting to more granular forecasting to be able to plan when, during a day, capacity will be needed. Typically, this would require not only store-level forecasts but also forecasting per sales and fulfillment channel, and in some cases even forecasts within the day-level. And the best thing is, it’s actually not that difficult to do.
If you want to read more about this, our whitepaper ‘Fresh Forecasting & Replenishment: Running An Efficient Omnichannel Grocery Retail Operation’ goes in-debt on the topic.
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