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Sunday, November 24, 2024

Automated demand forecasting allows retailers to beat inflation

Christmas season is a business growth opportunity for many retailers because of a sure spike in consumer spending.

Filipinos were found to spend 331 percent of their monthly income during the holidays in 2021. Yet, a successful season for many retailers this year is threatened by the continuing impact of COVID-19 on the supply chain, along with the current economic challenges such as soaring inflation, increasing price of petroleum products and weakening consumer confidence.

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“Similar to retailers globally, Filipino businesses also grapple with the increased supply chain challenges from both the pandemic and the ongoing conflict between Ukraine and Russia. What’s more, consumers are equally experiencing the brunt of this situation, making the climate harsher for many enterprises,” said Kristie Davison, vice president for sales in Asia Pacific at RELEX Solutions.

“The most efficient way for retailers to navigate these uncertainties would be to plan how to maximize sales while minimizing loss,” she said.

Seasonal inventory management is often difficult due to advanced purchasing before the season and a high risk of the residual post-season stock. Christmas, in particular, means that there’s a high turnover of product lines from one season to the next.

A lot of smartphones are sold during the holidays but the selection is always different per year. Brands also often launch new products that are systematically pushed throughout the -ber months as seen in 11.11 and 12.12 promotions, requiring retailers to assess demand for each.

These situations underscore how crucial demand forecasting is in order to get the right amount of stock-keeping units and ensure a return on investment. Unfortunately, many retailers manually forecast demand, posing high risks of inaccuracy that can lead to over- or understocking.

Automating demand forecasting helps businesses achieve optimal outcomes by improving the on-shelf availability of seasonal products and reducing residual stocks when the season ends.

A good forecasting model for seasonal planning includes a reference product that can be specified against seasonal or event-specific indices to calculate data-backed forecasts for new items.

Empowering businesses to search the historical assortment for items with similarities to those being introduced and build a forecast can potentially drive significant improvements to availability and inventory values while considerably reducing markdowns.

With Christmas spanning four months in the Philippines, smart replenishment also contributes to improving a brand’s responsiveness to consumer demands.

A good solution is to deliver only a part of the forecast demand to stores at the beginning of the season to avoid moving goods among shops. Once holiday shopping starts, SKUs at individual stores can be replenished through pull control that is based on the latest sales, store-specific forecasts, and actual inventory.

This enables retailers to effectively respond to local conditions with respect to external factors such as weather or a change in competition for an individual store. When products are bought in advance, push control should be used toward the end of the season to ensure that seasonal products don’t pile up unnoticed in the central warehouse. An ideal management system allows allocations to be directed to the stores with the best chances of selling the products such as those with the highest sales and no excess inventory.

“It is important to remember that a model of operations is not necessarily the best one simply because it has been used for years,” said Davison.

“Digitizing seasonal inventory management helps retailers make seasonal sales sustainable, achieve better results, and prepare well for such events.”

RELEX Solutions is a market-leading supply chain and retail planning platform that helps retailers and consumer brands unify their planning, from demand and merchandise to supply chain and operations, for maximum customer satisfaction at the lowest operating cost.

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