October 20, 2018      3 min read

Consumers around the globe are changing their shopping habits and retailers must constantly respond to shifts in consumer demand. Supply chains are more multi-faceted than ever – materials to make one product may come from multiple countries; imports and exports are sent around the world in just about every kind of vessel you can imagine; there are online eCommerce sites and brick-and-mortar retail stores that facilitate product distribution.

Since there are so many steps in the modern supply chain, it’s important to order the right amount of inventory stock for your business. Failure to have the right amount could result in unhappy customers and a loss of reputation for your business. So, how do you order the right amount to meet demand? Demand forecasting can support your decision-making process when deciding how much inventory stock is necessary.

What is demand forecasting?

Essentially, demand forecasting is a strategic process that helps businesses make educated estimations about future customer demand. These estimations are calculated by amalgamating historical sales data, looking at patterns in consumer buying habits and analysing previous inventory levels during different stages of demand. A series of algorithms can derive clear answers for your business across a variety of sales environments.

The algorithm results can support the decision-making process when it comes to purchasing or manufacturing more inventory stock. Demand forecasting provides a wide array of predictive analytics. These analytics aim to estimate upcoming customer demand. With these numbers, management can make more informed decisions on how to operate their warehouse and their supply chain logistics. Let’s take a look at a few important factors that support demand forecasting.

Historical sales data

They say hindsight is 20/20, right? With demand forecasting, one of the best ways to predict the future is to consider the past. Online inventory management systems can track stock levels in the warehouse, as well as sales data. Looking back at five years of sales data can reveal numerous patterns and provide clarity around demand. Of course, this input, alongside the other inputs act as a supportive adjunct to forecast demand. However, there are always going to be fluctuations due to unforeseen events. This could be due to extreme weather events, the release of a new trendy product, or economic events such as a financial crisis.

Seasonal sales patterns

It’s well known that buying habits increase around the holidays and shift with the seasons. When conducting demand forecasting, it’s important to look at all products against their seasonal activity patterns. Make sure you analyse the data carefully and consider all promotions and big sales you initiated to gain a holistic understanding.

Supplier data

Using supplier data can add another layer into the mix when calculating demand forecasting. They might have additional information about product availability and new products entering the market that could impact demand.

Demand forecasting can be hugely beneficial to a business. It can help you optimise inventory stock levels and work towards a more efficient mode of operation. There are a variety of inputs that can assist in demand forecasting. Utilise these resources and many more to help your forecast for demand.

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