There are a variety of reasons why demand for products can experience variability.
Extremes of weather, flash sales and in more recent Covid 19 times demand shocks have occurred in several sectors. Emotional and panic buying has resulted in demand, supply, and delivery uncertainty.
Having a more resilient supply chain by building the capability to respond effectively can reduce vulnerability, increase adaption to uncertainty and preparation for unexpected events.
With the continued growth of eCommerce, consumers are demanding product availability and faster delivery.
The retail landscape is especially competitive, and customers are expecting products when and how they want them.
Giving suppliers a more reliable anticipation of demand for uninterrupted product supply is an important factor in ensuring supply chain resilience.
"Drive from unknown uncertainty toward known variability by utilizing machine learning for better predictions." - Gartner (2019)
Demand forecasting utilizing machine learning creates better predictions providing less uncertainty and more knowledge about demand variation.
It uses multiple complex data sources such as pricing history, unusual sales activity in historical sales, promotions, variation in demand due to seasonality and external factors such as the weather or events.
Machine learning processing also use algorithms to find patterns and correlations to improve accuracy of the forecasts.
Constantly and automatically improving with time, machine learning enables companies to respond quickly to fast changing business situations.
It is important for demand planners to be able to solve supply chain problems quickly by having access to different planning horizons.
TrueStock generates a forecast horizon that provides a lower, middle, and upper estimate for sales demand each day.
A 120-day forecast is also available which helps with operational and tactical demand planning. Predictive forecasts can be generated at speed to identify unlikely trends in consumer demand to ensure that retailers do not run out of stock.
Another key element in supply chain resilience is connectedness. TrueStock automatically syncs with eCommerce stores daily so that forecasts are readily available for viewing ensuring the relevant teams have forecasts at their fingertips.
TrueStock also has an automatic replenishment process that informs you about future inventory replenishment quantities, the costs of replenishment, predicted revenue and the costs of missed sales opportunities.
It is also possible to add alerts on inventory including the supplier lead time so you can replenish with ease. Your teams can also be notified when stock levels are low or at a buffer stage allowing you to take immediate action.
The combination of machine learning-based demand forecasting and automated replenishment can help with optimizing speed, accuracy, and resiliency in the supply chain.
For customer centric companies who are serious about improving their supply chain through more accurate sales predictions and automated replenishment, TrueStock will prove to be an invaluable tool.