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Last week, Shai Cohen, Curve’s VP sales gave a talk at a Supply Chain Management conference in Tel Aviv about the many benefits that machine learning provides in supply chain management. More specifically, Shai talked about how Machine Learning technologies such as Curve’s are helping merchants create clearer inventory forecasts that ultimately improve sales.

A recent report by Wakefield Research which surveyed companies with $500m+ in annual revenue suggests an ongoing catastrophe in how inventory is tracked and forecasted in the $1.3 trillion retail sector.
Over 70 percent of those surveyed, stated that inaccurate inventory forecasting is a major issue, resulting in costly supply-demand mismatches. Additionally, two-thirds of those surveyed reported difficulty tracking inventory through the supply chain.
A few of the most common challenges that eMerchants, as well as brick-and-mortar retailers, are faced with is predicting online demand for their products, especially during holidays (Black Friday, Cyber Monday etc.). Another major challenge is managing inventory for both online and offline activities.

REACH YOUR SALES AND INVENTORY GOALS WITH CURVE

Due to rapidly emerging tech, a major shift is being witnessed across every industry vertical, and the supply change industry is no exception. Professionals need to be prepared for a sudden influx of new orders on account of quick growing retail businesses, or alternatively an unexpected business slowdown which may lead to unsold inventory. That’s where machine learning comes into play.
As Shai shared with the conference attendees, “Curve uses machine-learning based prediction technology, allowing companies to accurately forecast sales, products, and support requests, to increase revenue and optimize profitability.” He also said that “Curve’s unique technology goes beyond traditional business intelligence, by recommending the right solutions based on use cases and customer segments.”

Machine learning when used in conjunction with IoT further provide real-time monitoring throughout the supply chain. With the right sensors and reporting, organizations can track every item through its supply chain with ease. This allows for the identification of core inefficiencies that need to be resolved, as well as the ability to streamline the supply chain process.
In short, Machine learning now makes it possible to discover patterns in supply chain data by relying on a mix of historical data and algorithms that quickly pinpoint the most influential factors to business growth.