3 Predictive Analytics Strategies to Transform Your Supply Chain

The rapid growth and complexity in today’s supply chains and the ever-changing business landscape require businesses to improve resilience against disruptions. And for this, predictive technology is the biggest catalyst.

According to a recent survey, $41 billion worth of data-driven technologies are projected to be integrated into the logistics and supply chain industry by 2027.

This points to the importance of predictive analytics. However, data by itself is not enough. Shippers and beneficial cargo owners must invest in the tools and techniques of supply chain analytics. This will allow them to be prepared for interruptions, plan proactively, boost visibility and optimize operations.

Moreover, the incorporation of predictive analytics into supply chains helps organizations perform ‘what-if’ analysis and take early action by prioritizing software recommendations.

Here are three predictive analytics use cases for bringing predictability into your supply chains and building resilience and profitability.

Strategy 1: Demand Forecasting

Accurate predictions of customers’ demand are at the core of efficient supply chains. They help keep the right materials in the right place at the right time. When you know what your customers want and how much, you can avoid both over-stocking and stock-outs, cut costs and consistently meet demand.

Predictive analytics takes demand forecasting to another level. With its ability to sift through historical data and real-time information, predictive analytics plays a pivotal role in enhancing the precision of demand forecasting. By identifying patterns, trends, and anomalies in data, predictive analytics empowers businesses to make forecasts that are not only accurate but also adaptable in the face of changing market conditions.

For example, textile manufacturers can use predictive analytics to analyze past data and external market trends. It may predict that, just before the holidays, demand would jump for a key material of its products. This information would help modulate production plans and order the material in advance to reduce the risk of stockouts and expedite deliveries.

Strategy 2: Inventory Optimization

Maintaining optimal inventory levels is a balancing act that international shippers can achieve through using supply chain predictive analytics. This strategy revolves around keeping just enough inventory on hand to meet demand without incurring excess carrying costs.

Predictive analytics is most effective at picking up trends and patterns in inventory management. It helps a business calculate optimum levels of stock and ensure that products end up in the best placement for the customer, with the least lead time – resulting in more sales.

For instance, e-commerce companies can successfully strengthen their supply chain with predictive analytics. By monitoring shifts in product demand across different regions, they can forecast the availability of products in particular markets. Inventory levels of the specific products can be maintained in distribution centers optimally. Holding costs can be reduced and order fulfillment can be expedited for greater customer satisfaction.

Strategy 3: Supply Chain Risk Management

With unpredictable and costly global supply chain disruptions, predictive analytics offers companies a solution that allows for risk management by detecting and mitigating potential supply chain issues before they occur.

Predictive analytics tries to foresee potential disruptions by measuring metrics such as weather, geopolitical developments and supplier performance. Add-on technologies help businesses to design Plan Bs.

For instance, a global electronics manufacturer can reduce supply chain risk by analyzing geopolitical events and their effect on component supplies. Contingencies can be built and alternative suppliers can be approached in case there is a trade dispute. In that way, production could continue as normal, minimizing disruption and ensuring uninterrupted production.

Also Read: How Predictive Analytics Can Predict Supply Chain Success

To Sum Up

Predictive analytics can help businesses to make the most out of modern supply chains. Companies can boost their efficiency and reduce complexity in supply chains, customize their strategies according to customer demands and supply changes, and leverage analytics to make quick and effective decisions during challenging times.

Leverage predictive analytics with GEP. Learn more.