It’s an understatement to note that we’re experiencing a challenging time for the supply chain. Regardless of industry or geographic location, companies are struggling with global supply chain disruptions that show little sign of abating. Added to this are the risks associated with reduced product life cycles, changing consumer preferences, increasing volatility and availability of resources, and heightened regulatory attention and enforcement. 

This is certainly a challenging environment for organizations to navigate, but the good news, according to a recent CIO piece, is that data analytics can help improve many supply chain operations. Read on for some examples of how analytics is easing chief supply chain woes: 

Enhancing Supplier Operations and Relationships 

Analytics allows companies to enhance their relationships with suppliers in numerous ways. For example, a better understanding of customer demand informs more accurate forecasting data, which in turn enables suppliers to improve order management. Using price indexes for materials such as lumber or packaging or for costs related to things like labor or transportation can help determine when increases are required, leading to more transparent communication with stakeholders affected by any increase.

Improving Prediction of Product Demand and Inventory Needs

Another key benefit of analytics is its ability to better predict product demand and inventory needs. Organizations can deploy machine learning algorithms to drill into forecasting demands at the individual city level and optimize inventory accordingly. This allows companies to get products closer to the customers who want them and also reduce shipping costs where possible. 

Proactively Preparing for Equipment Failure 

Breakdowns and maintenance are just a fact of life when managing a logistics fleet. The costs associated with this inevitability, however, can be significantly reduced by using equipment-failure analytics. Gathering data on recent maintenance and the condition of vehicles in the fleet can help companies predict the lifespan of individual components, schedule maintenance, and also anticipate issues before they result in equipment failure. 

Providing Insight into Market Trends 

Companies can also use analytics to obtain a holistic understanding of variables such as transportation costs and identify the best path forward. For example, perhaps the organization can reduce costs by shipping products on different days of the week or by using alternate routes.

Head over to CIO for more on the above and other examples of how data analytics can help organizations get a handle on the current supply chain challenges.