Supply chain analytics uses data and advanced analytics to analyze and optimize various aspects of the supply chain, including procurement, manufacturing, and logistics. The main goals of supply chain analytics are to improve efficiency, lower costs, and increase revenue. Supply chain analytics can also provide real-time insights that help businesses adjust to changing conditions quickly and effectively.

Using supply chain analytics, you can ask the right questions, find the right answers, and realize the benefits of a well-optimized supply chain.

Frequently Asked Questions

There are four primary types of supply chain analytics: descriptive, diagnostic, predictive, and prescriptive. These advanced analytics techniques may sound complex, but you should find this simple business-level overview of what each type reveals with examples to be straightforward.

What events have happened?

Descriptive analytics mines historical data to identify trends and relationships. Examples include identifying excess inventory and late deliveries.

Why did these events happen?

Diagnostic analytics examines trends and correlations between variables to determine the root cause of a supply chain event. This type of analytics can diagnose events such as why there was too much stock and why deliveries were late.

What might happen in the future?

Predictive analytics uses supply chain data to predict future outcomes, such as forecasting demand or anticipating possible transportation bottlenecks.

What should we do?

Prescriptive analytics uses data to prescribe the best course of action, such as decreasing production or using alternative shippers.

Benefits of Supply Chain Analytics

Answering these types of questions provides a myriad of benefits. Below are just a few of them:

• Improved efficiency and cost savings: Through using supply chain analytics to streamline processes, reduce waste and optimize operations. Examples include optimizing routes and schedules, reducing manufacturing downtime, using less fuel and better sourcing of materials, and many more opportunities.
• Increased visibility and transparency: Allow organizations to identify potential problems early on and take proactive measures to address them.
• Better risk management: By highlighting interdependencies and uncovering areas along the supply chain where disruption can lead to failure.
• More accurate planning: Gain better insight into sourcing, manufacturing, and distribution to meet customer demand.
• Better customer experience: Real-time insights into customer demand can improve how you manage inventory levels and ensure that products are in stock when customers want them.
• Less environmental impact: Normalize analyzing energy consumption, waste, and other sustainability factors.

Getting Started

Supply chain analytics provides a data-driven way for businesses to optimize their operations, with its ability to provide real-time visibility, highlight risks, reduce costs and inefficiencies, better plan for customer demand, improve the customer experience, and reduce environmental impact.

To get started, you’ll need the right data platform to run your descriptive, diagnostic, predictive, and prescriptive supply chain analytics. The Avalanche Cloud Data Platform can help you transform your supply chain, by simplifying how you connect, manage, and analyze data. Using the Avalanche platform, you can easily aggregate and analyze massive amounts of supply chain data to gain data-driven insights in real-time, for optimizing supply chain operations.

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