Adopting a Data-Driven Approach to Supply Chain Management

The modern supply chain is increasingly complex and global. For businesses, that means it’s becoming much more challenging to identify potential vulnerabilities in the supply chain, eliminate bottlenecks, and quickly respond to supply chain disruptions. Fortunately, new information sources — like data from IoT devices — make it possible to take a more data-driven approach to supply chain management.

Learn what it means to build a data-driven supply chain management strategy — and how businesses can adopt this approach.

The Basics of a Data-Driven Supply Chain Strategy

The data-driven approach to supply chain management takes advantage of new data sources to help companies manage increasingly complex and global supply chains. In many cases, that data is an aggregate of various traditional and nontraditional sources. Some modern companies also use advanced tools — like artificial intelligence-powered big data analysis — to break down more complex datasets. For this reason, data-driven approaches require investment in analytical tools and data collection.

Traditional data may look like digitized shipping manifests and sales data that, when aggregated, can show how a company is sourcing materials, transporting goods, and fulfilling customer orders.

Nonconventional sources are also valuable. For example, some logistics companies use IoT sensors attached to product containers that track information like humidity, acceleration, vibration, and temperature as goods move from one location to another. That kind of information can help businesses reduce damage, minimize delays, and identify bottlenecks in the supply chain.

A data-driven approach is only as useful as its data’s breadth and quality. Without comprehensive datasets — that come from various sources and directly relate to problems supply chain managers want to solve — the approach won’t work. 

For this reason, a data-driven strategy will typically also require companies to continuously acquire new supply chain data. That information will get fed back into the system — enabling better forecasting and analysis to help identify further process improvements.

Adopting a Data-Driven Approach to Supply Chain Management

In the early planning stages, a business will typically identify what data it has access to and outline specific goals that it will use data to achieve. 

These goals may be hard metrics or KPIs the business wants to improve — like perfect order rate, cash-to-cash cycle time or on-time shipping rate. You may also be able to use data to identify suppliers that may be vulnerable to disruption, or otherwise improve your business’ ability to analyze risks and respond to supply chain threats.

No matter what the goal is, you must have something clear and specific to work toward. A well-defined objective will help track success and evaluate data use to drive supply chain management.

Next, business leaders will need to choose how to gather and analyze data. Most large companies use advanced enterprise resource management systems or similar technology to manage data collection, storage and analysis. The same technology can be useful in overseeing a business’ supply chain.

Some organizations may also develop proprietary in-house data-driven tools and algorithms to help collect and analyze data in a way that fits their specific needs.

Once a business has a process to collect and analyze data, they can use this new information to review their supply chain management strategy and make necessary adjustments. Over time, by continually making changes and pulling in new data, the company can achieve its supply chain management goals.

How Businesses Can Make Data Central to Their Supply Chain Strategy

New data sources and the economy’s digital transformation mean that most businesses have access to vast stores of data, if they know where to look. This information can be invaluable for creating data-driven management strategies — like ones that will help businesses manage their supply chain.

Editor’s note: Interested in staying up-to-date on all of the cutting edge topics in data science, including how to implement data-driven approaches in your industry? By subscribing to our Ai+ Training Platform, you gain access to new workshops and training sessions every week, meaning you’re never stuck behind.

Shannon Flynn is a tech writer and Managing Editor for ReHack.com. She covers topics in biztech, IoT, and entertainment. Visit ReHack.com or follow ReHack on Twitter or to see more of Shannon’s posts.