The ability to make informed and rapid decisions is more critical now than ever for a business' supply chain (SC). Every day, millions of packages, products, and shipments move through the supply chain on a winding route to their final destination. One broken link could cost millions of dollars. We've seen the impact of this with COVID-19.

According to Bain & Co., building a more resilient SC can increase plant output by as much as 25% and lower operating and logistics cost by 22%, all while improving forecast accuracy by as much as 60%. I personally found these things to be true at both Apple and Harry's.

The financial implications are astounding. With so much money tied into inventory, production, and manufacturing, any SC that is not working robustly could break your business. Driving long-term success starts with knowing and optimizing the SC analytics of your operation. 

Types of Supply Chain Analytics

Supply chain analytics empower companies to make intelligent decisions based on relevant, real-time data. There are several different types of SC analytics your business can make use of.  Capturing the treasure trove of data produced through your everyday operations will inform your business decisions.

Descriptive Analytics

Descriptive analytics provide an easy-to-consume visualization of "what's happening now." It's like taking your car to the mechanic for an inspection - you'll find out what's going on under the hood, what needs to be tuned up, and what's running on all cylinders. Examples include average supplier lead time and the number of dollars invested in inventory, as well as other critical data points for optimal operational efficiency.

Predictive Analytics

Sometimes a visual inspection can lead to a highly probable prediction. For example, your mechanic may examine your brake pads and tell you that a serious accident is likely in the next 3,000 miles.  Enter predictive analytics. Like your mechanic, this data will present you scenarios that could take place -- both good and bad -- if current processes stay in place. In the supply chain, predictive analytics help you mitigate risk by forecasting what will happen in the future.

Prescriptive Analytics

Now comes the solution. With brake pads that are likely to cause an accident, your mechanic may advise to replace them immediately. Prescriptive analytics tell you how to fix things by providing organizational solutions to problems within the supply chain. By leveraging predictive analytics -- knowing the end result if a change is not made -- prescriptive analytics can help organizations come up with solutions like building a more effective supplier base before something breaks, optimize manufacturer lead time prior to orders being issued, or improve overall logistics productivity when the good is still being produced. This data will tell you how to achieve (or avoid) a given outcome.

Patterns and Insights Through Analytics

Supply chain analytics are the key to the resiliency of your SC. They enable you to predict outcomes and prescribe solutions in real time, ensuring goods are delivered on time and customers are kept happy. When it comes to supply chain optimization, the answer is always simple: Listen to the data.

 

Rodney Manzo is the founder of Anvyl, an end-to-end management and production tool and platform; he was named an AlleyWatch NYC E-Commerce Influencer in 2019.