All About Supply Chain Analytics

Data and algorithms are used in supply chain analytics to help businesses manage risk, save money, and make the entire procurement process more efficient.

Fremont, CA: A company's supply chain is much more than a path from supplier to manufacturer to the retailer; it is a critical component of how efficiently it operates. Minor changes to the supply chain can have far-reaching consequences, both positive and negative. Rather than being reactive, supply chain analytics adds another layer of planning to the procurement process.

The following is a list of some of the most crucial supply chain analytics functions:

Supplier risk management considers company financial data, business credit scores and ratings, corporate family trees, and other factors to identify potential supply chain vulnerabilities.

Business data is frequently fragmented; supplier risk management tools consolidate it in one location. This could include outstanding debts, current liens, or ties to troubled parent companies. Visibility into these risks can help businesses anticipate problems before they occur, allowing them to avoid supply chain disruptions. For example, D&B Supplier Risk ManagerTM products enable companies to evaluate new partners or monitor vendors for signs of trouble.

Inventory Management and Demand Forecasting Align Supply and Demand, Lowering the Overhead Costs of Stocking Extraneous Items.

Sales figures from an e-commerce storefront in real-time can assist businesses in understanding seasonal trends in product purchases. In addition, the availability of machine components is used to predict when replacement parts should be ordered to keep an assembly line running. Analytics programs process these inputs through advanced algorithms to assist businesses in planning for the ebb and flow of supply and demand.

Suppliers Can Use Cost Modeling to Save Money on Their Procurement Expenses and Understand How Price Volatility Affects Them.

Raw material costs, transportation, and storage are all factors that influence product prices. In addition, commodity prices can be volatile, so buyers must also understand when and under

what conditions to buy. Cost modeling can also identify when upstream vendors are charging too much for their services and assist buyers in understanding the savings that could be realized by switching to a different supplier.