Analytics for Supply Chain

Supply chain management can be defined as the overall process that takes care of the flow of goods, information and funds or money across the entire chain i.e., from the raw material to the delivery of finished goods. It primarily includes the flow of information which centers on transmitting orders and updating status of delivery. Primary components of supply chain are planning, sourcing, making, delivery, and returning. It is curial for any organization to maintain transparency with the customers and help in deploying cost-effective solutions for the betterment of the service.

Supply chain analytics combines data from many applications, infrastructure, third-party sources, and emerging technologies to improve decision-making through out the supply chain management’s process. They are mainly used to improve risk management, increase planning accuracy, improve order management.

Let us discuss the different types of analytics in supply chain.

Inventory Management analytics: Effective inventory management analytics allows you to evaluate a large amount of data from previous sales and forecast future demand for your inventory while taking into consideration your company’s business seasons and production schedules.

Order management analytics : It provide organizations with comprehensive consumer insights, allowing them to make smarter decisions at every level of the process. Firms can easily improve their current order management plan to enhance profit margins and customer happiness by employing actionable information.

Warehouse Management analytics : The most important components in ensuring that the logistical flow is smooth and that client orders are fulfilled on time. Organizations utilize analytics not only to operate warehouse processes in IT systems, but also to optimise them by meticulously examining the varied data available.

Failure Analysis: The method of gathering and evaluating data to establish the reason of failure, usually with the objective of determining corrective measures or liabilities, is known as failure analysis.

Technologies like Blockchain, Graph analytics, Hyper automation are expected to play a big role in Supply chain Analytics.