Future of Operations & Supply Chain Management
“Analytics plays a vital role in supply chain management due to the complexities present and increasing competition and customer expectations effecting the company’s cost and profitability.”
Traditional supply chain are out casted due to mixing of global operating systems, pressure of pricing and increasing customer expectations. Wastage in supply chain are created due to recent economic impacts such as rising fuel price rise, global recession, there is a scarcity in supplier bases or moved off-shore, and increase in competition between low-cost outsourcers. There is need for data analytics to overcome the challenges & minimize the wastage.
Data Analytics is the practice of gathering data and drawing inferences and conclusions about the information. This helps a business entity to make better decisions and also to verify with the created models pertaining to the data. Supply chain analytics aims at improving the operational efficiency and effectiveness through data driven decisions at strategic, operational and tactical levels. It enables a business to encompass sourcing, manufacturing, distribution and logistics.
Analytical approach of supply chain deliver growth in revenues, improve margins, manage working capital in a better way, and enhance the control points across the supply chain. Precisely saying, helps in identifying the bottle necks and risks, potential new opportunities and helps in adapting to emerging supply chains & increasing the working capital. Below flow chart gives the components of a supply chain.
The analytical process can be broken down into Working Capital analytics, Inventory Analytics, Revenue & Expense analytics, Control analytics, Logistics analytics and the most important part “Supply Chain Network Optimization”.
Working Capital analytics focused on end to end supply chain inventory, it helps in freeing up locked capital and thus improving cash flow.
Inventory Analytics determines the right safety stock levels for
Traditional supply chain are out casted due to mixing of global operating systems, pressure of pricing and increasing customer expectations. Wastage in supply chain are created due to recent economic impacts such as rising fuel price rise, global recession, there is a scarcity in supplier bases or moved off-shore, and increase in competition between low-cost outsourcers. There is need for data analytics to overcome the challenges & minimize the wastage.
Data Analytics is the practice of gathering data and drawing inferences and conclusions about the information. This helps a business entity to make better decisions and also to verify with the created models pertaining to the data. Supply chain analytics aims at improving the operational efficiency and effectiveness through data driven decisions at strategic, operational and tactical levels. It enables a business to encompass sourcing, manufacturing, distribution and logistics.
Analytical approach of supply chain deliver growth in revenues, improve margins, manage working capital in a better way, and enhance the control points across the supply chain. Precisely saying, helps in identifying the bottle necks and risks, potential new opportunities and helps in adapting to emerging supply chains & increasing the working capital. Below flow chart gives the components of a supply chain.
The analytical process can be broken down into Working Capital analytics, Inventory Analytics, Revenue & Expense analytics, Control analytics, Logistics analytics and the most important part “Supply Chain Network Optimization”.
Working Capital analytics focused on end to end supply chain inventory, it helps in freeing up locked capital and thus improving cash flow.
Inventory Analytics determines the right safety stock levels for