Network optimization is the process of finding the optimal combination of facilities, factories, suppliers, products, and distribution centers in the supply chain to ensure the highest level of service for customers at a minimal cost. It is the art and science of designing a quantitative, strategic, and holistic view of the organization’s end-to-end supply chain.
The network optimization approach uses numerous pieces of information to build a supply chain network design. They are as follows:
Companies should know how to handle changes to maintain logistics operations at maximum productivity and profitability to stay ahead of the competition. A wide array of elements determine the need for network optimization. They are:
Acquisition and mergers
Inventory
Operational inefficiencies
Uncertainty
Carbon footprint reduction
Inability to keep up with diverse customer needs
Growth and expansion
Consolidation and Deconsolidation
New markets
Volatile markets
Fragile supply chain network
Formation of new customer segments
Sourcing
New Product lines
With rising competitive pressure, market volatility, and increasing raw material costs today, network optimization has become more important than ever. Here are the factors that emphasize the need for network optimization. Minimizes supply chain costs
Network optimization creates savings on all levels from small regional connections, national systems, to global, international supply chains. It enables a company to minimize the cost of operations drastically. The decrease in supply chain costs leads to increased profits.
A well-optimized network with warehouses and production sites helps a company efficiently communicate with its clients. It offers them more flexibility to fine-tune their supply chain operations and meet unexpected changes in the market.
A proper network optimization tool enables businesses to undertake what-if scenario analysis effectively. It helps them understand the impact of removing, adding, or expanding the manufacturing centers, warehouses, and distribution centers. It supports them to do a large set of geospatial visual simulations of supply chain networks and configure them.
Network optimization helps companies guard against the failure arising from unpredictable changes in logistics operations. Its what-if analysis helps them analyze all risks and their impacts on logistics operations, financial results, and service levels. Overall, they enable businesses to develop their supply chain resilience.
A network optimization tool helps businesses understand the organization’s growth potential based on various business factors. It enables them to identify potential growth and offers hard data to prepare for expansion plans. It also helps them have backup plans when the existing methods do not go their way.
An effective network optimization tool helps companies develop a well-functioning supply chain network design for smooth operations. It enables businesses to consolidate manufacturing and distribution networks after mergers and acquisitions quickly. It helps them to promptly realize Return on Investment (ROI) and minimizes the waste of company resources.
Network optimization helps businesses source products based on total supply chain cost analysis. It minimizes inventory costs and reduces the supply chain surplus for the products leading to better economies of scale. It makes way for effective risk-sharing apart from increased forecasting and planning efficiency for goods.
An optimal network design has become necessary to achieve an efficient supply chain that is flexible enough to respond to changing market conditions. Businesses should focus on improving their network optimization process to keep costs in control and maintain their flexibility.
With its powerful digital twin, Locus network optimization tool enables businesses to visualize and optimize their supply chain networks. It helps them build a sound network design with simulated multiple real-time scenarios. It supports them to strategically plan supply chain operations for small, medium, and long period goals based on constraints, risks, and costs.
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