A basic supply chain for an enterprise comprises simple sequential and linear process networks connecting various vendors for resources needed to produce and distribute traded goods. Given the complexity of the demand market and the variability of consumer preferences, supply chains have recently evolved into highly dynamic processes. A network usually supports a two-way interconnection between various links. When a simple problem in a single linear supply trail can disrupt the whole chain, the same damage can become more significant in a network of supply chains. Supply chain network optimization software finds an optimal solution by combining different factories and distribution centers in the same value chain. Surprisingly, only 22% of companies are working with a proactive supply chain network in 20221.
Proper network optimization is necessary for modern supply chain enterprises as it helps curb operating costs and deliver stellar customer experiences. Since a network includes an intricate web of resources, technologies, and facilities, optimization of the same raises the urgency for advanced analytical solutions. Supply chain network optimization tools leverage the power of Big Data, AI, and IoT for optimization and scalability.
Simply put, network optimization creates a crystal view of the organization’s supply chain to unearth inefficiencies and bottlenecks. Such data analytics are used to define ways to optimize existing processes for curbing various operating costs and ensuring each node in the network performs seamlessly.
Traditional linear value chains are not designed to meet the increasing complexities of the new-age economy. Complex hierarchies, rigid supply chains, and information silos have limited partner reach, persistent out-of-stocks, higher costs, latency, and lost opportunities. More importantly, conventional value chains are territorial in nature; hence, they are inherently rigid. It creates supply chain inefficiencies and limits any possibility for growth. And as mentioned, information silos impact supply chain planning, which results in delayed execution of critical actions.
Proper network optimization connecting critical parties in a non-hierarchical manner eliminates information silos. Furthermore, by leveraging new-age technologies like Artificial Intelligence in shared data, networks are transformed to become more cognitive and responsive to sudden disruptions or change.
For instance, AI-enabled supply chain network optimization software solutions like TradeEdge Network create opportunities for swift actions. It connects businesses in a peer-to-peer network accommodating prompt responses to products, services, and information needs. In addition, their multi-tenant architecture allows many-to-many connectivity, fostering a multi-enterprise network with a global reach.
Supply chain network optimization enables companies to gain an edge over the competition, discover new partners and products at scale, transform complex data into meaningful demand signals, and do much more. The network supports a 60-70% improvement in partner network visibility, a 12-15% reduction in out-of-stock scenarios, and many such enhancements.2
For example, one of EdgeVerve’s clients, a leading beverage manufacturer, could meet market demands quickly and grow sales by 2% with the help of the network-based approach. They leveraged the Business Network platform, TradeEdge Network, to connect with their partner retailers and distributors for enhanced visibility. As a result, they could move inventory quickly in the presence of restrictions by reaching out to another vendor. A similar connection with their suppliers allowed them to continue manufacturing without facing supply shortages
A purposeful network design is needed for a unified cognitive business network to fulfil its objectives effectively. The network should:
In network optimization business constraints can range from a limited number of facilities to fixed costs for each process. And the same constraints act as datasets for AI-powered supply chain network optimization software solutions to decide the most feasible strategy to create a more seamless channel of the demand-supply network. These network constraints could be:
However, every business is unique, and so are the requirements of its supply chains. Hence, in the absence of predetermined values, custom constraints are created for the baseline to further the comparative analysis and identify solutions for network optimization.
Specific supply chain network optimization tools have custom constraints, allowing users to create the best optimization solution for driving maximum profit.
Usually, supply chain complexities arise from changing dynamics that the industry is subjected to. Hence, the requirements of network optimization vary, as mentioned before. Some consider tech implementation a requisite for a growth strategy, while others think improving business processes is the key to success. Regardless of the requirements, supply chain network optimization brings manifold benefits to enterprises.
Reduce waste: Resource wastage is probably the most significant challenge enterprises face; some are born from poor demand forecasting and inventory planning. Supply chain network optimization tools help businesses discover areas where waste is prevalent and define strategies to curb them.
Reduce unnecessary costs: Some supply chain areas can raise unnecessary expenses if the network is left unoptimized. Proper network optimization pinpoints those areas so enterprises can identify ways to prevent excessive spending.
Optimize transportation: Higher transportation costs impact the product’s final price, which could have been less if the distribution network had been efficient and optimized. Supply chain network optimization aid enterprises find the best shipping methods or cost-effective distribution channels. This leads to reasonable product prices and higher customer satisfaction.
Enhance quality control: Quality control is harder in the later stages of the supply chain, soiling the brand’s reputation in the market. Proper optimization of supply chain networks provides granular insights about the performance of various suppliers so companies can choose the best one that upholds the quality requirement of their brand.
Mitigate risk and planning: Data analysis supported by supply chain network optimization software provides an eagle-eye view of the changing business dynamics. Enterprises can harness those insights to plan accordingly and stay future ready.
Improve visibility and flexibility: Supply chain network optimization tools enhance visibility by capturing data from different parts of the network and helping enterprises to take steps to remediate challenges. Further, optimization improves process flexibility, allowing businesses to meet unexpected changes.
Supply chain network optimization software leverages modern technologies to help enterprises understand how the demand-supply value chain works. Such insights are essential for addressing various challenges and curbing unnecessary costs, with a focus on enhancing customer experiences.