Multiple factors contribute to the challenges faced by companies in optimizing their supply chain networks. These include complex supply chain structures, inadequate data analysis capabilities, outdated supply chain software, and a missing end-to-end overview of the supply chain. Most supply chain software is designed for transactional efficiency and often needs more practical supply chain optimization tools.
Organizations require a solution that provides a comprehensive view of the supply chain network to overcome these challenges. This solution should identify the best possible option from several potential solutions based on the organization’s objectives.
Supply Chain Network Optimization Explained
Network optimization supply chain, also known as supply chain network design, is a process that creates a complete representation of an organization’s supply chain. It typically involves building a model that accurately mirrors the supply chain, with formulas that simulate actual transactions and transformations.
Depending on the complexity of the organization, this process may necessitate the use of sophisticated mathematical and analytical supply chain software to evaluate alternatives and pinpoint the optimal solutions.
Understanding the Process and Its Functioning
The process of supply chain network design systematically aims to identify the ideal mix of facilities, suppliers, and products through mathematical modeling. Unlike the spontaneous growth process seen in many organizations, this approach is intentional and planned.
The initial step involves defining the organization’s business objectives, including target markets, growth plans, and financial goals. Other relevant factors could be customer service levels, pricing, competition, and cash flow.
These considerations shape the subsequent supply chain network processes, with the aim being identifying the optimal blend of supply, production, and distribution costs. This analytical process eliminates subjectivity and bias.
Frequency of Supply Chain Network Optimization
The frequency of supply chain network optimization depends on two key aspects. One aspect is the presence of indicators suggesting the need for optimization, such as:
- A significant amount of time since the last optimization
- Decreasing company margins
- Changes in product portfolios
- Mergers and acquisitions
- Unacceptable inventory levels and costs
The second aspect to consider is the effort and time required to undertake this exercise, which is closely linked to how the supply chain is modeled. Manual modeling using spreadsheets is labor-intensive, error-prone, and resource-heavy. In contrast, modeling using simulation software is easier to repeat and refine as the bulk of the work involved in preparing and populating the model is already done.
Despite practical considerations like the effort required, the fast-paced changes in today’s business environment suggest that supply chain network optimization should ideally be carried out as frequently as feasible.
Internal or External Handling of Network Optimization
Many organizations opt for external consultants to optimize supply chain networks to reduce the burden on internal staff. While this is a practical solution, it has drawbacks, such as
- The consultants’ lack of in-depth business knowledge
- The need for substantial involvement of internal personnel
- Potential resistance to recommendations
- Time and cost implications
- Less flexibility
On the other hand, some organizations choose to have their staff perform supply chain network optimization, despite the increased staffing requirements. This approach offers several benefits, including internalizing knowledge and expertise, lower costs, greater flexibility, and the possibility of conducting optimization more frequently.
Significance of a Holistic Perspective on the Supply Chain
The holistic or end-to-end view of the supply chain is paramount for operational efficiency. It encompasses all aspects, from procurement to manufacturing, sales, and final product delivery. Using disparate software suites for these functions can create silos, hindering optimization.
Integrated solutions like ERP and S&OP processes can offer a unified perspective, facilitating network tracking from start to finish. However, traditional S&OP often overlooks financial aspects, focusing mainly on production units and sales volumes.
Advanced analytics offer a solution to the complex task of analyzing supply chain networks. Prescriptive analytics use advanced modeling techniques to create a realistic supply chain network model, enabling organizations to make data-driven decisions. These models consider constraints, operational limitations, and strategic goals, ensuring proposed solutions are feasible and adaptable to changing organizational realities.
