Supply chain analysis is key for any business looking to maximize efficiency. As a former production line worker who became a lean management expert, I can attest to the power of knowing your supply chain and how it can improve efficiency and profitability.
You’ll learn about supplier relationships, inventory management, and logistics that you can use to operate a more efficient business.
Supply Chain Analysis: Definition and Importance
A supply chain analysis is a deep dive into the entire process of moving products or services from suppliers to customers. You analyze each step of the supply chain to identify inefficiencies, areas for improvement, and potential risks. The main goals of a supply chain analysis are to reduce costs, increase efficiency, and improve customer satisfaction.
Today, conducting a supply chain analysis is essential in a competitive business landscape. Companies that are really good at supply chain analysis have a significant competitive advantage. They can react more effectively to changes in the market, reduce operating costs, and provide more value to customers.
I’ve personally seen supply chain analysis work wonders for businesses. Here are the benefits:
- Lower operating costs
- Better inventory management
- Higher customer satisfaction
- More effective risk management
- Greater agility and ability to react
- Stronger supplier relationships
- More sustainability
You’re probably wondering how these benefits apply to your business. These benefits ultimately drive significant improvements in your profits and overall competitiveness.
Components of Supply Chain Analysis
It all starts with supplier analysis and evaluation. You need to evaluate the performance, reliability, and cost-effectiveness of your suppliers to ensure you’re working with the best suppliers.
Next is inventory management analysis. You have to find the sweet spot of ensuring you have enough inventory on hand to meet demand, but not too much that you tie up capital in excess inventory.
Logistics and transportation analysis is all about optimizing the movement of products. This may include optimizing shipping routes, selecting the right carriers, and warehousing location strategies.
Demand forecasting and planning are equally as important. If you don’t accurately predict demand, you may experience stockouts or tie up capital in too much inventory. This is a complex aspect of the business, but it’s critical to operate smoothly.
Then, you need to analyze your production and manufacturing processes. The goal is to identify any inefficiencies and bottlenecks that may be lowering your production speed.
Each of these requires a deep analysis. And they’re all intertwined, so if you make an improvement to one, it often impacts another.
Analytical Techniques for Supply Chain Analysis
Process mapping and value stream mapping are excellent tools that create a visual representation of your supply chain, making it easier to see waste and inefficiencies.
Performance metrics and KPIs measure success. Some of the most important include:
- On-time delivery rate
- Inventory turnover
- Order fulfillment accuracy
- Cash-to-cash cycle time
- Total supply chain costs
Data visualization helps make sense of complex data and can reveal patterns and trends you might miss when looking at raw data.
Statistical analysis offers more in-depth insights and allows you to understand relationships between different variables in your supply chain.
Cost-to-serve analysis calculates the total cost to serve a customer with products or services and helps you determine which customers and products are most profitable.
Network optimization modeling uses advanced algorithms to design the most efficient supply chain network, including facility locations, inventory levels, and transportation routes.
These tools give you a comprehensive toolkit to analyze your supply chain and really dive deep into your operations to find opportunities to improve them.
Types of Analytics
There are five primary supply chain analytics: descriptive, diagnostic, predictive, prescriptive, and cognitive analytics. Each analytics has a different objective and provides different insights.
• Descriptive analytics tells you what happened in the past. It uses historical data to determine trends and patterns. This analytics is helpful for understanding how you are currently performing.
• Diagnostic analytics answers why something happened to you. It digs deeper into the data to determine the causes of any issues you’re experiencing in your supply chain.
• Predictive analytics forecasts what is likely to happen next. This is invaluable for planning and managing risk effectively.
• Prescriptive analytics takes the forecast one step further and tells you what actions to take. This analytics provides decision support for complex supply chain problems.
• Cognitive analytics is the most advanced. This analytics leverages AI and ML to continue learning and improving forecasts and recommendations.
Here’s a comparison of supply chain analytics:
| Analytics | Focus | Question | Complexity |
|---|---|---|---|
| Descriptive | Past | What happened? | Low |
| Diagnostic | Past | Why did it happen? | Medium |
| Predictive | Future | What might happen? | High |
| Prescriptive | Future | What should we do? | Very High |
| Cognitive | Future | How can we continue to improve? | Extremely High |
Each analytics is a level more advanced than the previous analytics. As you move up the chain from descriptive to cognitive analytics, you gain more advanced insights and decision-making capabilities.
Essential Software for Logistics and Distribution Management
• Enterprise Resource Planning (ERP) systems are the backbone of most supply chain management efforts. These systems integrate various business processes and offer a centralized data store.
• Advanced Planning and Scheduling (APS) tools optimize resource allocation and production scheduling. Using an APS tool can optimize processes and reduce costs.
• Business Intelligence (BI) platforms help you make sense of raw data and often offer excellent data visualization capabilities.
• Data warehousing and integration tools are essential to combining data from different sources to create a single source of truth for your supply chain analysis.
There are also several emerging technologies making a significant impact.
• Artificial Intelligence and machine learning enable predictive and prescriptive analytics.
• The Internet of Things (IoT) provides real-time visibility into your supply chain.
Selecting the right tools to use depends on your specific needs and budget. When evaluating tools, consider factors like scalability, ease of use, and integration with other tools.
Evaluating Procurement and Distribution Networks
A comprehensive supply chain analysis includes the following steps:
- Define objectives and scope
- Data collection and preparation
- identify key performance indicators
- Map and analyze supply chain processes
- Identify bottlenecks and inefficiencies
- Develop improvement strategies
- Implementation
- Monitoring
Data collection and preparation is often the most time-intensive step. You must gather data from various sources and ensure it’s accurate and consistent.
Key performance indicators are important, as you’ll use these to measure the success of your analysis and any subsequent improvements.
Analyzing the supply chain processes is where the rubber meets the road. You’ll go through each step of the process with a fine-tooth comb to find areas where time, money, or resources are wasted.
Identifying bottlenecks and inefficiencies in the supply chain is the real value of the analysis. There you’ll have an opportunity to make a significant improvement. This might be in inventory management, transportation, or a specific production process.
Developing improvement strategies is where the analysis becomes more of an art than a science. You must creatively think through potential solutions and then carefully evaluate each to understand the likely impact, cost, and feasibility.
Implementation and monitoring is the last critical step. Here you’ll track the results of your change and be prepared to make additional changes.
Common Obstacles in Logistics and Distribution Management
Supply chain analysis is a complicated and difficult task. Many businesses face similar challenges when conducting supply chain analysis.
• Data quality and integration problems are often the most common. Different departments or systems may use different data formats or have different definitions, making it nearly impossible to piece the story together.
• A lack of visibility throughout the supply chain is another frequent complaint. You may struggle to follow products or data as it moves through different steps and organizations.
• Global supply networks introduce another layer of complexity. You need to juggle different cultures, regulations, and time zones.
• Market conditions change frequently, making your analysis outdated almost instantly. You need to be prepared to pivot and adjust your strategies consistently.
• Resistance to change in organizations prevents people from adopting your findings. Even if you can prove a better way of performing a task, people may choose not to switch from the current process.
• Limited resources and expertise is another hurdle. Not all organizations have the talent or tools required to conduct supply chain analysis in the first place.
Understanding these challenges is the first step to overcoming them. With the right strategy and tools, you can solve each of these challenges when analyzing a supply chain.
Best Practices
• Defining clear objectives and scope is key. You should have a clear understanding of what you want to accomplish and which areas of your supply chain you’re analyzing.
• Ensuring data accuracy and reliability is the foundation. If you don’t have accurate data, your analysis is useless. Establish data validation processes and conduct regular data audits.
• Promoting cross-functional collaboration is also critical. Supply chain analysis often requires input from multiple departments. If there isn’t open communication and collaboration, it will be difficult to analyze your supply chain effectively.
• Using more advanced analytics techniques allows you to uncover deeper insights. Don’t hesitate to use more sophisticated tools or methods if they deliver valuable insights.
• Continuously monitoring and updating your analysis is important. Your supply chain is constantly changing, so your analysis should change with it. Regularly reviewing and updating your analysis is a must.
• Aligning your analysis with the broader business strategy ensures that any improvements you make to your supply chain contribute to the broader objectives of your company. And if you’re aligning your work with the company goals, it’s easier to get support and resources.
Implementing these best practices will ensure your supply chain analysis is more effective and have a greater impact. Just remember it’s a journey of continuous learning and improvement.
To Conclude
Supply chain analysis is one of the most effective strategies to optimize business operations. By evaluating the entire chain from suppliers to end customers, companies can identify inefficiencies and areas for improvement.
The key to supply chain analysis is using the right analytical methods and tools. Also, effective supply chain analysis is a continuous journey. It requires dedication, cross-functional collaboration, and a readiness to change. When executed properly, supply chain analysis can result in substantial cost savings, higher customer satisfaction, and a competitive advantage.
