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Use Case: Integrated Supply Chain Planning

Problem Overview

Our case study examines a beverage company that produces three types of bottled water: spring water, sparkling water, and flavored water. The company distributes these products to 100 different markets across the United States. Each product has its own demand distribution, which varies geographically, requiring careful planning to ensure customer demand is met efficiently.

The company operates multiple manufacturing facilities, each with its own production limits and capacities. These facilities are responsible for producing and distributing the three water products. The company's goal is to balance production with distribution, minimizing costs while meeting all market demands.

Demand Heatmap
Demand heatmaps for three water products, with red dots marking production facilities capable of manufacturing each product.

Objective: The task is to create a comprehensive supply chain plan that integrates three key processes:

  1. Material Requirements Planning (MRP) – Determining the raw material needs for production.
  2. Master Production Scheduling (MPS) – Planning production based on demand and facility constraints.
  3. Distribution Requirements Planning (DRP) – Optimizing the transportation of finished products to the markets.

The final plan must:

  • Meet customer demand for each product.
  • Satisfy production and capacity constraints for each manufacturing facility.
  • Minimize overall costs, including production, transportation, and inventory holding costs.

Given Data:

  • Demand by Product and Market: Demand data for each of the three water products (spring, sparkling, and flavored) across the 100 markets.
  • Facility Constraints: Production capacity data for each manufacturing facility, including the number of products that can be produced, production rates, and any limits on production quantities.
  • Transportation Data: Information on transportation routes and costs associated with shipping products from manufacturing facilities to the 100 markets.

Download Sample Data

Using Convect AI's IBP Software

To create a comprehensive supply chain plan for your beverage company using Convect AI’s Integrated Business Planning (IBP) software, follow the steps below:

Step-by-Step Instructions

  1. Sign in to Convect AI Navigate to https://flow.convect.ai and sign in with your credentials.

  2. Open the IBP Application Once signed in, find the Integrated Business Planning app on the dashboard. Click to open it and begin setting up your supply chain plan.

  3. Create a New File and Upload Data

    • Click the Create File button.
    • Fill out the necessary information, such as the file name (e.g., “Beverage Company Supply Chain Plan”).
    • Upload the sample data file containing your demand, production, and transportation data.
    • Once you've filled in the required information, click the Create button.
    • Wait for the data import process to complete, which may take a few moments.

  4. Examine the Imported Data After the data import is finished:

    • Open the Input View to review the uploaded data. Make sure that the data is accurate.
    • If you notice any discrepancies, adjust the data before proceeding.

  5. Start the Optimization Process Once the data is verified, click the Solve button to begin the optimization process. The software will calculate the best production, material procurement, and transportation plans to meet the given demand while minimizing costs. The process may take a few minutes depending on the size of the data and complexity of constraints.

  6. Review the Output and Visualization After the optimization process is completed:

    • Open the Output View to see the detailed results, including production, transportation, and inventory plans.
    • For a more intuitive understanding, click the Graph View to see built-in visualizations of the output data, such as demand fulfillment, production schedules, and transportation routes.

Understanding the Output

The results from Convect AI’s IBP software include several key tables that provide a holistic view of the entire supply chain plan:

  1. Master Production Schedule (MPS) This table details the production plan for each site, specifying:

    • Site Name: The manufacturing facility where production will occur.
    • Production Line: The line assigned to produce specific products.
    • Product: The specific product being produced (e.g., Spring Water, Coconut Water).
    • Quantity: The number of units to be produced, based on demand and capacity constraints.

  2. Material Requirements Planning (MRP) The MRP table shows the requirements for raw materials (ingredients) needed to fulfill the production plan. It details:

    • Product: The raw material needed for production (e.g., water, bottles).
    • Site Name: The production facility where the raw material is required.
    • Required Quantity: The amount of each ingredient needed at each production facility.

    This ensures that the right materials are available in the correct quantities to avoid production delays.

  3. Transportation Plan This table outlines the logistics of moving finished products from production plants to markets. It includes:

    • Origin Site: The production facility from which the product will be shipped.
    • Destination Site: The market where the product will be delivered.
    • Quantity: The amount of product to be shipped.

    In some cases, products may be shipped between plants before reaching their final destination, especially if it's more cost-effective to distribute products from one facility to another and then to nearby markets.

  4. Inventory Output The inventory table summarizes the ending inventory for both finished goods and raw materials after production and distribution are completed. It includes:

    • Product/Material: The item being tracked (finished product or raw material).
    • Ending Inventory: The remaining inventory at the end of the planning period.

    This helps you understand if any excess inventory is being held and allows you to make adjustments for future production cycles.

  5. Demand Output This table reports how much of the customer demand has been met for each product, showing:

    • Product: The specific item requested by customers.
    • Demand Fulfilled: The portion of the demand that was successfully fulfilled.
    • Shortage: If there is a gap between demand and supply, the shortage amount will be listed.

    This ensures transparency in understanding whether all customer orders have been satisfied and where any shortfalls may have occurred.

Understanding the Optimization Algorithm

Convect AI’s Integrated Business Planning (IBP) software employs advanced optimization algorithms to minimize total supply chain costs while satisfying demand. Let’s take an example from the Spring Water product flow to illustrate how the algorithm works.

Product Flow Map
The product flow map for Spring Water.

In the product flow map, we can see that all California markets except San Diego are served by the Salem, Oregon manufacturing plant. Surprisingly, the San Diego market is served by the Coppell, Texas plant, even though it is farther away. This choice by the algorithm may seem unusual, but a closer look at production and transportation costs explains the decision.

Production and Transportation Costs Breakdown

The Salem, Oregon plant has two production lines, B3 and B25, that can manufacture Spring Water. The capacity of line B3 is fully utilized, while line B25 has an extraordinarily high production cost of $910 per unit. In contrast, the Coppell, Texas plant has a production line, B32, that can produce the same product at a much lower cost of $243 per unit.

The Input View of the Production Policy table, showing four production lines capable of producing Spring Water.

The optimization algorithm compares two scenarios: producing the required 275.81 units at Salem B25 versus Coppell B32, and considers the total cost, including both production and transportation.

Here’s a comparison of the two scenarios:

Scenario Production Quantity Production Cost (per unit) Transportation Cost (per unit) Total Production Cost Total Transportation Cost Total Cost
Salem B25 275.81 $910 $724.89 $250,987.10 $199,931.91 $450,919.01
Coppell B32 275.81 $243 $939.77 $67,021.83 $259,197.96 $326,219.79

Why Did the Algorithm Choose Coppell?

Even though the transportation cost from Coppell to San Diego is higher than from Salem, the production cost at Coppell is significantly lower, which results in a much lower total cost.

  • Total cost of Salem B25: $450,919.01
  • Total cost of Coppell B32: $326,219.79

The optimization algorithm, which aims to minimize the total cost, selects Coppell B32 for production and distribution, as its total cost is over $124,000 lower than Salem’s.

Conclusion

Convect AI’s IBP software evaluates all possible production and transportation combinations, choosing the option that minimizes the overall cost while ensuring demand is met. In this case, even though Coppell is farther from San Diego, the lower production cost at the Coppell facility justifies the higher transportation expense, leading to significant cost savings for the company.