One-Click Supply Chain: Integrated Demand Planning & Inventory Control

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Overview of the One-Click Supply Chain Model

Kunal Jetta, a demand planner and inventory controller, presents an integrated supply chain model that synchronizes demand planning, sales and operations planning (S&OP), and inventory control. This model is designed for manufacturers of perishable products such as juices, shakes, and yogurts distributed across multiple global regions including Africa, Middle East, North America, Asia Pacific, Australia, New Zealand, Europe, Indian subcontinent, and Latin America.

Demand Planning and Forecasting

  • Demand-Driven Forecast: The forecast is based on actual orders sold during a specific period combined with end-of-month back orders that were unfulfilled, ensuring a realistic demand-driven approach.
  • Forecasting Method: Utilizes exponential smoothing with an alpha value of 0.3 to generate statistically sound forecasts. For a deeper understanding of this technique, check out Mastering Linear Programming: A Step-by-Step Guide to Graphical Solutions.
  • Multi-Level Analysis: Forecasts can be toggled between product level, region level, and product-location combinations for granular insights.
  • Error Metrics: Absolute and squared errors are calculated to measure forecast accuracy.

Sales and Operations Planning (S&OP)

  • Consumption Forecasts: Yearly consumption data, last month’s closing figures, and forecasted values are presented for each product-region combination.
  • Forecast Adjustments: Sales and marketing teams can adjust forecasts based on market intelligence, upcoming orders, or promotional activities, with options to specify reasons such as regular targets, bulk orders, or institutional sales. For more on how these adjustments can impact overall strategy, see Understanding Linear Programming Problems in Decision Making.
  • Impact Tracking: Changes in forecast quantities are tracked and updated in real-time to maintain transparency.

Inventory Control Integration

  • Stock Levels: Inventory is monitored at SKU, regional, and supply point levels, including stock on hand and in transit.
  • Stock Thresholds: Minimum (7 days), reorder (15 days), base/optimum (30 days), and maximum (45 days) stock levels are defined to balance availability and minimize expiry risks.
  • Perishability Considerations: Given the products’ shelf life, the model prevents overstocking to reduce losses from expired goods. For insights on managing perishability in inventory, refer to A Quick Guide to Supply Chain Optimization.
  • Replenishment Logic: Replenishment orders are triggered only when stock falls to or below the reorder level, ensuring efficient inventory turnover.

Additional Features

  • Sales Performance Analysis: Identifies highest and lowest selling products and regions, along with their contribution to overall consumption.
  • Supply Point Management: Tracks inventory across distribution centers, warehouses, clearing agents, and distributors.
  • Hypothetical Data Support: The model is supported by sample sales and consumption data to validate the forecasting and inventory algorithms.

Summary

This integrated supply chain model leverages exponential smoothing for demand forecasting, incorporates real-time sales and operations adjustments, and tightly controls inventory levels to optimize stock for perishable products. It provides a robust, one-click dashboard for manufacturers to reduce stockouts, minimize expiry losses, and align supply with actual market demand across diverse global regions.

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