Introducing Microsoft Dynamics 365 Supply Chain Management’s AI-Driven Precision in Demand Planning

Posted on: December 4, 2023 | By: Fred Liu | Microsoft Dynamics AX/365, Microsoft Dynamics Manufacturing

Microsoft Dynamics 365 Supply Chain Management’s (D365) demand planning feature, which is not to get mixed up with demand forecasting, is poised to revolutionize supply chain management (you can however, read more about demand forecasting here). This innovation will transform how modern supply chains operate. In the current competitive business environment, where challenges are constantly evolving, the shift to intelligent demand planning is no longer optional but essential for businesses to not just survive but flourish. This technology equips companies with the tools to navigate the complexities of today’s supply chain dynamics, optimizing profitability with confidence, adaptability, and success.

The standout aspect of demand planning in D365 is its ability to integrate custom entities into the D365 framework seamlessly. This integration enables smooth data flow from various sources, including multiple D365 instances and data lakes. It also provides powerful metrics and error calculations, like Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE), to constantly refine demand planning strategies.

Demand Planning’s Role

Before exploring the key features and functionalities of demand planning in D365, it’s important to understand demand planning’s crucial role in supply chain management.

Demand planning involves forecasting future customer demand for products and services, enabling organizations to use resources efficiently, manage inventory effectively, and optimize production schedules.

Benefits of accurate demand planning include:

1. Efficient Resource Allocation: Precise demand forecasts help organizations efficiently allocate resources like raw materials and labor, preventing overproduction or underproduction, thus reducing costs and minimizing waste.
2. Optimized Inventory Levels: Understanding expected demand allows companies to maintain optimal inventory levels, reducing carrying costs and stockout risks.
3. Improved Customer Service: Meeting customer demands promptly enhances customer satisfaction and loyalty, leading to repeat business.
4. Cost Reduction: Effective demand planning reduces costs associated with excess inventory, production inefficiencies, and urgent shipping.
5. Market Responsiveness: Quick adaptation to changing demand patterns is crucial for business survival in today’s fast-paced market.

Demand Planning for Different Industries:

Let’s examine real-world examples demonstrating how Dynamics 365 Supply Chain Management’s new demand planning capabilities can enhance supply chain operations, boosting efficiency, profitability, and customer satisfaction.

AI Forecasting Models:

• A furniture manufacturing company employs AI forecasting models such as Exponential Smoothing (ETS) and Autoregressive Integrated Moving Average (ARIMA) to predict demand for various furniture categories, considering historical sales data, housing market trends, and lifestyle shifts. Benefit: Accurate demand forecasting enables the company to efficiently plan production schedules, avoid furniture stockouts, and reduce overproduction. This leads to cost savings, enhanced production efficiency, and minimized waste.

Data Hierarchy Management:

• A chain of fashion boutiques uses product hierarchy management to categorize items into different styles (e.g., casual, formal, activewear) and organizes stores by urban and suburban locations. They also use time hierarchy to capture seasonal fashion trends. Benefit: The structured data hierarchies help the boutique chain make informed decisions about product ranges, inventory management, and targeted promotions. They can stock items that cater to local tastes and optimize sales during fashion seasons, boosting customer satisfaction and profitability.

Collaborative Demand Planning:

• A multinational pharmaceutical company coordinates demand planning for various medications across different continents using collaborative planning features. Benefit: This strategy enhances transparency and consensus among international teams, while version control offers a comprehensive record of changes for accountability and traceability.

Location-Based Demand Planning:

• A multinational automotive parts distributor uses location-based planning to adjust for varying demand in different countries and regions, considering factors like local vehicle preferences and regional regulations. Benefit: The distributor can fine-tune inventory and distribution schedules based on specific regional demand, ensuring efficient deliveries and reducing logistical waste.

Real-Time Demand Monitoring:

• A leading sports equipment manufacturer integrates real-time sales data from their online platform, using Azure Data Explorer for swift data analysis. Benefit: This allows the manufacturer to quickly adapt their manufacturing, inventory, and marketing strategies in response to current market trends, ensuring they remain competitive in the sports equipment market.

Outlier Detection and Management:

• A food and beverage company uses outlier detection algorithms to monitor sudden changes in demand for their products, such as a spike in demand for certain beverages during a heatwave. Benefit: Quick identification of demand outliers enables the company to respond swiftly to market changes, ensuring the availability of their products during peak demand and maintaining regulatory compliance.

Demand Forecasting and Inventory Management:

• A toy retailer integrates multiple data sources, including historical sales and holiday season trends, using advanced forecasting models to predict demand for different toy categories and specific items. Benefit: This enables the retailer to precisely manage their inventory, optimizing purchasing decisions, and planning marketing initiatives effectively to prevent overstocking or shortages, thus reducing inventory costs.

Next Steps

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