Accurately balancing supply and demand management, optimizing inventory levels, and forecasting future needs is challenging. Customers expect speed, flexibility, transparency, and reliability from brands. Forecasting and staging inventory effectively is critical, making a strong understanding of current and future inventory requirements. We have already examined how reliable logistics forecasting can be an accelerator of business growth. Let’s explore the common strategies and steps that supply chain managers can use to significantly enhance forecasting speed and accuracy. services.
Logistics forecasting requires robust computer modeling. To achieve this, it’s important to focus effort on three main areas:
There are many enablers in each of these areas, dependent on your sector, industry, and marketplace. We provide helpful starting points below.
Process-based improvements focus on creating efficient communication channels and information sharing protocols throughout the supply chain to ensure logistics forecasting can take internal and external factors into account.
These factors will feed into a logistics forecasting model to generate scenarios that represent a range of real-world changes and disruptors.
Data-based improvements focus on measuring, sharing, and using accurate and timely data to ensure you have high-quality inputs for forecasting, which lead to high-quality outputs.
Technology-based improvements focus on the applications and systems you use to generate logistics forecasts. This ensures you have proper integration, centralized data, and actionable scenarios.
Business strategy relies on solid forecasts of likely future supply and demand. Good modeling supports stronger, more confident planning and strategy. We describe on three main areas in which you can optimize your supply chain forecasting process, meeting customer needs while mitigating risk and preparing for future demand.
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