Amazon measures packaging reduction from batching primarily through the use of advanced machine learning models, automation technologies, and data analytics that optimize packaging decisions and monitor material usage across its extensive fulfillment network.
Packaging Reduction through Machine Learning and AI
Since 2015, Amazon has reduced the average packaging weight per shipment by 36-43%, eliminating over 3 million metric tons of packaging materials worldwide. One of the core methods Amazon uses to measure and achieve packaging reduction is the application of machine learning models that determine the most effective packaging type for each product. These models use data about the products, such as dimensions, fragility, and how products have fared in returns due to damage, combined with customer feedback and image analysis from multiple product angles taken at fulfillment centers. The AI system analyzes this information to select the minimal but sufficient packaging that ensures safe delivery while reducing waste. This model, often referred to as the Package Decision Engine, continuously learns and adapts to improve packaging efficiency, thereby reducing the use of cardboard boxes, filler materials, tape, and plastic. Measurement is done by tracking packaging weight, material type used, and the impact on carbon emissions.
Automated Packaging Technology
Amazon uses innovative automated machinery in its fulfillment centers that combine sensors, real-time measurement, and custom packaging creation to minimize packaging material per shipment. For example, in Europe and the US, Amazon has introduced automated packing machines that scan each item and cut made-to-measure paper bags from rolls of recyclable paper. These bags are heat-sealed without glue and do not use additional padding, drastically reducing packaging volume and weight compared to traditional boxes. Measurement of reduction here is through the average grams of packaging saved per shipment (more than 26 grams per shipment on average) and tracking how many plastic bags were avoided by replacing them with these paper bags (130 million plastic bags avoided in 2023 in US alone). Such automation enables Amazon to scale packaging reduction efforts reliably and measure the cumulative impact on packaging materials across millions of shipments daily.
Ships in Product Packaging Program
Another initiative Amazon has implemented is the Ships in Product Packaging program, which identifies and certifies products that can be shipped directly in their original manufacturer packaging without additional Amazon packaging. Machine learning helps Amazon identify such products by analyzing product information and packaging safety. This program reduces packaging significantly and is measured by the number of shipments made without additional Amazon packagingâover 5.5 billion items shipped this way since 2019 in North America and Europe alone. The growth of this program across geographies and increasing participation of sellers is tracked as a key metric of packaging reduction. The reduction is also reflected in less packaging weight per shipment and lower use of plastic and cardboard materials.
PackOpt Optimization Tool for Box Suites
Amazon has developed the PackOpt tool, which helps optimize the suite of box sizes used in fulfillment centers to match product dimensions more closely. This web-based tool simulates product-to-box fits across regions and identifies inefficiencies where oversized boxes generate excess "air" shipment volume. Amazon managers use PackOpt to identify which boxes to introduce or retire, directly affecting packaging material reduction. PackOpt measures efficiency through metrics like total cardboard weight used, packaging volume, box utilization rate, and air per shipment. By the end of 2022, 90% of Amazon's boxes in North America were optimized via PackOpt, resulting in 7%-10% annual reduction in cardboard waste, roughly 60,000 tons saved annually in that region.
Measurement of Environmental Impact and Reporting
Amazon holds itself accountable primarily through the carbon footprint reduction metric, which ties packaging choices to overall sustainability goals. The company tracks annual packaging weight reduction, amount of packaging waste eliminated, and the associated carbon emissions avoided. For example, AI-driven packaging models have helped save over 2 million tons of packaging between 2015 and 2022, with incremental increases reported subsequently. Amazon's sustainability updates provide frequent data on shipment packaging weight reductions, percentage of shipments using lightweight packaging, reductions in plastic packaging usage, and how many packages shipped with no additional Amazon packaging. These publicly shared metrics and internal tracking systems facilitate precise measurement of packaging reduction achieved through batching and other methods.
Packaging Reduction as a Business Metric
Amazon integrates packaging efficiency into its operational and financial KPIs. Reducing packaging not only cuts materials cost but also improves logistics efficiency by increasing truck fill rates and lowering shipping volumes. The company monitors variable costs per unit, which includes packaging expenses, to quantify the financial benefits from packaging innovations. By consolidating orders and optimizing packaging sizes through batching and machine learning, Amazon reduces packaging material per order while also improving handling efficiency. This business focus ensures that packaging decisions are continuously measured and optimized for cost-effectiveness alongside environmental benefits.
Summary
Amazon measures packaging reduction from batching and packaging optimization by combining:
- Machine learning models that calculate optimal packaging for each item, reducing packaging weight and materials used.
- Automated packaging machines that create made-to-measure packaging to avoid waste and track per-shipment material savings.
- Programs such as Ships in Product Packaging that quantify the number of shipments shipped without extra packaging.
- Tools like PackOpt that analyze box utilization and simulate packaging efficiencies to optimize box suites.
- Key sustainability metrics including packaging weight reductions, waste avoided, and carbon emissions saved reported in regular sustainability updates.
- Business metrics tracking cost savings and logistics efficiencies tied to packaging changes.