Doctrine

Reflections Prompted by the Technological Transformation Hidden Behind "Estimated Delivery Tomorrow"

由“预计明天送达”背后隐藏的技术变革引发的思考

PLA Daily (解放军报) 12 May 2026

Summary

A PLA-affiliated author writing in what appears to be a military theory publication draws an extended analogy between commercial logistics platforms—specifically same-day delivery systems—and future PLA warfighting, arguing that full-process data collection, algorithmic decision-making, and networked coordination in logistics offer a template for digitalized, intelligentized, and networked combat operations. The piece is notable less for any doctrinal novelty than as evidence that PLA theorists are actively mining civilian technology sectors to operationalize concepts like algorithmic command (算法研判), self-healing network architectures, and closed-loop battle damage assessment, suggesting these remain unsolved implementation problems rather than settled capabilities. The framing around breaking down data barriers between services, branches, and echelons points to interoperability as a persistent friction point the PLA is still working to resolve.

Translation

Starting from "Estimated Delivery Tomorrow"

■ Liu Yang

When we shop online and see the promise of "estimated delivery tomorrow" on a shopping platform, few people stop to think about the technological transformation hidden behind those words. This seemingly simple service commitment rests on a modern logistics system in which data collection, intelligent scheduling, and network coordination are deeply integrated. Through real-time collection of data across the entire process, relying on intelligent algorithms to precisely calculate delivery times, and using networks to connect the ordering, receiving, sorting, transporting, and delivery stages, the delivery process—full of uncertainty—is transformed into a deterministic result that can be calculated, anticipated, and controlled. The operating logic of this system offers inspiration and reference for the future development of warfare toward digitalization, intelligentization (智能化), and networking. Studying the application, transformation, and practical experience of emerging technologies, and exploring the mechanisms of victory in war, holds important practical value and guiding significance for accelerating the formation of modernized combat capabilities and improving operational effectiveness.

On a network platform, from the moment an order is placed, the user's order information, delivery address, shipment time, location nodes, and other data constitute the initial dataset. The foundation for on-time delivery lies in the full-process collection of digitalized information. Without continuous and reliable data support, relying purely on experiential estimation, on-time delivery would be out of the question. In the past, commanders at all levels were trapped in the fog of war and frequently unable to make optimal decisions due to incomplete, inaccurate, or untimely information. Commercial logistics technology provides a reference for penetrating that fog. Future warfare is data-driven warfare. One important prerequisite for victory is transforming the battlefield into a digitalized space that can be perceived, calculated, and shared, thereby driving the transformation of vague, approximate battlefield information into clear, precise battlefield situational awareness, and providing reliable, real-time data support for battlefield perception. On one hand, information must be collected in real time—comprehensively employing the Internet of Things, satellites, unmanned aerial vehicles, sensors, and other means to automatically and continuously collect data, integrating scattered, heterogeneous, and isolated data into a battlefield situational picture with full-domain coverage, continuous updates, and full-dimensional linkage. On the other hand, data standards must be unified, breaking down data barriers between different services and branches, different echelons, and different systems, to form a standardized and complete battlefield data pool.

For order delivery to be completed, data support alone is far from sufficient; the key is to conduct deep learning and algorithm refinement through analysis of historical order delivery data. The on-time delivery of modern logistics orders lies precisely in the shopping platform's intelligent scheduling, precise anticipation, and autonomous optimization. The sharp increase in uncertainty factors in future warfare objectively demands that planning and decision-making advance from experiential judgment toward algorithmic analysis (算法研判), providing quantified, scientific decision-making support for achieving battlefield victory. First, computational capacity must be improved—dedicated algorithmic models must be developed to form an algorithm library covering the full cycle of reconnaissance, control, strike, assessment, and support, enabling rapid processing and deep mining of information and data. Second, analytical and assessment capacity must be improved—artificial intelligence deep learning technology and other means must be used to predict indicators of adversary action, transforming static data into dynamic early warning. Third, decision-making efficiency must be improved—automatically distinguishing strike targets, allocating strike platforms, and calculating support requirements, rapidly generating multiple courses of action for commanders to choose from, and compressing the time required for command-and-control centers to produce plans.

The final execution of order fulfillment cannot be separated from a highly coordinated execution network. Sorting robots inspect and package goods; couriers deliver to the door; goods arrive at the estimated time—behind all of this is an efficient, closed-loop, and coordinated collaborative network. The on-time delivery of modern logistics orders is supported by a collaborative network characterized by node interconnection, autonomous adaptation, and high-degree linkage. Future warfare should likewise build a networked operational coordination system, achieving distributed deployment, networked command, and integrated coordination, transforming the sequential top-down implementation of operational coordination into autonomous regulation and control, and providing efficient and controllable structural support for operational coordination. First, dynamic self-organizing networks must be built—breaking down barriers between nodes to form a self-healing, wide-area interconnected network architecture, enabling any node to connect, any break point to self-heal, and any area to be covered, thereby improving system survivability and stability. Second, full-dimensional cross-domain linkage must be advanced—linking different combat units across all domains into a unified whole, achieving real-time information sharing and autonomous operational coordination, and forming a systemic advantage of cross-domain energy concentration and full-domain energy release (跨域聚能、全域释能). Third, full-process closed-loop management and control must be strengthened—from situational awareness, command decision-making, and action control through to effects assessment, with continuous point-by-point tracking, real-time correction, and closed-loop implementation throughout, ensuring that combat operations are precise, controllable, sustained, and effective.

Original Chinese

从“预计明天送达”说起 ■刘洋当我们在网上购物，看着购物平台上“预计明天送达”的承诺时，很少有人会去思考这句话背后所隐藏的技术变革。这一看似简单的服务承诺，其背后是数据采集、智能调度、网络协同深度融合的现代物流体系，通过对全流程数据实时采集，依托智能算法精准测算配送时长，再以网络贯通下单、收件、分拣、运输、派送各环节，将充满不确定性的配送进程转化为可计算、可预判、可调控的确定性结果。其运行机理，给未来战争数字化、智能化、网络化的发展带来启示和借鉴。研究新兴技术的运用转化与实践经验，探索战争制胜机理，对加快形成现代化作战能力、提升作战效能，具有重要实践价值与指导意义。网络平台上，从订单产生的那一刻起，用户的订单信息、收货地址、发货时间、位置节点等便构成了初始数据。订单准时送达的基础，就在于数字化信息全流程采集。如果没有持续可靠的数据支撑，单纯依靠经验估算，准时送达便无从谈起。过去，各级指挥员被战争迷雾所困，常因信息不全、不准、不及时而无法作出最佳决策，商用物流技术为穿透这层迷雾提供了参考。未来战争是数据驱动的战争，制胜的一个重要前提是把战场变成可感知、可计算、可共享的数字化空间，进而推动将模糊、概略的战场信息转变为清晰、精准的战场态势，为感知战场提供可靠、实时的数据支撑。一方面，要实时采集信息，综合运用物联网、卫星、无人机、传感器等，不间断自动采集数据，将零散、异构、孤立的数据整合为全域覆盖、全时更新、全维联动的战场态势。另一方面，要统一数据标准，打破不同军兵种、不同层级、不同系统间的数据壁垒，形成规范、完整的战场数据池。订单的配送完成，仅有数据支撑是远远不够的，关键是通过分析订单配送的历史数据来深度学习、修正算法。现代物流订单的准时送达，恰恰在于购物平台的智能调度、精准预判与自主优化。未来战争不确定性因素激增，客观上要求推进筹划决策由经验判断转向算法研判，为决胜战场提供量化、科学的决策依据。首先，要提升计算能力，研发专用算法模型，形成覆盖侦察、控制、打击、评估、保障全周期的算法库，实现对信息与数据的快速处理与深度挖掘；其次，要提升研判能力，利用人工智能深度学习技术等，预测对手行动征候，把静态数据转化为动态预警；再次，要提升决策效率，自动区分打击目标、分配打击平台、测算保障需求，快速生成多套行动方案供指挥员选择，压缩指控中心方案形成时间。订单完成的最后落地离不开高度联动的执行网络。分拣机器人验货包装，快递员上门派送，商品按预计时间送达……其背后是一个高效、闭环、联动的协同网络。现代物流订单配送的准时送达，支撑源于节点互通、自主适配、高度联动的协同网络。未来战争也应构建网络化行动协同体系，实现分布式部署、网络化指挥、一体化协同，将逐级落实的行动协同向自主调控转变，为行动协同提供高效、可控的结构支撑。一是要构建动态自组织网络，打破各节点壁垒，形成可自愈、广域互联的网络体系，实现任一节点可接入、任一断点可自愈、任一区域可覆盖，提升体系抗毁性与稳定性；二是要推进全维度跨域联动，将各领域不同作战单元联为一体，实现信息实时共享、行动自主协同，形成跨域聚能、全域释能的体系优势；三是要强化全流程闭环管控，从态势感知、指挥决策、行动控制到效果评估，全程定点跟踪、实时修正、闭环落实，确保作战行动精准可控、持续高效。