小h漫谈（22）：智能物流介绍

摘要：而日本早稻田大学教授西泽修提出的“物流冰山说”则认为，物流就像一座冰山，其中沉在水面以下的是我们看不到的黑色区域，这部分就是“黑大陆”，而这是物流尚待开发的领域，也是物流的潜力所在。这两个理论都旨在说明物流活动的模糊性和巨大潜力。

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“小h漫谈（22）：智能物流介绍”

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"Xiaoh's Ramblings (22):Introduction to Smart Logistics"

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一、思维导图（Mind mapping）

二、精读内容（Intensive Reading Content）

在物流领域，有两个著名的理论——“黑大陆说”和“物流冰山说”。

In the logistics sector, there are two well-known theories: the "Dark Continent Theory" and the "Logistics Iceberg Theory."

管理学家彼得·德鲁克（Peter Drucker）提出了“黑大陆说”，他认为在流通领域中，物流活动的模糊性尤其突出，是流通领域中最具潜力的领域。

The "Dark Continent Theory" was put forward by management scholar Peter Drucker. He argued that the ambiguity of logistics activities is particularly pronounced in the field of distribution and that this area holds the most potential for development within the distribution sector.

而日本早稻田大学教授西泽修提出的“物流冰山说”则认为，物流就像一座冰山，其中沉在水面以下的是我们看不到的黑色区域，这部分就是“黑大陆”，而这是物流尚待开发的领域，也是物流的潜力所在。这两个理论都旨在说明物流活动的模糊性和巨大潜力。

The "Logistics Iceberg Theory" was proposed by Professor Fumito Nishimura of Waseda University in Japan. According to this theory, logistics can be likened to an iceberg, with the part submerged beneath the water's surface being the invisible "dark area," which is also referred to as the "dark continent." This submerged part represents the yet - to - be - developed area in logistics and is where the potential of logistics lies. Both theories aim to illustrate the ambiguity and vast potential of logistics activities.

对于如此模糊而又具有巨大潜力的领域，我们该如何去了解、掌控和开发呢？答案就是借助大数据技术。

Given such an ambiguous yet highly potential - laden field, how can we understand, control, and develop it? The answer lies in leveraging big data technology.

发现隐藏在海量数据背后的有价值的信息，是大数据的重要商业价值。大数据是打开物流领域这块神秘的“黑大陆”大门的一把金钥匙。物流行业在货物流转、车辆追踪、仓储等各个环节中都会产生海量的数据。有了这些物流大数据，所谓的物流“黑大陆”将不复存在，我们可以通过数据充分了解物流背后的规律。

Uncovering valuable information hidden behind massive amounts of data is a significant commercial value of big data. Big data serves as a golden key to unlock the mysterious "dark continent" of the logistics field. The logistics industry generates vast amounts of data in various aspects such as goods circulation, vehicle tracking, and warehousing. With these logistics big data, the so - called "dark continent" of logistics will cease to exist.

借助大数据技术，我们可以对各个物流环节的数据进行归纳、分类、整合、分析和提炼，为企业战略规划、运营管理和日常运作提供重要支持和指导，从而有效提升快递物流行业的整体服务水平。

We can fully understand the underlying patterns of logistics through data. By utilizing big data technology, we can organize, categorize, integrate, analyze, and refine data from each logistics link. This provides crucial support and guidance for corporate strategic planning, operational management, and day - to - day operations, thereby effectively enhancing the overall service level of the express logistics industry.

大数据将推动物流行业从粗放式服务到个性化服务的转变，甚至颠覆整个物流行业的商业模式。通过对物流企业内部和外部相关信息的收集、整理和分析，可以为每个客户量身定制个性化的产品和提供个性化的服务。例如，Amazon通过分析用户的历史购买记录和浏览行为，为用户提供个性化的商品推荐和物流配送选项。这种个性化的服务不仅提高了客户满意度，还增强了企业的竞争力。

Big data will drive the logistics industry's transition from extensive services to personalized services and may even disrupt the entire logistics industry's business model. By collecting, organizing, and analyzing relevant internal and external information of logistics enterprises, personalized products and services can be tailored for each customer. For example, Amazon analyzes users' historical purchase records and browsing behavior to offer personalized product recommendations and logistics delivery options. This personalized service not only increases customer satisfaction but also enhances corporate competitiveness.

阿里的“天网+地网”计划是大数据在物流领域的成功应用案例。所谓“地网”，就是指阿里的中国智能物流骨干网，最终将建设成为一个全国性的超级物流网。所谓“天网”，是指以阿里旗下多个电商平台为核心的大数据平台。由于其电商业务量大，在这个平台上聚集了众多的商家、用户和物流企业，每天都会产生大量的在线交易。

Alibaba's "Sky Net + Ground Net" plan is a successful application case of big data in the logistics field. The so - called "Ground Net" refers to Alibaba's China Smart Logistics Backbone Network, which will eventually be built into a nationwide super logistics network. The "Sky Net" refers to the big data platform centered around Alibaba's multiple e - commerce platforms. Due to its large e - commerce business volume, numerous merchants, users, and logistics enterprises gather on this platform, generating a vast number of online transactions daily.

因此，这个平台掌握了网络购物物流需求数据、电商货源数据、货流量与分布数据以及消费者长期购买习惯数据等。物流公司可以对这些数据进行大数据分析，优化仓储选址、干线物流基础设施建设以及物流体系建设，并根据商品需求分析结果提前把货物配送到需求较为集中的区域，做到“买家没有下单、货就已经在路上”，最终实现“以天网数据优化地网效率”的目标。

As a result, the platform has access to data on e - commerce logistics demand, e - commerce sources, cargo flow and distribution, as well as consumers' long - term purchasing habits. Logistics companies can conduct big data analysis on this data to optimize warehouse location selection, trunk logistics infrastructure construction, and logistics system development. They can also deliver goods in advance to areas with concentrated demand based on product demand analysis results. This achieves the goal of "goods already on the way before buyers place orders," ultimately realizing the objective of "using Sky Net data to optimize Ground Net efficiency."

此外，大数据技术还可以帮助物流企业进行风险预测和管理。通过对历史数据和实时数据的分析，物流企业可以提前预测可能出现的运输延误、货物丢失等问题，并采取相应的措施进行预防和应对。例如，通过分析天气数据和交通状况，物流企业可以在恶劣天气来临之前调整运输路线，避免货物受损和延误。这种风险预测和管理能力不仅提高了物流服务的可靠性，还降低了企业的运营成本。

Moreover, big data technology can also assist logistics enterprises in risk prediction and management. By analyzing historical and real - time data, logistics companies can forecast potential transportation delays, cargo loss, and other issues in advance and take corresponding measures for prevention and response. For instance, by analyzing weather data and traffic conditions, logistics enterprises can adjust transportation routes before bad weather arrives to prevent cargo damage and delays. This risk - prediction - and - management capability not only enhances the reliability of logistics services but also reduces corporate operating costs.

总之，大数据技术在物流领域的应用前景广阔。它不仅能够帮助物流企业更好地了解和掌控物流活动，还能够推动物流行业从传统的粗放式服务向更加个性化、高效化的服务模式转变。随着大数据技术的不断发展和应用，物流行业将迎来更多的创新和发展机遇。

In summary, the application prospects of big data technology in the logistics field are broad. It can not only help logistics enterprises better understand and control logistics activities but also drive the logistics industry's transition from traditional extensive services to more personalized and efficient service models. As big data technology continues to develop and be applied, the logistics industry will usher in more innovation and development opportunities.

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