Smart logistics network cost optimisation

由于冠状病毒，英国的供应链面临压力，离开欧盟和正在实施的新立法。这些供应链高度分散，数据存储在许多组织的孤岛中，目前没有看到共享数据的商业案例。这使得公司看不到他们的行为对其他参与者的影响，而商业力量，而不是数据，通常为决策提供理由。当一个参与者降低成本时，他们会转移并经常增加其他参与者的成本，从而降低整个系统的弹性。目前市场上可用的工具和模型旨在优化单个公司的流程，而不是整个供应链。这意味着他们无法分析公司内部和公司之间复杂的产品和信息流和活动，从而产生反映参与者相互依赖性的所需财务和资源效率。十多年来，Incept一直处于该领域的前沿，与家乐福、联合利华、SPAR、CHEP和可口可乐等公司合作，并开发了网络价值模型（NVM），当应用该模型时，已经实现了数百万英镑的节省，相当于总成本的10%-30%。NVM模型在几分钟内运行一个完整的分析，但是详尽模型的设置是一个手动练习，需要几周的时间才能运行，分析需要专家解释，这意味着可能需要几个月的时间才能实现节省，到那时操作环境已经发生了变化。该研究将使用20，通过包括1，200家供应商、1，400家商店和11个分销节点在内的供应链，运送了超过1亿箱的000种产品。这将为整个英国杂货物流供应链整合和优化的潜在利益提供有效的代表。这项可行性研究将测试的假设是，人工智能的最新技术可以用于优化现有的NVM模型，为用户节省10-30%的成本。这将反过来减少类似水平的碳排放，并在提高资源利用率的同时显著减少浪费。它还将开发一种用户信任的商业和治理模式，将该工具的知识产权纳入由用户管理的社会企业结构，并减少英国制造业所有利益相关者采用的障碍。

Supply chains are under pressure in the UK due to coronavirus, leaving the EU and the new legislation that is being implemented. These supply chains are highly fragmented, with data stored in silos across many organisations that at present, do not see a business case for sharing the data.This leaves companies blind to the impact of their actions on other actors and commercial power, rather than data, normally provides the justification for decisions. When one actor reduces costs, they then transfer and often increase costs for others diminishing the resilience of the whole system.The current tools and models available in the market are designed to optimise the processes of single companies not whole supply chains. This means they cannot analyse the complex product and information flows and activities within and between companies to generate the required financial and resource efficiencies that reflects the interdependence of the actors.For over a decade, Incept have been working at the forefront of this field with companies like Carrefour, Unilever, SPAR, CHEP and Coca-Cola and have developed the Network Value Model (NVM) that, when applied, has delivered millions of pounds of savings equivalent to between 10%-30% of total costs.The NVM model runs a full analysis in minutes, however setup of the exhaustive model is a manual exercise which takes weeks to run, the analysis requires expert interpretation meaning it can take months to realise savings, by which time the operating environment has changed.The study will use data from 20,000 products shipped in over 100 million cases through supply chains including 1,200 suppliers, 1,400 stores and 11 distribution nodes. This will provide a valid representation of potential benefits of supply chain integration and optimisation for UK grocery logistics across the whole of the country.The hypothesis that this feasibility study will test is that the latest techniques in AI can be used to optimise the existing NVM model to deliver cost savings of between 10-30% for the users. This will in turn reduce carbon emissions at a similar level and significantly reduce waste whilst improving resource utilisation.It will also develop a business and governance model that will users will trust to enshrine the IP for the tool into a social enterprise structure that is governed by its users and reduce the barriers to adoption for all stakeholders in the UK manufacturing sector.