Remote Productivity and Paperless Processing in a Trade Document Workflow Platform for Pandemic Resilience and Greener Recovery

今年4月，世界经济论坛（WEF）在供应链方面指出，“针对COVID-19的措施已经明确表明，当不可能存在实体时，依赖纸质等实物资产的运营可能面临严重中断……纸质打印输出通常由必须到办公室或其他工作场所的操作人员处理，并与他人协调。此外，依赖于这些纸质文件中的信息的价值链很快就会失去这种可见性，并且无法对不断变化的条件做出反应……众所周知，贸易依赖于纸质流程。”摩根大通2017年的贸易展望报告估计，由于效率低下和文书工作缺乏可视性，与贸易有关的财富500强企业每年产生超过810亿美元的不必要供应链成本。目前手工检查文书工作的方法导致周转时间长、可见性有限、没有正式的知识获取和容易出错的过程。除了货币成本，还有环境负担，全球贸易每年产生3200亿份文件（摩根大通，联合国贸易和发展会议），保守地假设每份文件只打印一次，这相当于150万纸吨和1650万吨二氧化碳排放/年。世界经济论坛指出，为了在2019冠状病毒病疫情下取得更好的表现，“数字化……不仅仅是成本问题，而主要是可见性和管理供应链风险的问题。为了限制故障点的影响……通过数字手段提供数据非常重要。”COVID-19在整个组织中造成了“碎片化的知识”，通常当你坐在办公室时发生的知识转移不再自然发生。组织积累的知识和技术诀窍必须在系统和流程中得到更好的捕捉——因为协作仍然是航运行业生存的关键。”该项目旨在对尖端机器学习研究进行研究和初步测试，以升级我们的核心平台算法，并提供高度准确、可靠的文件数字化，以刺激受到严重影响的贸易部门转向无纸化贸易，并通过使用灵活、远程可访问的数字工具加速强劲、持续的复苏。我们将对当前的提取算法进行机器学习改进，从而提高生产率，获取专有技术，并提高对文件数据的远程数字可见性。我们将进一步开发团队通信功能，使贸易运营部门能够以目前无法实现的方式远程高效协作。

In April, the World Economic Forum (WEF) noted, in regard to supply-chains, that "measures for COVID-19 have made clear that operations dependent on physical assets, such as paper, can face serious disruption when physical presence is not a possibility...paper printouts are usually handled by operations personnel who must come to the office, or another place of work, and coordinate with others. In addition, value chains that rely on information in these paper documents lose access to that visibility very quickly and cannot react to changing conditions...Trade is notoriously reliant on paper-based processes". JPMorgan's 2017 trade outlook report estimates that trade-involved Fortune 500 companies incur more than $81 billion of unnecessary supply chain costs each year due to inefficiencies and lack of visibility around paperwork. The current manual approach to checking paperwork results in long turn-around times, limited visibility, no formal knowledge capture and error prone processes. Beyond monetary costs, there is an environmental burden, global trade generates 320 billion documents/year (JPMorgan,UNCTAD), conservatively assuming each document is only printed once, that equals 1.5mio paper tonnes and 16.5mio tonnes of CO2 emissions/year.. WEF notes for better performance under COVID-19, "digitizing...is not simply a matter of cost, but primarily of visibility and managing supply chain risk. To limit the impact of points of failure... it is important to make data available through digital means." COVID-19 has created "fragmented knowledge across an organization, the knowledge transfer that normally happens when you're sitting in an office doesn't happen naturally anymore. The cumulative knowledge and know-how of organizations is going to have to be captured better in the systems and processes --- because collaboration will still be the key to survival in shipping." This project aims to conduct research and preliminary testing into cutting edge machine learning research to upgrade our core platform's algorithms and deliver highly accurate, reliable document digitisation to incite the heavily impacted trade sector's movement into paperless trade and expedite a robust, sustained recovery through use of flexible, remotely accessible, digital tools. We will deploy machine learning improvements to our current extraction algorithm, in doing so delivering productivity enhancements, captured know-how and greater remote digital visibility over data within paperwork. We will further develop team communication features that will enable trade operations departments to work efficiently remotely and in collaboration in a way that is currently not possible.