Let them eat cake! During the COVID-19 pandemic, vast amounts of bread might be stuck on the supply chain or be thrown away to pigs. Actually, multiple pigs end up being thrown away, just like thousands of gallons of milk, eggs, and vegetables left to rot on the fields. During this unfortunate wastage caused by the pandemic, grocery stores still experience shortages (Newman and Bunge 2020; YaffeBellany and Corkery 2020). Even though it has been exacerbated and enhanced by the epidemic, this logistics and supply chain crisis has been a long time in the making, as is noted by both business researchers and practitioners. Centralization of supply chain operations and information, lack of data integration and aggregation, and societal, regulatory and systemic constraints have all led to food wastage and supply chain issues in the industry (Gruber et al. 2016; Shanker and Mulvany 2018). In tandem, the crisis emphasizes the numerous problems that appear in public and private systems in relation to data reporting, integration, aggregation, and analytic systems. Scientists are faced with analyzing which COVID-19 public policy strategy worked best in order to formulate future measures (Gibney 2020). In this process, they are contending with problems related to compiling data, merging distinct reporting systems and methods among states, regions, and countries, and standardizing information collected by different teams. Researchers and analytics experts have limited access to quality data, require time to calibrate existing models, and might face pushback from decision-makers due to outcome bias, or the tendency to overweight observed outcomes (Dillon et al. 2016). The importance of high-quality data and analytics throughout the back-end and front-end organizational processes, including the supply chain and the customer relationship management process, as the food industry demonstrates, is greater than ever (Peltier et al. 2013). Previous literature cites the importance of information sharing and collaboration among stakeholders to generate collective insights and emphasizes the role of digital technology to bridge circularity holes in the supply chain (Ciulli et al. 2019; Gadde and Amani 2016). To lower food wastage in the network, stakeholders must collaborate to increase societal engagement, awareness, and knowledge; information sharing with quality data can ultimately lead to greater sustainability and sustainable innovation levels (Bonadonna et al. 2019; Crittenden et al. 2011; Devin and Richards 2018; Sheth et al. 2011; Varadarajan 2017). At times like these, high quality data and analytics can enable knowledge-based, creative, innovative, and transformative solutions.

中文翻译：

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大流行期间高质量数据和分析的重要性

让他们吃蛋糕！在COVID-19大流行期间，大量面包可能会粘在供应链上或扔给猪。实际上，最终有多头猪被扔掉了，就像数千加仑的牛奶，鸡蛋和蔬菜在田间腐烂一样。在大流行造成的不幸浪费中，杂货店仍然遇到短缺（Newman和Bunge 2020； YaffeBellany和Corkery 2020）。正如商业研究人员和从业人员所指出的那样，尽管这种流行病加剧并加剧了这种物流和供应链危机，但危机已经形成了很长时间。供应链运营和信息的集中化，缺乏数据集成和汇总以及社会，法规和系统的约束都导致了该行业中的食品浪费和供应链问题（Gruber et al。2016; Shanker和Mulvany（2018）。危机同时强调了公共和私人系统中与数据报告，集成，汇总和分析系统有关的众多问题。科学家面临着分析哪种COVID-19公共政策策略最有效以制定未来的措施的问题（Gibney，2020年）。在此过程中，他们要解决以下问题：数据编辑，州，地区和国家之间合并不同的报告系统和方法，以及标准化不同团队收集的信息。研究人员和分析专家访问质量数据的机会有限，需要时间来校准现有模型，并且可能因结果偏倚或倾向于超重观察到的结果而面临决策者的压制（Dillon et al.2016）。正如食品行业所展示的那样，在整个后端和前端组织流程（包括供应链和客户关系管理流程）中，高质量数据和分析的重要性比以往任何时候都要重要（Peltier等，2013）。先前的文献援引了利益相关者之间信息共享和协作以产生集体见解的重要性，并强调了数字技术在弥合供应链中的圆孔方面的作用（Ciulli等人2019; Gadde和Amani 2016）。为了减少网络中的食物浪费，利益相关者必须合作以增加社会参与度，意识和知识；与高质量数据进行信息共享最终可以提高可持续性和可持续创新水平（Bonadonna等人2019; Crittenden等人2011; Devin和Richards 2018; Sheth等。2011; Varadarajan 2017）。在这样的时候，高质量的数据和分析可以实现基于知识的，创造性的，创新的和变革性的解决方案。