导语：清华－康奈尔双学位金融MBA项目的在读学生在学习期间需进行两次赴美集中学习，每次需在大洋彼岸进行2~3周充实的理论+实践课程。2016级同学们第二次的赴美学习之旅已经结束，但同学们在华尔街实践中力争上游的身影还历历在目，在课堂上受到康奈尔教授的赞扬亦犹在耳边。为了铭记这些荣耀，我们收集了赴美同学的部分优秀作业，整理出“Cornell Task”系列，干货满满，敬请期待。
今天推出的2016级郭心蕊同学的课程作业就是关于与Wall Street Trek 课程的感想和体会，原文为英文，由学生本人翻译供稿。
图为：赴美期间，郭心蕊代表全体同学为Matthew-Baron教授献礼Robert H. Frank合影
以下为作业原文：
Student Name: GUO Xinrui
Professor: Jason Hogg
Course Title: Hackathon
Date: 2017.4.28
First of all, the author really views the Hackathon event as a great opportunity to not only analyze a Fintech issue within the JD system from a practical perspective but also work with cross culture/expertise teammates and learn. Some key notes taken from the experience are listed as follow.
Cross-culture negotiation and collaboration
The very useful first steps would always be building mutual trust and align goals. Instead of jumping to the Hackathon topic, the team started with some introductions, chit-chats, members’ self-introductions (background, current career/academic focus, professional expertise, things to do in the city, etc). Members also went on to align the goals: the Hackathon event is more than a school project and the team would like to devote as much energy as possible to deliver it.
In retrospection, the author finds the beginning discussions very help. It motivates the team towards the same goal and helps members to understand each other’s expertise. Chinese members have purchasing experience on JD.com before and know better about JD’s image, strategies and innovation in various areas. The US members have strong tech background and contribute the most regarding data crunching, solution construction and SQL analysis.
However, the team did run into some challenges when deciding the key issue to solve in the project. The US members suggested JD to learn from Amazon while the Chinese members believed given JD’s self-operated nature and the country’s infrastructure, some sample patterns cannot be installed directly. It was until 6 in the afternoon that the team reached a consensus to utilize machine learn to find out consumers’ unmet needs and high margin areas in which JD should cultivate its own private brand (white label).
Suggestions for Future Hackathon
In order to identify the real issue and offer solid solution for JD, the team would need real time operational data from the company. When looking at white label, the team could use data regarding the current self-operating to third part goods ratio, the current profit margin, customers’ feedback, developing cost for both groups and financial data on how well the current white label brands are doing.
Throughout previous research and brief exchange with JD professionals, the team found related data still need further specification. The team also tried to get in touch with other JD management team through their own connections. However, given the size of the organization and the complexity of data, it is relatively hard to locate the specific personnel in such a limited time window. The missing of key data made it challenging for the team to locate key areas where JD should go white label.
Thus, for next year’s event, it would be very helpful if data channel is open and real time operational data or maybe mock data could be shared with the teams based on specific topics. It would also be beneficial if through higher administration, each team could have a 20-min informational interview with key personnel regarding specific topic 1 day before the competition.
译文
学生：郭心蕊
指导教授:Jason Hogg
课程: Hackathon
日期：2017.4.28
首先，笔者认为此次京东康奈尔Hackathon竞赛活动是一次难得机会。一方面可以一窥京东体系内科技金融的架构和操作，另一方面可以和康奈尔Tech学院的学生切磋交流，体验跨文化交流与协作。现将此次几点心得体会整理如下：
为提升跨文化交流的效率，第一步往往不是直奔主题。我们小组首先组员间自我介绍，了解各成员的背景、职业领域、学术专长、研究方向、甚至纽约旅行的好去处……这些话题看似无章，其实帮助组员迅速建立了良好的互相认同，明确了组内成员的各自强项，也将大家此次项目的目标统一到了一起。组员们都认为，此次项目不仅仅是一个简单的作业，更是一个了解京东业务和科技金融领域的良好机会，大家希望全力以赴。笔者认为，这些讨论使大家目标一致，且对组内成员的强项非常清晰，有益于后期小组合作的高效推进。比如，来自清华大学的小组成员对京东及其传递的战略、形象和消费体验领域的创新非常熟悉，而来自康奈尔Tech学院的同学有很强的技术背景，对SQL分析，数据挖掘，方案搭建更为擅长。
但是，我们的团队在推进过程中也遇到了一些关键问题。美国组员建议京东参考亚马逊的模式，而中国组员认为京东自营的本质和国内基础设施情况不允许京东直接拷贝他人模式。经过一天激烈的讨论，下午6点全部组员达成共识：探讨京东如何借助机器学习(machine learning)识别并满足特定高利润空间领域的消费者需求。识别需求后，京东通过贴牌生产实现该部分产品利润。
为了完成上述分析，小组成员需要大量的平台销售和利润数据，尤其是目前自营品牌商品、三方品牌商品和贴牌商品间的利润差异、顾客反馈及开发成本。尽管有京东核心团队高官的现场答疑和网络数据，此类信息仍然很难收集。这也导致小组很难细化目前可进入的细分产品领域并提出相应的解决方案。因此，对于下一年的活动，本小组的建议是:京东提供部分数据库作为分析基础。并提前与各小组沟通课题，如需可提前1天安排informational interview。帮助小组更好的认识实际操作情况并提出切实的解决方案。
