Leadership and Management Training: Business Analytics Program
8:30 AM, Monday, May 11, 2015 - 4:30 PM, Friday, May 15, 2015 - May 11-13: AmCham China Conference Center May 14-15: Salon 1, Beijing Marriott Northeast Hotel
This course will provide interpretation in Chinese.
In today’s dynamic business environment, a company’s success is increasingly tied to its ability to use data – including website, customer and social network data – as a strategic asset. In order to learn how to analyze and interpret data and use it for decision making, managers need to develop an understanding of the capabilities and common pitfalls of essential tools and techniques for data mining and predictive analytics. The Business Analytics Program will provide managers with a deeper understanding of how to effectively use data to improve their organization’s performance as well as hands-on experience with the latest tools and techniques for mining data and making meaning from data to drive business decisions.
AmCham China is pleased to host a five-day Business Analytics program in partnership with the Robert H. Smith School of Business at the University of Maryland. Smith is a world-class business school with an Executive MBA that was ranked No.11 in the US by The Financial Times (2014) and No.44 in the world.
The Business Analytics program will blend a focus on data analytics with a focus on social media and web analytics.
Who Should Attend:
The Business Analytics program targets high-potential senior- and mid-level managers in marketing, information systems, operations, supply chain, HR and other functional business areas who have a strong desire to use data analytics as well as social media and web analytics to drive business. The ideal program participant will have at least five years of management experience. The topics covered would be relevant both for managers in established business analytics groups as well as those interested in learning how to lead change in this direction.
Program Requirements:
Participants will need a laptop with a Windows operating system to use for hands-on data exercises during class. Participants will need Microsoft Excel software installed on their computers prior to class and will download two Excel plugins – XLMiner and NODEXL – for use in class.
Part I. Session on Data Analytics
“Data is the new oil.”
In business magazines, on TV and in board rooms, the topic of “big data” is hot. Technological advances in the last decade have enabled the capture, storage and processing of massive amounts of data – including new types of data such as web traffic, social network data and reviews and comments on websites – which can be analyzed in real-time using ever more powerful computers. The great companies of our age, such as Amazon, Alibaba, Facebook, Google and Netflix, have distinguished themselves by their capability in the use of data and algorithms. This module will provide an introduction to the essential tools and techniques of data mining and predictive analytics. Examples from marketing, finance, healthcare and operations management will be used to illustrate the many different ways in which data and analytic techniques create value for companies. Program participants can expect to take their business analytics skills to the next level, and will learn how to effectively use data to improve their organization’s performance.
Program participants will:
• Learn how to integrate business analytics with strategy, overcoming organizational and cultural challenges in the process
• Understand how to leverage data and improve organization performance by studying the example of leading companies
• Learn the fundamental data analytic concepts and techniques required to make effective use of large amount of data
• Develop an understanding of cutting-edge ideas in visualization, association, classification and causation, and learn how these can aid better decision-making
• Study a range of business applications – such as targeting in marketing campaigns, customer retention, fraud detection, loan default prediction, collaborative filtering – so as to be better equipped to develop solutions for problems facing their own company
• Learn how to avoid common pitfalls and ensure a successful data-mining project
• Gain hands-on experience using realistic datasets and data-mining software
Software:
The software we will use for this course is XLMiner. A six-month license comes bundled with new copies of the textbook. Basic guidance for using R (an open source language widely used in industry) can be provided to anyone who is interested.
Part II. Social Media and Web Analytics
Businesses today operate in a world that is changing faster than they can cope with. Traditional product- and service-based strategies are no longer sufficient in a world where firms and consumers operate in a highly networked environment, and a constant diffusion of new technologies is rapidly changing consumer behaviors and firms’ competitive landscapes. It is becoming more important than ever for businesses to craft strategies that leverage the vast amounts of data provided by the digital footprints of their customers. Predictive analytics, particularly social media analytics and web analytics, can provide clear and actionable initiatives based on existing company data as well as data gathered from online channels and platforms. This module on social media and web analytics provides business executives from a wide range of professional backgrounds the conceptual understanding and the analytical skills they need to succeed in today’s rapidly changing environment. Social media and web analytics is the logical next step for business professionals and managers using traditional business analysis techniques and seeking to leverage the power of the web and emerging online platforms.
Program participants will:
• Understand fundamental concepts and issues relating to online networks, platforms and the sharing economy, and the opportunities and challenges these developments pose for businesses
• Learn how social network analytics and the use of social network analytic tools can help understand customer and competitor networks
• Gain hands-on experience with social network and social media analytic tools and techniques
• Learn how to apply social networks analytics tools and techniques to identify, and target influential customers and partners, and craft marketing, pricing, and positioning strategies that leverage social network information
• Learn how to apply social network tools and techniques to leverage data from online social media platforms as well as data about networks within your organization and industry
• Understand the emerging online sharing (peer-to-peer) economy and how they are changing consumer behaviors and what it means for your business
• Gain hands-on experience with sponsored search and web analytics and learn how to measure performance and drive conversions
Software:
NodeXL Add-in to Microsoft Excel. Available for download from http://nodexl.codeplex.com/
Program Faculty
Dr. Siva Viswanathan is an Associate Professor at Smith. He is also the Co-Director of DIGITS – the Center for Digital Innovation, Technology, and Strategy. Viswanathan's research focuses on business intelligence and predictive analytics and their transformative potential in a variety of sectors including financial services, consumer retailing, auto-retailing, telecom and advertising. He also studies emerging issues related to online firms and markets, and the competitive and strategic implications of new information and communication technologies. His current work focuses on online crowdsourcing and crowdfunding platforms, social media and web analytics. Viswanathan’s research has appeared in top academic journals including, and he is on the Editorial Board of MIS Quarterly, a top-tier academic journal, and is also an active participant in international conferences and industry forums.
Viswanathan has also been actively engaged in consulting and research with a number of leading organizations including Adobe, LivingSocial, Facebook, Efficient Frontier, A9, Amazon, HomeDepot, J.D.Power and Infosys. Viswanathan teaches graduate courses on Digital Businesses and Markets, Google Analytics, and Social Media Analytics. He also teaches a PhD seminar in Information Economics. As a co-director of DIGITS, Prof. Viswanathan also co-organizes the D.C. Forum on Digital Innovation, which brings together leaders from government, industry, and academia.
Viswanathan currently lives in Maryland with his wife and two children. Prior to becoming a US citizen, he was a resident of Hong Kong and Singapore.
Dr. Kislaya Prasad is a Research Professor in the Decision, Operations & Information Technology Department and Director of the Smith School’s Center for International Business, Education and Research. He is also a Guest Scholar at the Brookings Institution’s Center on Social Dynamics and Policy in Washington, D.C., and an External Scientist at the Johns Hopkins Center for Advanced Modeling.
Prasad received his Ph.D. in Economics and M.S. in Computer Science from Syracuse University. His previous positions include Professor of Economics at Florida State University and Research Officer at the University of Cambridge. He has also been a Visiting Professor in the Kellogg Graduate School of Management at Northwestern University and in the Economics Department at New York University. His research has been published in leading economic journals and funded by grants from the National Science Foundation.
As an expert on advanced business analytics and data mining, Prasad has worked on several consulting engagements with industry and with international development agencies. Recent work has included assessing the economic impact of infrastructure investments in Asia for the ADB, and detecting fraud, waste and abuse in the healthcare industry.
Prasad teaches data analytics in the EMBA, MBA, and MS programs at the Smith School and has won numerous teaching awards, including the University Teaching Award at Florida State University in 2001-2002 and the Smith School’s Krowe Award for Teaching Excellence in 2010. He has previously taught data mining in the Smith School’s EMBA program in Beijing.
领导力与管理培训：商业大数据分析
本次课程将提供中文同声传译
在如今这样活跃的商业环境下，公司的成功与它通过数据打造战略优势的能力联系越来越紧密，包括网站、顾客和社交网络数据。想要学习如何分析和解读数据来为决策服务，企业管理者需要理解用于数据挖掘和预测分析中使用的主要工具和技术，以及他们的优缺点。本次商业大数据分析课程将带领管理者深度理解如何有效运用数据来提高公司效益，并提供最新工具和技术的实操经验，教授如何 利用大数据推动商业决策。
中国美国商会和美国马里兰大学史密斯商学院联合推出为期五天的商业大数据分析培训课程。作为世界顶级商学院，马里兰大学的工商管理硕士项目（EMBA）在美国排名前11位（The Financial Times 2014 年排名），世界排名17名（BusinessWeek 2013）。
此次商业大数据分析课程将聚焦大数据分析并融合社交媒体和网络分析。
课程适合人群：
我们的商业大数据分析课程针对营销、信息系统、运营、供应链、人力资源及其他功能性商业领域希望通过数据分析、社交媒体和网络分析推动商业发展的极具潜力的中高层管理者。理想的参与者应拥有五年以上的管理经验。课程主题既适合已涉足商业分析，也适合有兴趣了解如何向该方向转型的管理者。
项目要求:
参与者需携带拥有Windows操作系统的笔记本电脑以配合课堂实操数据练习。参与者需于课前在电脑中安装Microsoft Excel软件及其两个插件——XLMiner和NODEXL，以便课堂使用。
第一部分 大数据分析课程
“数据是新的石油。”
在商业杂志、电视和会议室中，“大数据”往往是一个热词。近十年科技的进步使得庞大的数据得以被捕捉、存储和处理，包括网站流量、社交数据、网站评论，这些数据可以在实时工作的强大电脑上进行分析。当下众多大型公司，如亚马逊、阿里巴巴、Facebook,、Google和 Netflix就是依靠其使用数据和算法的能力是自己脱颖而出的。我们将会介绍数据挖掘和预测分析的必备工具和技能。我们将选取营销、金融、医疗和运营管理的案例讲解数据和分析技能以多种方式为公司带来价值。课程参与者将会得到商业数据分析技能的提升，并学会如何有效用数据提升他们公司的绩效。
培训项目的目标：
课程参与者将能够：
• 了解如何将商业大数据分析与企业战略融合，克服来自组织构架与企业文化方面的挑战；
• 从成功企业的案例中学习如何利用大数据提升企业绩效；
• 了解数据分析的基本概念和高效利用大数据的技能；
• 进一步理解关于可视化、联系、分类和因果关系的前沿理念，并了解这些理念如何有助于决策过程。
• 学习一系列商业应用，例如针对营销活动、客户维系、欺诈识别、贷款拖欠预测、协同过滤—以更好地应对公司面临的问题。
• 了解如何避免常见的错误，确保成功挖掘数据；
• 使用真实数据收集及数据挖掘软件，获得实际操作经验。
软件：
本课程所使用的软件为XLMiner，教科书附赠该软件的6周使用证书，对有兴趣的学员，我们可提供R预言（一种工业中广泛采用的开放源码语言）的基础指导。
第二部分 社交媒体与网络大数据分析
如今的商业运作飞速变化，甚至无法应对。基于传统产品和服务的战略已经不能满足这个企业和顾客都高度依赖社交关系的商业环境了，不断传播新科技迅速改变着消费者的行为和企业的竞争环境。利用顾客的数字足迹提供的庞大数据制定商业战略变得越来越重要。在公司已有数据和线上渠道或平台收集到的数据的基础上，预测分析，尤其是社交媒体大数据分析和网络大数据分析可以提供清晰、深刻和可行的方案。社交媒体和网络大数据分析模块给来自各专业背景的企业家一个概念性的理解，并教授分析技能来帮助他们在现今快速变化的商业环境中取得成功。如果您是过去使用传统商业分析方法、现在希望充分利用网络和新兴线上平台力量的企业家和管理者，那么社交媒体和网络大数据分析则是您理应选择的下一步。
学习目标：
课程参与者将能够：
• 理解有关线上社交、平台和共享型经济的基本概念和问题，并了解他们给商业带来的机遇和挑战；
• 了解社交网络大数据分析和有关工具如何帮助企业理解消费者和竞争者；
• 获得有关社交和大众媒体分析工具和技术的宝贵实践经验；
• 学习如何运用社交大数据分析工具和技术去识别、锁定重要客户和合作伙伴，并利用社交信息制定营销、价格和定位战略。
• 学习如何运用社交大数据分析工具和技术从社交媒体平台和机构或产业自身的社交网络数据中提取有价值的数据。
• 帮助您更好地理解新兴分享型经济（P2P）并了解它如何改变顾客行为，以及对您的意义。
• 获得有关赞助搜索和网络分析的实践经验，并能了解到如何评估商业表现、推动转变。
必备软件：
Microsoft Excel 及其插件 NodeXL，下载地址：http://nodexl.codeplex.com/
项目负责人员
Siva Viswanathan博士是马里兰大学史密斯商学院副教授。他也是DIGITS（数字创新、科技与战略中心）的主任。Viswanathan博士致力于研究商业智能和预测分析，及其在包括金融服务、零售、电信和广告等领域中的变革性潜力。他的研究还涉及关于线上企业和市场的新兴问题，和新兴信息和传播技术的富有竞争力和战略性的影响。他目前的研究聚焦于众包和众筹平台、社交媒体和网络分析。Viswanathan教授的研究发表于顶级学术期刊，如Management Science, Information Systems Research, Journal of Marketing, Journal of Marketing Research, Decision Support Systems, 和MIS Quarterly。他是一本顶级学术期刊MIS Quarterly的编委会成员。同时，他也是国际会议和行业论坛的积极参与者。
Viswanathan教授还积极参与Adobe、LivingSocial、Facebook、Efficient Frontier、A9、Amazon、HomeDepot、 J.D.Power 和 Infosys等顶级机构的咨询和研究。他目前正帮助中国一家餐饮连锁理解顾客选择的不同呈现形式的影响。Viswanathan教授负责讲授数字企业和市场、谷歌分析，和社交媒体分析等硕士课程，同时也教授一门有关信息经济的博士课程。作为DIGITS中心的主任，Viswanathan教授还联合组织了关于数字创新的D.C论坛，将政府、行业，和学术的领军人物汇聚一堂。Viswanathan教授是纽约大学博士，企业管理硕士和工程学士，目前与妻子及两个孩子住在马里兰。在成为美国公民之前，他居住在香港和新加坡。
Kislaya Prasad博士是决策运营与信息技术学院的研究教授，也是史密斯国际商务教育和研究学院主任。他也是华盛顿布鲁金斯学会社会动态与政策中心的特约学者，也是约翰霍普金斯中心高级建模方面的外部科学人员。
Prasad博士在雪城大学取得经济学博士和计算机科学硕士学位。他曾任佛罗里达州立大学经济学教授和剑桥大学研究员，西北大学凯洛格管理学院客座教授，纽约大学经济学院客座教授。他的研究发表在顶级经济学期刊中并获得了美国国家科学基金会资助。
作为高级商业分析和数据挖掘的专家，Prasad博士与行业和国际发展投资机构有过众多咨询合作。近期的工作包括为亚洲开发银行评估亚洲基础设施投资的经济影响，以及监控医疗行业的欺诈、浪费和滥用行为。
Prasad博士在史密斯商学院教授EMBA、MBA和硕士项目的数据分析课程，曾获得多项教学奖项，包括2001-2002年度佛罗里达州立大学教学奖和2010年史密斯学院优秀教学Krowe奖。他曾在史密斯商学院在北京开设的EMBA项目中教授过EMBA数据挖掘课程。
Venue:
May 11-13: AmCham China Conference Center, The Office Park, Tower AB, 6th Floor No. 10 Jintongxi Road, Chaoyang District, Beijing 100020 PRC
May 14-15: Salon 1, Beijing Marriott Northeast Hotel 26A Xiao Yun Road, Chaoyang District, Beijing
May 11-13: 中国北京市金桐西路10号,远洋光华国际AB座6层. 100020
May 14-15: 北京市朝阳区霄云路26号A 北京海航大厦万豪酒店 Salon 1厅
Program:
8:30-9:00 - Breakfast
9:00-12:15 - Morning Session
12:15-13:15 - Lunch
13:15-16:30 - Afternoon Session
Registration:
Cardholding members advanced discounted online price: RMB 46,800
Non-cardholding employees of member companies: RMB 46,800
Non-members: RMB 49,600
Special Registration Information:
• You must register in advance. Walk-ins will not be accepted. • Attendees need to pay by March 30, 2015. • Limited spots are available and attendance is given on a first-come, first-served basis.
AmCham China Events:
Events have limited seating so to ensure your attendance we encourage advance online registration and payment for ALL events. We cannot guarantee entry to anyone not registered in advance. All AmCham China events are in English unless stated otherwise. Please also be aware that the Member Advanced Price is only for members who register AND pay online prior to the closing date and time for this event. Members who do not register and pay online will be charged the At-The-Door price.
This event is off-the-record.
For more information, please contact: Caroline Wang, Tel: (8610) 8519-0892, Email: [email protected].
Cancellation Policy:
If you cannot attend an event for which you have registered, please cancel your registration no later than one business day prior to the event. If you fail to notify AmCham China of your cancellation in a timely fashion, you will be charged for event costs.
To cancel you can 1) call 8519-0828 and leave a voicemail message including your name, and event title and date, 2) email [email protected], or 3) cancel online if you registered for the event through the website. Thank you for your cooperation and helping AmCham China maintain the quality of its events.
Receipts:
Please note: Requests for official payment receipts for 2013 (fapiao) must be submitted to AmCham China before December 25, 2013. Requests made after that time will not be accommodated. Please contact [email protected].
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