On April 22, the Swedish Chamber of Commerce in China invites our members and friends to a full-day training in Shanghai on "AI Data Analysis Empowered Business Decision-making/AI数据分析工具助力业务决策" and this training will be conducted in Chinese language.
Introduction/课程介绍
We need to make decisions for business performance at work. However, decisions are often based on experience, intuition, and even panic reactions under pressure. Whether they are correct or not is simply a matter of luck. Digitization makes it easier to obtain data, but we often struggle to draw valid conclusions when faced with massive amounts of data. This course is designed to overcome the above dilemmas. It helps students build a data analysis empowered decision-making mindset. The course is systematic and practical:
• Systematic: organically insert data analysis tools into a clear overall framework of decision-making. Students will master a systematic approach rather than discrete tools.
• Practical: With a Business Performance Improvement simulation case-tudy embedded, students could actively practice the tools. Not only to learn the "what" and "why", but also master the " how" and achieve visible results onsite.
• Easy to Master: Traditional data analysis content often requires coding or complex operating, but in the data analysis section of this course, you only need speak"human language" to AI and get accourate data analysis result effortlessly.
工作中我们为了业务表现需要做出决策,然而,这些决策的依据常常是经验、直觉、甚至是压力下的慌乱反应,正确与否全拼运气。数字化让获取数据变得容易,然而,面对海量数据我们却常常无从下手,苦于得不出有效结论。基于数据的业务决策课程专为破除以上困境设计,旨在帮助学员建立数据导向思维和科学决策习惯从而在工作中提升业务表现。本课程兼具系统化、实操性、易掌握三个特点:
• 系统化:从思维方式入手,为学员搭建起清晰的科学决策逻辑框架,并在合适的步骤中有机地插入数据分析工具,内容关联紧密。学员将掌握系统性的方法,而非相互割裂的单个工具。
• 实操性:培训中贯彻了一个沉浸式的业务表现提升沙盘模拟,学员将把所学工具带入该场景实操练习,不仅能学会"是什么"和"为什么",还能在培训现场掌握"怎么做"并取得可见的成果。
• 易掌握:传统数据分析内容往往需要掌握编程语言或复杂的工具操作,而在本课程的数据分析部分,你只需要"说人话"就可以让AI帮你完成复杂的数据分析。
Target Audience/目标学员
Professionals in all industries and positions who is in need of business performance improvement and/or data analysis, including but not limited to R&D, production & operation, sales, SCM, HR, admin, marketing, OpEx, etc.
有业务表现提升和/或数据分析需求的企业各职能人群,包括但不限于研发、生产运营、销售、供应链、人士、行政、市场、卓越运营等。
Teaching Method/授课形式
Lectures, case study, group discussion, group exercise, simulation game
课堂讲授、案例分析、分组讨论、小组练习,模拟游戏
Objective/课程目标
Through this course, participants will be able to:
· Change the mindset: get rid of their fixed pattern for problem solving and data analysis, while establishing a systematic decision-making mindset based on data analysis
· Master the method: master the approach to improve business performance through systematic decision-making
· Upgrade the skillset: be proficient in using data analysis tools such as hypothesis testing, correlation analysis, regression analysis, etc., and mastering the logic principles
· Master AI Data Analysis: Learn how to perform data analysis using AI tools.
· Solve a real problem: participants will improve the business performance of stimulatied operation case.
在课程结束时,学员将:
• 改变固有思维模式:打破"跟着感觉走"和"被数据推着走"的固有模式,建立基于数据分析的科学决策思维
• 掌握问题解决方法:掌握通过科学决策提升业务表现的方法
• 熟练数据分析工具:熟练使用假设检验、相关分析、回归分析等常用数据分析工具,并掌握背后原理
• 学会AI数据分析:掌握通过AI工具完成数据分析的方法
• 解决实际工作问题:通过模拟游戏,在培训现场实现某个真实运营场景的业务表现提升
Outline/课程大纲
Part One: Establish the Mindset
· Interaction Case 1: Scientific decision-making mindset
· Interaction Case 2: Correct data-driven mindset
· Reflection: How to build a data analysis empowered decision-making mindset
Part Two: Master the Approach
· A simulation case study for business performance improvement (initial status)
· Step 1: Understand the problem itself
o Establish problem indicators
− SMART principles
o Clarify the essence of the problem
− From "Voice of the Customer" to "Critical Quality Characteristics"
o Team exercise 1: practice phase 1 tools in the simulation case
· Step 2: Assess the Current State
o Scientific data collection
− Data collection approach
− Reliability of data collection
− Statistical sampling basics
− Sampling strategy
o Effectively present data collection result
− Key statistics
− Key performance indicators
− Visualization
o Team exercise 2: practice phase 2 tools in the simulation case
· Step 3: Find out the root causes through AI empowered data analysis
o Data analysis foundation
o Hypothesis test
o Correlation
o Regression
o Above-montioned data analysis using AI tools
o Team exercise 3: data analysis practice with the simulation case data (using AI tools)
· Step 4: Make scientific decision
o Generate potential solutions: structured brainstorming
o Select the optimal solutions: prioritization tools
o Team exercise 4: decision making practice based on the simulation case
· Summary and recap
第一部分:建立思维方式
· 互动案例1:科学的决策思维
· 互动案例2:正确的数据思维
· 思考:如何建立基于数据分析的科学决策思维
第二部分:掌握方法工具
· 某业务表现提升模拟情景的背景介绍(初始状态)
· 第一步:明确问题本身
o 设立问题指标:SMART原则
o 明确问题本质:从"客户的声音"到"关键质量特性"
o 团队练习1:第一阶段工具在模拟情景中的实操练习
· 第二步:通过数据衡量现状
o 科学收集数据
− 定义数据收集方法
− 检验数据收集方法的可靠性
− 理解抽样原理
− 选择抽样方法
o 有效呈现结果
− 关键统计量
− 流程表现指标
− 可视化
o 团队练习2:第二阶段工具在模拟情景中的实操练习
· 第三步:通过AI助力的数据分析工具识别根本原因
o 数据分析基本原理
o 假设检验
o 相关分析
o 回归分析
o 以上数据分析在AI工具中的实现
o 团队练习3:基于模拟情景中数据的定量分析工具实操练习(需使用AI工具)
· 第四步:做出科学决策
o 生成潜在方案:结构化头脑风暴
o 筛选最优方案:优先级排序工具
o 团队练习4:基于模拟情景的科学决策练习
总结与回顾
Trainer/讲师
Nadya Liu
Date/日期
22 April, 2025 (Tuseday)
Time/时间
9:00 - 17:30, Beijing Time
Price/价格
Member: 3050 RMB
Non-Member: 3650 RMB
Early Bird for Members only: 2895 RMB (valid until 1 April, 2025)
Small (3-5 people) & large group (10 people) tickets are also available, please contact jonatan@swedcham.cn for more info about group ticket.
Language 培训语言
The workshop will be held in Chinese.
本次培训以中文进行
Venue 地点
SwedCham Shanghai Office
中国瑞典商会上海办公室
Livat Office, Room 601, Office Tower D, No. 788 Jinzhong Road, Changning District, Shanghai, P. R. China
上海市长宁区金钟路788号荟聚(Livat) 办公楼D栋6楼D601
Cancellation Policy
If you cannot attend a training for which you have registered, please cancel your registration no later than seven business days prior to the event. If you fail to notify us of your cancellation in a timely fashion, you will be charged for the training costs.
Fapiao (VAT Invoice)
Apply fapiao when purchasing a ticket, by inputting the Chinese entity name and tax ID (if the title is wrong, you will be unable to receive the Fapaio). Make sure your IT has whitelisted the domain "XX@hlzrkj.xyz. E-Fapiao will be sent to your e-mail within 7 days after completed event (check spam folder). If the fapiao can not be received, please provide an alternative email or contact finance@swedcham.cn.