The European Chamber Tianjin Chapter is pleased to invite you to join the one-day offline training, "[Data Analysis] AI Data Analysis Empowered Business Decision-making", on 16th September 2025.
中国欧盟商会天津分会诚挚邀请您参加于2025年9月16日举办的线下培训课程 - AI数据分析工具助力业务决策。
In today’s volatile business landscape, professionals face critical decision-making dilemmas—relying on vague intuition when making key business choices or drowning in data without extracting actionable insights. Teams often spiral into trial-and-error cycles when KPIs decline; when questioned by leadership, they lack data-backed justification; when challenged on solutions, "industry norms" replace evidence-based arguments. Compounding this, AI-empowered colleagues solve problems at speed while others remain trapped in manual data processes. This course is designed to overcome the above dilemmas. It helps students build a data analysis empowered decision-making mindset. The course has following advantages:
- 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-study 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 to speak "human language" to AI and get accurate data analysis result effortlessly. Participants can use Excel with Copilot or ChatExcel for on-site practice.
在瞬息万变的商业环境中,许多职场人深陷决策困境——面对关键业务选择时,要么依赖模糊的经验直觉,要么被海量数据淹没却无法提炼有效结论。当KPI下滑时,团队常陷入反复试错的恶性循环;当老板追问决策依据时,只能给出缺乏数据支撑的苍白解释;当汇报被挑战方案合理性时,只能以“行业惯例”搪塞却拿不出有说服力的证据。更令人焦虑的是,掌握AI数据分析工具的人已能够迅速分析解决问题,而自己仍困在手工处理数据的低效流程中。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。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"。
- 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。学员可使用装载了Copilot的Excel或国产工具ChatExcel(酷表)完成演练。
[Language 语言]:Chinese 中文
[Why Should Attend 适合人群]
Professionals in all industries and positions who are 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 授课方法]
Lecture, 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
[Training Outcome 培训收获]
Through this course, participants will be able to:
- Change the Mindset: Get rid of their fixed patterns 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 simulated 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 培训大纲]
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
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
Part Two: Master the Approach
A Simulation Case Study for Business Performance Improvement (Initial Status)
Step 1: Understand the Problem Itself
- Establish Problem Indicators, SMART Principles
- Clarify the Essence of the Problem, From "Voice of the Customer" to "Critical Quality Characteristics"
- Team Exercise 1: Practice Phase 1 Tools in the Simulation Case
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
- 设立问题指标,SMART原则
- 明确问题本质,从"客户的声音"到"关键质量特性"
- 团队练习1:第一阶段工具在模拟情景中的实操练习
Step 2: Assess the Current State
- Scientific Data Collection
- Data Collection Approach
- Reliability of Data Collection
- Statistical Sampling Basics
- Sampling Strategy
- Effectively Present Data Collection Result
- Key Statistics
- Key Performance Indicators
- Visualization
- Team Exercise 2: Practice Phase 2 Tools in the Simulation Cas
第二步:通过数据衡量现状
- 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
- 关键统计量
- 流程表现指标
- 可视化
Step 3: Find out the Root Causes through AI Empowered Data Analysis
- Data Analysis Foundation
- Hypothesis Test
- Correlation
- Regression
- Above-Mentioned Data Analysis Using AI Tools
- Team Exercise 3: Data Analysis Practice With The Simulation Case Data (Using AI Tools)
第三步:通过AI助力的数据分析工具识别根本原因
- 数据分析基本原理
- 假设检验
- 相关分析
- 回归分析
- 以上数据分析在AI工具中的实现
- 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)
Step 4: Make Scientific Decision
- Generate Potential Solutions: Structured Brainstorming
- Select the Optimal Solutions: Prioritization Tools
- Team Exercise 4: Decision Making Practice based on the Simulation Case
第四步:做出科学决策
- 生成潜在方案:结构化头脑风暴
- 筛选最优方案:优先级排序工具
- 团队练习4:基于模拟情景的科学决策练习
>> Payment 付款方式:报名后请将培训费汇款至以下账户,并在银行转账单上附注TJ20251113或 联系商会工作人员付费
A/C Name: 中国欧盟商会
A/C No.: 7110210182500027543
China CITIC Bank 中信银行京城大厦支行
北京市朝阳区新源南路6号京城大厦
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