The Training will be conducted in Chinese.

培训语言为中文。

In today's rapidly changing business environment, are you experiencing these challenges?

• The Decision-Making Dilemma: When facing critical business choices, you're forced to choose between relying on vague experience or struggling with unmanageable masses of data.

• The Performance Decline Cycle: Teams often fall into a loop of repeated trial and error with no effective solution when KPIs continue to drop.

• Unsubstantiated Reporting: You can only provide weak, data-lacking justifications for your decisions to leadership, failing to prove their validity convincingly.

• Ineffective Response to Challenges: When your proposals are challenged, you default to "industry practice" as a response but lack compelling concrete evidence.

• The Efficiency Gap Anxiety: While many are already using AI tools for rapid data analysis and precise decision-making, you remain stuck in the inefficient manual processing stage.

On September 16, AmCham China Tianjin, in collaboration with Linke Consulting, launched a Data Analysis Training. This training is designed to help you develop a data-oriented mindset and scientific decision-making habits, ultimately enhancing your business performance at work.

Training Highlights

• 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.

Who Should Attend?

Professionals in all industries and positions who need business performance improvement and/or data analysis, including but not limited to R&D, production & operation, sales, SCM, HR, admin, marketing, OpEx, etc.

Teaching Method

Lecture, Case Study, Group Discussion, Group Exercise, Simulation Game.

Training Outcome

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.

Training Outline

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

• 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

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 Case

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)

Step 4: Make Scientific Decision

• Generate Potential Solutions: Structured Brainstorming
• Select Optimal Solutions: Prioritization Tools
• Team Exercise 4: Decision Making Practice Based on the Simulation Case

Summary and Recap