Course Highlights
  • How to break down problems? How to use hypotheses? How to request data? How to clean data? How to use a DMAIC process improvement framework?
Curriculum

8 Topics
What will you learn in this course?
3.1 Think broadly about the problem
3.2 Scope should be both broad and narrow
Course outline for note taking
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Consulting Fundamentals: Skills tools tips (2023)
Scope creep is scary avoid it
Optional: meet and greet

3 Topics
3.3 Breaking the problems into "buckets"
3.4 Using “logic trees” to connect the “buckets”
Optional BCG reports: Loose dogs

4 Topics
3.5 Hypothesis-based consulting
3.6 Developing confidence in your solution(s)
Bulletproof problem solving (Conn and McLean) 2019 
Hypotheses and data analysis

6 Topics
3.7 Why do consultants love data?
3.8 Messy data is an opportunity
3.9 Data lends credibility
3.10 The journey from data to insights
Superpowers: China Silicon Valley and the New World Order
Why is data so important?

7 Topics
3.11 Data request
3.12 Client follow up (data request example)
3.13 Data cleansing and structuring
Data Analytics Basics for Managers (HBR 2018)
Exceljet.net a great way to learn Excel
Optional: How much excel do you use?
Optional: Do you have a "data challenge" story?

6 Topics
3.14 DMAIC: A key tool for process improvement
DMAIC example: Losing weight
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Data requests and DMAIC
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Consulting Approach to Problem Solving

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