a) Self-practice recommendations
1. I was wondering how I should go about hypothesis and structuring self practice when online casebook prompts and solutions do not share the metric by which to evaluate the problem in the “interviewer notes to share with candidates” section.
2. Are there any casebooks you can share suitable for self practice with clarifying questions responses included? Usually online casebooks do not share responses to candidate's clarifying questions, such as the success metrics, etc before creating the hypothesis and custom structure / framework.
b) Structuring advice
1. I find it hard to know how to structure framework with just qualitative factors and not success metrics? Any tips here?
c) Clarifying questions
1. Should I aim to get specific numeric information within the Q/A clarifying questions portion like the market size or growth rate? I thought specific data questions like this should NOT be asked early on (only broader issue defining questions)?
2. Are these 6 questions a good template to ask during the Q/A clarifying portion even thought I understand not all information will be shared from each of these questions? I also understand these questions are more than the typical 2-3 questions as part of convention.
1. Motivation behind phenomenon
2. Time frame behind phenomenon or how long the business has been in operation
3. Business model of client / industry, with drivers of revenue streams and customer base types
4. How to define success / metrics or any particular priorities?
5. What does "xyz" refer to / how will it be measured (ex. "growth")?
6. Any additional context you feel is relevant?
Thank you!
- Logistics?
1. what to say when receiving it
2. how long to pause and what to do / study during pause
3. what to say after pause?
- Insights?
1. what trends/insights to share with interviewer and how long should it take? 2. how long to keep on discussing patterns on the data?
- Calculations?
1. Should the interviewer prompt us to make a calculation on the graph, or should we the candidates be the one to say we would like to calculate "xyx" given this data?
- Connecting it back to case / hypothesis / etc?
1. How should we go ahead and connect our chart insights back to the case and share a "so what"?
2. Should we try to do this "so-what" step pre-calculation or post-calculation, or during both times, and 3. what should we say to effectively make a true link / share the "so what" aspect?