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Which analysis breakdown should we use?

A simple example: A firm has two segmentations: by region and by product. The region segment revenues fell by 100M each, but in the product segment, all of it rose except for a product that declined by 500M. So we obviously know the issue is with that product right?

What about firms with 10-20 segmentations? Are we expected to drill down on each? Im struggling with this hypothesis approach thing, as it seems that it could easily be wrong and could lead us off the track? What does it actually mean to have a hypothesis? Is it even effective when its changing everytime I do an analysis?

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Top answer
Hagen
Coach
edited on Oct 28, 2024
#1 recommended coach | >95% success rate | 8+ years consulting, 8+ years coaching and 7+ years interviewing experience

Hi there,

I would be happy to share my thoughts on your questions:

  • First of all, I would highly advise you not to worry as you will not realistically be faced with such a multi-causal case study as it would simply take too long.
  • Moreover, I would advise you not to overthink hypotheses. Ultimately, they are nothing more than opinions based on a limited but insufficient amount of data to call them truth.
  • Lastly, I would advise you to consider working with an experienced coach like me on this. I developed the “Case Structuring Program” to help exactly such candidates like you who struggle with properly structuring any case study.

You can find more on this topic here: How to succeed in the final interview round.

If you would like a more detailed discussion on how to best prepare for your upcoming interviews, please don't hesitate to contact me directly.

Best,

Hagen

Alessa
Coach
on Oct 26, 2024
xMcKinsey & Company | xBCG | +200 individual & group coachings | feel free to schedule a 15 min intro call for free

Hey there! 

I would say that the goal is to focus on the most likely drivers of a problem rather than analyzing every possible segmentation. 

Here’s how I would approach it: Formulate an initial hypothesis based on the data (e.g., one product declined by $500M while regions saw smaller declines) and start with a working hypothesis that the major issue could be in that product line. This gives direction without locking you into an assumption. Test key drivers first by focusing on primary factors that significantly impact the overall metric—in this case, revenue for the product line in question. For 10-20 segmentations, begin with the highest-impact ones or those that seem more likely based on initial data. Refine hypotheses as you analyze; it's normal and expected to adjust your hypothesis as new information emerges. 

A hypothesis-driven approach isn't rigid; rather, it helps you avoid “boiling the ocean” by narrowing the focus based on what appears most likely. Use a process of elimination, and if you confirm that a key factor (like a product or region) isn’t the primary issue, move to the next hypothesis. You don’t need to drill down into every segmentation unless no clear drivers emerge. 

In summary, a hypothesis-driven approach is effective because it helps structure your analysis by prioritizing high-impact segments. As you analyze, it’s okay for your hypothesis to evolve. Think of it as a guide to focus your efforts—not a fixed answer.

Hope that helps! Alessa :)

Ashwin
Coach
on Oct 27, 2024
Bain Senior Manager , Deloitte Director| 200+ MBB Offers | INSEAD

Hi,

Assuming you’re referring to diagnosing an issue before exploring solutions, start by asking the interviewer which segmentation type (e.g., product or geography) the client uses. Focus on the high-impact segment and drill down until you identify the quantitative problem driver. For instance, if product segment 1 shows a decline, check if it’s due to volume or price.

Once you isolate the issue (e.g., volume decline), ask 'how' and 'why' questions to uncover the underlying cause, then propose measures to address it.

All the best, 
Thanks Ashwin 

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