# Market sizing assumptions/structure

marketsizing
Recent activity on Nov 21, 2018
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Hi,
I was recently told I should be more structured when I approach calculations for market sizing in case studies, by first saying what I will be looking at and only then proceeding with calculating/making assumptions.
As far as I agree with this, I would like to know when do you think it is "too forced" to first state what you are going to do and then do it rather than proceeding with the calculations in the first place when stating what you are going to do ? At what level of detail can I just proceed with calculating straight ahead the number without laying out my process before hand?

For example, one of the building blocks of almost every formula is population, should I first state I will first look at which percentage of the population falls within the target range, and then calculate how many people that corresponds to, or should I just say let's assume 50% of the population is in the relevant age range which corresponds to 30M people. (and so on for all the other building blocks of the market sizing formulae.)

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Hi,

First of all - yes you should always tell your approach first.

Secondly - never say - let's assume 50%. Your assumption should always be based on something:

1. Personal experience (e.g. in my apartment building with 100 households, I see 10 people walking with the dogs every morning. So I would assume that 10% households have a dog)
2. General knowledge (e.g. The average family size is 3 people)

You should also adjust your assumption where it's possible (E.g. The average family size is 3 people, but since we are talking about New York where people are mostly single, I would assume the av. household size of 2 people)

Here are some useful market sizing skills:

1) First of all, there are 2 ways to structure market sizing:

• Formula - basically a math formula to come up with a solution. The problem with the formula is that it is easy to forget something or get lost.
• Tree - same as with regular cases you build a tree. A very simple example: you need to calculate the number of dogs on manhattan. A number of dogs = share of households having a dog * # of households. # of households = population / average household size. In the end, you'll have a pyramid where you have to fill the numbers on the base of the pyramid. This approach is much easier and help you track all the numbers

2) You should learn the key market sizing techniques:

• Making assumptions based on personal experiences (Use the example of your house where out of 100 apt-s 10 have dogs)
• Adjusting numbers (NY is a busy city thus fewer people have dogs)
• Sanity check - try to apply your calculations to real environment
• etc.

3) You should learn the key tools:

• Using age even age split (suppose life expectancy is 80 years. Assuming even age split we have 4 mln people in US of each age group)
• Using 80/20 split (suppose 20% people earn 80% wealth and the average salary is xx...)
• Using approximations (Length of NY-SF flight and plane speed to calculate US length)
• etc.

4) Learn key numbers: populations, gas price, gas consumption, Boeing speed and nmber of seats, average salary, # of gates in the airport, GDP growth rate, inflation, etc.

5) Practice 10-15 cases and you'll be fine

Feel free to PM for clarifications

Good Luck!

Hi,

Although it may seem a little forced talking through your approach before you start answering the question, it’s a very important skill to master. In this situation, you need to consider the interviewer as client or co-worker that you’re explaining your methodology to.

The process I like to follow when doing market sizing questions is as follows:

1. Repeat question back to check your understanding
2. Ask clarifying questions – are we talking the number or burger per year or the value of the market (e.g. revenue?) chips included? Drinks?
3. Say ‘Would it be OK if I take 30/60 seconds to gather my thoughts?’
4. Structure your approach on paper – this will come with practice!
5. One your time is up, turn your paper 90 degrees to the interviewer and change your body angle so you’re not directly facing them. The aim here is to demonstrate this is a collaborative exercise and not just you telling the client the solution
6. Talking through your approach with the interviewer. This the high-level structure of your formula or issue tree. Always start with the original objective, ‘in order to estimate the size of X market, I would to consider …’
7. Once you’ve finished explaining your structure, say ‘how does that approach sound to you?’ this provides an opportunity to get some feedback for the interviewer and highlight any major errors before you get into the calculations
8. Once you’ve agreed on an approach, start filling in the numbers – by making assumptions. Use personal experience and proxies wherever possible to inform your assumption making. Again, try and make this is a collaborative exercise. For instance, ‘From my experience of buy product X, I believe the price is between X and Y. Therefore, the average price would Z. How does that value sound to you?’
9. Do the math
10. Sense check your final answer – is it ballpark correct? Correct order of magnitude? Why could it be too small or too big? Talk out loud so the interviewer can hear your thought process
11. Relate the final answer back to the case objective – is this a good market to be in for the client? Would you expect it to get bigger or smaller with time?

You can see that doing the ‘math’ is pretty far down the list. Market sizing isn’t just a numbers exercise!

And here are some consideration when doing MS questions:

• Aim of the game is to demonstrate how to break down a problem and reach a sensible answer – getting to a ‘correct’ solution isn’t very important, it’s the process
• Remember data for population size and the number of households
• Assumptions – life expectancy 80 years, equally distributed between all age group e.g. 0-20 years
• Use nice numbers to make the math simple and round!!

Hope that helps.

Harri

McKinsey / Accenture Alum / Got all BIG3 offers / Harvard Business School
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