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Vlad

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Market sizing question: # of vending machines in the US

Hi All,

Just encountered the market sizing question specified in the title. My partner and I came up with two different approaches:

  1. First, divide by the total US population into (i) urban and (ii) rural areas. Next, almost entirely disregard the rural areas, and focus on urban areas, which we further broke down into cities of (a) low, (b) medium and (c) high population density areas. For each of these three, we assigned an average number of people per vending machine (e.g., if high, then 1 vending machine for every 25 people, etc). Needless to say, we assigned weights / percentages along the way.
  2. Divide by places where vending machines are commonly found, such as, office buildings, residental buildings, service places (e.g., gyms, libraries) and most importantly, public places and streets. Next, we sought to go about calculating number of office buildings and other categories, etc. We felt that this approach was more accurate but more time consuming compared to the above approach.

So the question is, (i) what do you think of our two approaches and how would you improve them?, and (ii) what other approaches would you recommend?

Thank you in advance,

PrepLounger

Hi All,

Just encountered the market sizing question specified in the title. My partner and I came up with two different approaches:

  1. First, divide by the total US population into (i) urban and (ii) rural areas. Next, almost entirely disregard the rural areas, and focus on urban areas, which we further broke down into cities of (a) low, (b) medium and (c) high population density areas. For each of these three, we assigned an average number of people per vending machine (e.g., if high, then 1 vending machine for every 25 people, etc). Needless to say, we assigned weights / percentages along the way.
  2. Divide by places where vending machines are commonly found, such as, office buildings, residental buildings, service places (e.g., gyms, libraries) and most importantly, public places and streets. Next, we sought to go about calculating number of office buildings and other categories, etc. We felt that this approach was more accurate but more time consuming compared to the above approach.

So the question is, (i) what do you think of our two approaches and how would you improve them?, and (ii) what other approaches would you recommend?

Thank you in advance,

PrepLounger

1 answer

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Hi,

I would go in a bit different way and calculate:

  1. Split the people into different age groups (80 years life expectancy, 4 mln people in US per age if you assume people being split evenly)
  2. Calculate the vending consumption among each age group (e.g. teenagers, adults, elder) in units (1 unit is either a bottle or a snack)
  3. Calculate the capacity of an average vending machine (e.g. 100 units)
  4. Assume that there is always 30-50% stock left before replacement on average
  5. Calculate the number of vending machines from the total consumption and the replacement rate
  6. You can also make some adjustments for other types of vending machines (e.g. cigarettes)

Best!

Hi,

I would go in a bit different way and calculate:

  1. Split the people into different age groups (80 years life expectancy, 4 mln people in US per age if you assume people being split evenly)
  2. Calculate the vending consumption among each age group (e.g. teenagers, adults, elder) in units (1 unit is either a bottle or a snack)
  3. Calculate the capacity of an average vending machine (e.g. 100 units)
  4. Assume that there is always 30-50% stock left before replacement on average
  5. Calculate the number of vending machines from the total consumption and the replacement rate
  6. You can also make some adjustments for other types of vending machines (e.g. cigarettes)

Best!

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MeGrain is a co-operative of 5000 farmers in the central part of India. As a co-operative, the farmers came together to sell the grains to retailers and wholesalers. They are the 3rd largest grain sellers in India and sell 10million quintals of grains annually. They have operations in 4 regions in ... Open whole case