how many drivers does uber need to serve the bay area
hey everyone welcome back to another exponent product management mock interview my name is kevin
and on today's show we have selena we're going to be doing an estimation question but before we
dive into that selena do you mind just telling the audience a little bit about who you are
yeah for sure and thanks for having me um i'm selena i'm a product manager at google and i've
been there about two years now and prior to that i was an apm at yahoo cool thanks for
coming on today's show we're going to be doing an estimation question like i said and this is what
i'd like to ask i'd like for you to tell me how many drivers does uber need to serve the bay area
how many drivers does uber need to serve the bay area okay i'm typing but nothing is writing
okay there we go there's a little bit of a lag awesome so i am gonna assume that when we say uh
the amount of drivers that uber needs um they're talking about not necessarily how many people are
like you know on staff in general just more like given some peak traffic time how many uh drivers
are needed to cover that demand yeah we can do that that sounds good awesome cool so then um
let's say uh let's say we're just gonna visualize like you know it's a friday afternoon at like 5
30 pre-covered conditions like people are either coming back from work or going out to like dinner
with their friends and so at a really high level the way i think we can approach this
is um we want to know how many you know writers are being demanded per you know this peak traffic
hour um sorry rides are being demanded uh per peak traffic hour and then we also are going to
want to calculate how many of these rides per driver um can be done within an hour as well
um and so if we take the demand and divide it by uh the supply we'll come out with the number
of drivers in the end so basically rides per hour divided by um rides uh per driver per hour
will get us the number of drivers awesome so if we tackle the left hand part of this first um
in order to find how many rides are being demanded let's sort of take a sense of like how many people
we're working with in general so i know that there are about seven million people in the bay area and
you know if we sort of think about the types of people who would be picking uber
um someone who's under 18 can't really take uber because it's part of just their policy and say if
you're above you know 60 you might be too old to be familiar with the technology um and so
let's say we have like a 80-year life expectancy for people um and if we assume
a uniform distribution of ages uh cutting out under 18s and over 60s that's going to be about
3.5 million people who could potentially use uber alrighty and so now that we have uh this number um
i also want to call out that the amount of rides would differ depending on where you are in the
bay area um so i don't know if you're familiar but you know an sf most people don't have cars
they walk they depend on public transportation um and in the south bay things are much more
spread apart so like most people actually do have a car um and so you know the demand would be less
there so um i do want to break it out by like sf versus everywhere everywhere else um and so i know
that sf has a population of uh one million and so if we just subtract out like for everywhere else
that's gonna be like 2.5 million people um does this make sense so far yeah yeah this
is a good segmentation on the geography and for for the people who who might not be familiar um
sf is more city-like whereas everywhere else is a little bit more suburb-like
yeah exactly um cool so now if we want to sort of take these two separate geographies um you
know not everyone out of these 1 million and 2.5 million cohorts are going to be ubering again like
some people might walk drive you know shuttle if you're working in tech um and so i think
one way to sort of approximate this is you know given uh most people in sf do not have a car um
and you're thinking about the average friday night uh we know there's three people per household you
know maybe you have roommates maybe you're a small family um and so if that's true that's going to be
a and you say one person per household has plans that are not within walking distance or on like
a bart line um so that would give us 33-ish percent of the 1 million um which is about
333. let's just make it 350 to make it a little bit easier on us in the future um
and so that would be how many rides per hour are coming from us and so given what i said earlier
about the south bay just having like way more cars i would i would um guesstimate that the demand is
probably 10x less um like literally everyone has a car here so if we just sort of um cut that down
to 10 we would get point five k um or sorry yeah three uh we would get three point three percent
um which let's make that five percent for math um and then five percent of 2.5 million
is 125 k i believe and so if we total up 350 k plus 125k that will give us
the total number of rides in the bay area in that given hour and that's about 475k
alrighty okay so that's the first part of the equation now we kind of have to think about
okay out of all these rides um how many rides can a single driver handle per hour
and so um let's see i think you know when i think about the average trip in an hour
um i'm thinking it might be you know 15 minutes if we if we decide to include uberpool because uber
has a benefit of like you don't have to go back to the start you can just pick up where you left
off and start taking the next person to wherever they're going um so keeping that in mind um i
think a 15-minute trip is reasonable so it would be you know four trips per hour and you know given
the popularity of pool let's say um on average like you know you have the single riders but you
also have you know pools with like you know three to four people so maybe like two people per trip
and of course we can revisit this based on like how many people we think are actually
using pool versus other types of uber but for now like let's go here um so that's gonna be
um eight rides per driver per hour okay so now if we go
back to the original equation we wanna take these two numbers and divide and so we get 435k
divided by eight and that is about 60 62 k let's just say 60k
um okay so now i've gotten to some final answer i kind of want to check to see if this is close um
one way i might think about is like out of a seven million person population like how many do i think
are actually uber drivers and 60k is a little less than one percent of the total population of
the area it actually makes a lot of sense um like you know given tech is a really big industry here
i don't imagine um you know more than one percent of the would you know have the dispensable income
to like spend on ooze and so it makes sense that you know less than one percent of the population
uh would be you know drivers for people that can afford extra rides um so i'll pause there in case
you have any questions on how we got here yeah this this totally makes sense one question that
i have you don't have to go through the math for this but you made the assumption here that we're
that customers are taking uberpool what if this is during covet times but with the same demand as
non-cova times and everyone wants to take uberx so uh one customer per car
where would you change some numbers if you had to go back and make those changes
yeah good question so assuming you know we're in covit and they've not allowed pools um this part
would go away it would basically just be like a very serial process you would have to pick up one
person at a time but four would remain the same because i'm assuming the distance that someone
is going is still about the same okay um and if you i think in here you you made some pretty good
assumptions where most of these based around your intuition and if so what sort of additional data
might you take if you had access to additional data to make your estimation more accurate
yeah definitely i think um a lot of my more like intuitive guesses are around like how many trips
per hour and how many people would be in said trip uh if i had data around like the split
of usage between like uberx uber like is it called luxury uberpool um we would be able to have a more
accurate estimate of how many people provide um and then if i had data around like how far
you know different mooney and bart stops are and what the split of geography in terms of
um public transportation coverage um i could potentially do a better job with the number
of trips per hour like for example maybe it takes longer to get places in the south bay
and so we would want to split like maybe it's like two rides per hour in the south bay
but in sf maybe it's actually much shorter rides and maybe it's actually like five or six
um so i would want to layer that in as well cool um yeah i i think that makes sense i
think your gut check makes sense is there anything else that you might want to mention
um no i think um overall uh yeah i think the gut check makes sense um i think
uh given that given that we're thinking about like the total number of drivers it was important that
we think about peak only because from like a user experience perspective like that's all that really
matters like we don't care about the lazy you know sunday where no one is going anywhere um the peak
is what really matters here totally great so i'll take off my interviewer hat i've written down some
feedback here that i'd love to share with you and at the end i'd also love any tips that you might
have for the audience who might be preparing for an estimation type interview so i think i
think you did a really good job in the beginning clarifying what the question means i think with
this question it could mean any number of things you wanted to focus on peak time which is fine um
i think there are some other approaches you could have taken one was like what you mentioned take uh
looking at the aggregate number of drivers needed that that would have been a whole another
uh route um if you went that path you also had some pretty good assumptions that you say to them
up front such as assuming that the people with 0 to 80 life expectancy have uniform distribution
i think you also did a good job breaking down the geography so uh taking the bay area and
not treating it as some uniform land mass but really thinking about sf and non-sf and
yeah you also did a great job of showing your soft skills in terms of not just answering the
question but also taking the time to check in with me making sure we're on the same page and making
sure that uh you you check to see if this was an overestimate or an underestimate at the very end
so um all in all great answer and yeah i'd love to hear if you have any tips for the audience
who might be preparing for their own estimation question interviews yeah awesome thank you for
that feedback i think i agree with the general feedback you gave i think it's important um
after like every big chunk of your answer to just pause and give your interviewer a chance
to interject um because they probably do want to ask questions at some point they don't want to be
silent the whole time and another one is yes just being really clear where you're making assumptions
and where you don't have the data and just telling your interviewer like hey like if at the end we
aren't really happy with the outcome like let's go back and visit like this particular estimation
cool thanks selena and that's it for today's video for the audience good luck with your upcoming
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