YT YouTube2Text

YouTube2Text → Transcripts → Case Interview Fundamentals: Lesson 26 [Drill: Sports apparel retailer]

Case Interview Fundamentals: Lesson 26 [Drill: Sports apparel retailer] — Transcript

by CraftingCases · 5,368 words · 839 segments · language en · Watch on YouTube

Open in transcriber Summarize with AI Download SRT/VTT

Full transcript

0:00Hello everyone, how's it going today?
0:02Before we start this case, I wanted to
0:03remind you that we are building a skill
0:07progression in this module. So,
0:10this case is going to be
0:13slightly tougher case than the previous
0:15one. It's going to have a few more
0:17steps. So, I want you to make sure that
0:20you follow the steps of the first step
0:22approach thoroughly and focus on the
0:25form so that the steps and the
0:26techniques that we learned in the first
0:30video of this module become second
0:32[snorts] nature to you. So, that when
0:34you get an analysis during your
0:36interview, regardless of how tough it
0:38is,
0:39these steps and these techniques will be
0:42natural to you and you will rock the
0:45interviewer's world. All right? Just a
0:48quick recap on what the first step
0:50approach is, what these steps are, and
0:53what techniques I would highly recommend
0:55you use here. The first step approach is
0:57first you structure your case,
1:00preferably with a step-by-step
1:02structure. Then, second, you ask
1:05questions that you might have and data
1:08that you might need. Third, you
1:09calculate the number and fourth, you
1:12come up with insights and next steps for
1:15your client. Okay?
1:17Now, to create the structure, I want to
1:20remind you that I gave you a technique
1:22in the first video, which is
1:24to create a step-by-step structure.
1:26First, you find some number that you
1:29know you can get to and that you
1:32are comfortable getting to and that you
1:34know it is in the way
1:36to take you towards the final answer.
1:38That's all you need to know and that is
1:40what you call step one.
1:42And then, once you have that, you will
1:44see what other number you can get to
1:47that you know is in the way, you know
1:49will get you somewhere closer to the
1:51number you need to get to, but still
1:53isn't it, and that you can get to using
1:56the numbers that you have. And then you
1:57call that step number two. And then you
2:00repeat this until you get all the steps
2:03for your structure. All right? And I'm
2:06going to go through this step-by-step
2:07process with you in this case again. And
2:10last thing before we jump into the case,
2:12you should know that the structure that
2:14I'm going to use in this case is a
2:16fairly common one
2:18for
2:20average difficulty cases, break-even
2:22cases like this one. So, I highly
2:24recommend you take notes on it cuz
2:26you're definitely going to be using it
2:28in your practice time and most likely in
2:31your interviews as well. So, let's get
2:33to the case question.
2:34Your client is a sports apparel retailer
2:37in Europe with 35 stores and around 120
2:41million euros in revenues. They have
2:43satisfactory profitability at the moment
2:46and have hired your firm to help them
2:48develop a growth strategy for the next 4
2:51years in order to reach a 40% revenue
2:55increase.
2:56So, the initial case question was
2:59>> [snorts]
2:59>> how would you help them create this
3:01growth strategy plan? But this is not
3:03the question that we're going to be
3:04working on right now. We're going to be
3:06working on the analysis question, which
3:08is considering we'll get the incremental
3:11revenues only from current stores
3:14reaching maturity and from opening new
3:16stores, how many stores will we need to
3:19open next year to reach a revenue goal
3:22in 4 years? You may use the data in this
3:25exhibit to help you. And then, well, I
3:27got this data over here, this table,
3:30which has
3:31>> [snorts]
3:31>> the data for all of the stores that we
3:33have apparently divided by age with the
3:37number of stores in that specific age,
3:39average size of store,
3:42and average revenue per square meter of
3:44the store. All right? So, let's move on
3:46to the case.
3:47Now, before we do anything,
3:50pause your video, come up with your
3:52structure, and only then listen to the
3:54structure that I have built. And then
3:56I'm going to walk you through my process
3:58of building the structure.
4:01So, here's my answer.
4:02I would solve this case in three steps
4:06to get to the number of stores that we
4:08need to open.
4:09First, I would find the
4:13total
4:14revenues that we are going to need in
4:17order to achieve our revenue goal. So,
4:20that's basically what our revenue
4:22increase goal is minus what our organic
4:27growth is already going to be given that
4:29some of the stores are going to mature,
4:31right? Then, I'm going to find
4:34what are the revenues per new store when
4:38they reach maturity cuz apparently
4:39they're already going to have reached
4:41maturity by the time we are to reach our
4:44goals since we're going to open them
4:45next year.
4:47And then, third, I am going to find how
4:50many stores need to be opened. So, to do
4:53that, I'm basically going to divide the
4:56volume of revenue that we're going to
4:57need to achieve our goal by the revenues
5:02per store at maturity that we're going
5:04to have. Now, would you be fine if I
5:06asked a few questions
5:08>> [snorts]
5:08>> about the case and about the data before
5:11I start calculating to get to the
5:13answer?
5:14And let's say the interviewer says this
5:15is okay. But before you pause the video
5:19and ask the questions yourself, I want
5:22to explain to you exactly how I got to
5:24the structure cuz I think it could be
5:26super useful to you. Here's what I did.
5:29So, I usually tell you to find
5:32a number that you know you can get to
5:34and then make it your step one and then
5:36find another one that you know you can
5:38get to and make it your step two. In
5:40this case, I did the very opposite and
5:43this is precisely why I think it's
5:45interesting to you.
5:46So, first thing I did was I looked at
5:49what I needed to find, which is the
5:50number of stores that we need to open.
5:53Right? To find that, I know that the
5:56objective with opening stores is
5:59getting increase in revenues. And what
6:02supplies this increase in revenues is
6:05opening stores. And so,
6:07I need to get the increase in revenues
6:09that I need and divide it by
6:11the supply of revenues that each store
6:14will give me, right? And so, basically,
6:17I found my last step here, which is
6:19revenue increase necessary divided by
6:22revenues that each new store is going to
6:24bring me. Okay? And so, what I did next
6:27is look into how can I get to those two?
6:30Do I have them? Or do I have data that
6:33will help me? And revenue per store was
6:35quite easy. I saw the data that I had
6:38and it told me square meters per store
6:40and it told me revenues
6:42per square meter in the stores. And so,
6:45if I only knew the size of the stores
6:47that we're going to open and the
6:48revenues per store that we would have
6:50with them,
6:51which I might be able to extrapolate
6:53from these or the interviewer might tell
6:55me, then I can definitely get to the
6:57revenues per store.
6:59And the revenue necessary
7:01to fulfill my goal, I have most of the
7:04data that I need. So, I know the
7:05revenues that we currently have, I know
7:07the goal that we have, and I know that
7:09if I extrapolate
7:11the revenues of each of those stores to
7:14maturity, assuming that it won't change
7:16or if it will change, I can ask this to
7:18the interviewer,
7:19then I know that I can get to the
7:21revenue that we will have organically.
7:24And so, basically,
7:25this is how I created my structure. But
7:27after thinking like this, I structured
7:30it in steps so that I could explain it
7:33simply to my interviewer. Now, if you
7:35want to think out loud, just like I did
7:38with you right now, with the interviewer
7:40and talk through your entire thought
7:42process. That is not a problem at all.
7:45If it makes you more comfortable, do it.
7:46The interviewer is even going to
7:47appreciate it. But, regardless of
7:49whether you choose to think out loud
7:53while talking to your interviewer or to
7:55think quietly and then get into a
7:56structure, you always have to show the
7:59interviewer your step-by-step structure
8:02in the end before you start the case.
8:04That way, you know that you are both on
8:06the same page, which is absolutely
8:08crucial for this step. Now, it's time to
8:12move on to step number two and ask our
8:14questions to the interviewer. So, pause
8:17this video and ask the questions that
8:19you have, then listen to mine and see if
8:21you missed anything. Okay? Let's go.
8:23Question number one.
8:25So, I am going to calculate the
8:29absolute value of our revenue increase
8:32goal. To do that, I'm going to multiply
8:34our current revenues by the
8:37revenue increase goal in percentage,
8:40which is 40%.
8:42And I know that you told me that our
8:44revenues are around 120 million, and I
8:46have data here that
8:49provided we only sell in
8:51brick-and-mortar stores and not in the
8:52internet, will allow me to calculate the
8:55total revenues cuz I have the
8:57number of stores, the [snorts] size of
8:59the stores, and the revenues per square
9:01meter of each store.
9:03Do you want me to calculate the
9:07the
9:08company's revenues to use the market
9:10size number or can I just use the 120
9:13million that you gave me? And let's say
9:15the interviewer tells me that I can use
9:16the 120 million. I don't need to
9:19calculate the full revenues.
9:21Next, I'm going to need to assume a
9:24revenues at maturity for each store
9:27since their revenues are still going to
9:29increase for the ones that are not
9:30mature.
9:31And from the data that you gave me, it
9:33looks like I I assume that
9:37stores that are 3 years
9:39old are already mature and that their
9:41revenues at maturity are
9:433.5 thousand euros per square meter.
9:47Is that right or should I use a
9:49different value for it?
9:51And let's say the interviewer tells me
9:52that those two statements are right.
9:55Now, my third question is regarding the
9:58size of the new stores. Since I'm going
10:00to have to calculate the revenues per
10:02new store at maturity, I don't only need
10:05to know
10:06the revenues at maturity, I also need to
10:08know their size.
10:10And let's say the interviewer tells me
10:12that it's going to be 1.3
10:14thousand square meters per store.
10:17That's the size of the new stores we're
10:18opening. And there just another thing
10:20came to my mind.
10:23Should I assume that there's going to be
10:24some kind of inflation, especially on
10:27the values of revenues per square meter
10:29at maturity? So,
10:31we're talking about 3.5 thousand euros
10:35per square meter right now for mature
10:37stores.
10:39And including for the ones that we are
10:40going to open, but in 4 years, is that
10:43going to be the same? And let's say the
10:45interviewer tells me that yes, that's
10:46going to be the same as well.
10:48Okay. So, now I have everything that I
10:50need, so I'll just start calculating.
10:53So, you who are using this as a practice
10:56drill should pause the video and run
10:59your calculations before watching mine.
11:02First, I want to calculate the
11:05revenue that we need to achieve.
11:07Specifically, I want to calculate the
11:11revenue increase goal in euros, right?
11:13So, that [snorts] is our revenue 120
11:15million times our percentage increase
11:18objective, which is 40%.
11:21So, 40% times 120 million
11:2410% of 120 million is
11:2912 million.
11:30That times four is
11:3248 million. Now, let's move on to
11:35finding the organic growth that we're
11:38already going to have from all the
11:40stores that we've opened growing to
11:42maturity. And so, this is going to be a
11:44little bit trickier. Here's what I'm
11:45going to do.
11:47I'm going to calculate for each tier of
11:49stores, which all have different sizes
11:52and different revenues per square meter,
11:54and of course a different number of
11:55stores,
11:57what is the total area, which is
11:59basically, you know, the number of
12:00stores times the area per store.
12:03And I'm also going to find the
12:07difference in revenues per square meter
12:10from where they are to maturity. So,
12:12basically, if the store has 1,000 euros
12:16per square meter in revenues, and when
12:17they're mature they're going to be at
12:193.5 thousand, then the difference is 2.5
12:22thousand, for example.
12:24And then I'm going to multiply those
12:26two, and I'm going to get to the
12:28total organic revenue increase expected
12:32by the time they reach maturity for all
12:34the stores in that tier. Okay? And so,
12:37the way I'm going to do this is with
12:38these three extra columns that I drew
12:40here. Now, let's move on and run the
12:43calculations. So, for
12:45first tier,
12:48this is 20 * 1.2 thousand square meters.
12:53So, this is 24 thousand square meters.
12:565 * 1.3 thousand. So, this gives me
13:005,000 plus
13:03.3 * 5, this is 1.5.
13:06So, 6.5 thousand square meters. For the
13:10next tier of stores that are 1 year old,
13:14four stores times 1.35
13:18thousand square meters. So, this is
13:221,000 * 4 is 4,000 plus 0.35
13:27* 4. 0.35
13:30* 2 is 7. 7 * 2 is 14.
13:35So, this 0.35
13:37* 4 is
13:391.4. So, I have 4 + 1.4. This is 5.4
13:44thousand square meters.
13:46Now, the last tier of stores that are 0
13:49years old is 6 * 1.3 thousand. Right?
13:53So, 6 * 1 is 6.
13:55.3 * 6 is 1.8. So, this gives me
14:006 + 1.8 7.8 thousand.
14:03Okay? Now, let's move on to the
14:06delta in revenues for each square meter
14:10per tier. So, for tier number one,
14:13stores that are three or more years old,
14:15that's zero, right? Cuz it's
14:17they're are already at maturity. And
14:20since maturity revenues is 3.5 thousand,
14:24for tier number two, 3.5 thousand minus
14:273 thousand is 0.5 thousand.
14:31For stores that are 1 year old, what I
14:33have is 3.5 minus 2, 1.5 thousand. And
14:38for stores that are 0 years old, 3.5
14:41minus 1, this is 2.5 thousand.
14:44Okay? Now, I just got to multiply one
14:46column by the other.
14:48And for the first tier of stores, it's
14:51of course zero cuz they're already
14:53mature, so no organic revenue increase
14:55should be expected. For
14:58stores that are 2 years old, what I have
15:00is 6.5 thousand square meters times
15:03half
15:05thousand euros per square meter. Okay?
15:07So, this is 6.5
15:11thousand times 0.5 thousand. Thousand
15:14times thousand is million, and this is
15:16going to happen in all of this table.
15:18So, 6.5 divided by 2
15:21is 3 plus
15:23half divided by two is 0.25. So, this is
15:253.25.
15:285.4
15:29* 1.5. So, it's 5.4 + 1/2 of 5.4.
15:351/2 of 5.4 is 2.7. So, 5.4 + 2.7 7 + 4
15:41is
15:4311. So, this is 8.1.
15:47Now, 7.8
15:49* 2.5.
15:51This is 7.8
15:53* 5 / 2, right? Cuz 2.5 is 1/2 of 5.
15:597.8 * 5
16:02So, I'm going to call 7.8 8 - 0.2.
16:068 * 5 is 40.
16:080
16:10.2 * 5 is 1. So, this is 39. Now, you
16:14got to divide it by two. 39 / 2 is
16:1819 and 1/2. So, this is 19 and 1/2
16:20million.
16:21So, I just got to add all of these up
16:24cuz this is the increase in
16:28revenues expected just because these
16:30stores are going to mature for each
16:32tier. And so, 0.25 + 0.1 + 0.5 is 0.85.
16:403 + 8 is 11 + 19 30. So, this is 30.85
16:47million. Now, 48 million - 30.85.
16:5248 - 30 is 18.
16:5518 - 0.85
16:58is 17.15.
17:01So, this is the revenue that we need to
17:04achieve by opening new stores. Now, I
17:06just need to figure out how much revenue
17:08each store is going to bring me, and
17:11then I can know how many stores I will
17:14need.
17:15Now, let's move on to calculating the
17:18revenue per new store that we can
17:20expect. So, I have the revenues per
17:21square meter at maturity, which is 3.5
17:25thousand euros
17:27times the size of the new stores, which
17:29is 1.3 thousand. So,
17:343.5 * 1.3
17:374.55
17:40million. Now, I just need to divide
17:43the revenue needed, 17.15
17:46million, by the revenues that each
17:49stores will bring me, which is 4.55.
17:54And it seems like this is going to be
17:57so, 17.15 is close to 18, 4.55 is close
18:01to 4.5.
18:034.5 * 2 is 9, 4.5 * 4 is 18. So, it's
18:08pretty close. This is going to be close
18:11to four.
18:13Just possibly slightly low four because
18:16it's less than 18.
18:18And actually I can't open fraction
18:22stores. [snorts]
18:22I can't open 3.8 stores. So, I actually
18:26have to open four stores. If I open
18:29three, I won't meet my goal. If I open
18:31four, I'll go slightly above, but I'll
18:33have met my goal.
18:34So, the answer is that I should open
18:37four stores.
18:38And what this tells me
18:41So,
18:42this is
18:44just
18:45slightly above 10% of the stores that we
18:48currently have, which is not that
18:50little. It's actually a lot of stores to
18:52open, but it's less stores than we
18:54opened last year. It's less stores than
18:57we opened two years ago
18:59or three years ago. And it doesn't seem
19:02like a lot given the rhythm that we've
19:05been opening stores. And if we open more
19:07stores, and not [snorts] only stores in
19:10this next year, but some stores in the
19:12other years, also.
19:14We're going to be way above this goal.
19:17So, honestly, what I would be looking at
19:19right now is
19:21why is this goal so
19:23achievable?
19:24Couldn't we have been considering
19:27a more ambitious goal?
19:29I would be looking into that.
19:32And I'd be asking this question, why is
19:34this goal so achievable? Why is it so
19:35easy to achieve?
19:37Just doing some math here, I can see
19:39that
19:40if we opened the same number of stores
19:42as the previous year, six,
19:45then we would have at maturity an
19:47increase of nine for every two stores.
19:50So, it's 36.
19:5236
19:54million
19:55while we only need 17.
19:58And so, what this means is around 20
20:00million above our goal.
20:03And so, just by opening the same number
20:05of stores we opened last year. If last
20:07year wasn't a catastrophe in terms of
20:10profitability, then I see no reason why
20:12we wouldn't do that.
20:14All right, this is it for this case,
20:15guys. Now, I want to show you a few
20:19insights that I would love if you
20:21learned from this case.
20:23Insight number one is a new tool that
20:27you have seen I use in this case and
20:29that you can use in your own cuz it's
20:33quite impressive. It's super helpful in
20:35solving the case, in communicating
20:38both your structure and uh your
20:41calculations. And it's also impressive
20:43to the interviewer cuz it shows that you
20:44already think like a consultant. And
20:46that is creating new
20:49data sets in the exhibits that you get.
20:52In this case, I created new columns in
20:54my table, but it could be a another data
20:58set in chart exhibit that you get. So,
21:01you could write numbers on the bottom
21:03with something you calculated, like
21:05under each column, for example. Or you
21:07could create other columns next to the
21:10columns that are there if you're
21:12explaining something like, "Oh, I would
21:14like to see this data." And then you
21:15place something in there. Or I would
21:17expect to see this change, and you draw
21:19a different line or something like that.
21:21Right? And the secret sauce to make this
21:24extra impressive to your interviewer and
21:26make them really see that you think like
21:29a consultant is to label your columns or
21:33data sets appropriately. So, it's one
21:35thing to just, you know, start writing
21:38on a different column, and the
21:39interviewer kind of knows what you're
21:41doing, kind of not. He's not He can't be
21:43sure. And it's another thing to actually
21:47write down the title of the column like
21:49I did, and then write everything on the
21:52bottom, or write exactly what that new
21:55data set is.
21:57That's completely different, and it
21:58makes all the difference because it's
22:00visual. It's not only intellectual, it's
22:03also visual to your interviewer that
22:05they are talking to someone who is
22:07completely ready to be a consultant. And
22:10it also signals to them that you can, at
22:12the same time, think about solving the
22:15problem with an appropriate structure,
22:17but also create it in a way that you can
22:20already communicate it
22:22to someone who is outside of your mind,
22:24possibly even outside of consulting.
22:27Now,
22:28the second insight is about the type of
22:32analysis that this is. So, you might
22:34have noticed that this is a kind of
22:36break-even case, but only conceptually.
22:38What this means,
22:40a break-even calculation is basically
22:43figuring out how many units you need to
22:46sell to compensate an investment that
22:49you made. So, on the top you will put
22:51investment and fixed costs as the
22:54numerator, and on the bottom as the
22:56denominator you will put the
22:58contribution margin of the specific
23:00product that you have. Right? That is
23:02the correct definition of a break-even
23:05analysis. But, the conceptual definition
23:08that I use is different. It's basically
23:11I think of
23:13the units sold on the denominator as
23:18a unit that supplies their contribution
23:21margin in order to offset the
23:23investment, which we can call a goal of
23:27cash flow being zero. Right? And in this
23:30case, the stores are what supply the
23:33revenue, which are created to offset a
23:36goal in revenue growth. And that's why
23:39we have the necessary revenue growth as
23:42the numerator and the uh revenues per
23:46store, because stores supply revenue in
23:49this case, on the bottom as the
23:51denominator. Okay? And
23:53since we've now agreed that this is a
23:56break-even case, what you can pay
23:58attention to is that break-even cases,
24:01including this one, are often made
24:03difficult by adding extra steps. And
24:06these steps can be added in three
24:08different parts of the structure.
24:10They can be added as extra steps to find
24:12the numerator, or in this case the
24:14revenue goal, and this is where this
24:16case was tougher, cuz you had to do a
24:18ton of calculations to find how much
24:20extra revenue you needed to find. They
24:22can be extra steps to find the
24:23denominator, in this case revenues per
24:26store. So, imagine that we didn't have
24:28the number for revenues per store, we
24:30needed to do a bunch of calculations to
24:32get it. In this case, we did have to
24:34break it down a little bit.
24:36And it can also be extra steps after
24:38finding the break-even value. Meaning,
24:41once you find the number, you still have
24:44to calculate something afterwards. For
24:46example, in this case, it would be if
24:48they had asked me
24:50what percent growth of stores
24:53we would need, rather than the number of
24:55stores that we need to open. Or if they
24:57asked us, "What will be the necessary
24:59investment?" And then after I find the
25:01number of stores, I need to calculate
25:03the investment based on the investment
25:05per store to open. Okay?
25:08Now,
25:08this is something that you should keep
25:10in mind because it's going to appear a
25:11lot. And once you see a case that is
25:13conceptually a break even, you can
25:15already know
25:17what are the general steps that you're
25:19going to need to take. There is the
25:20actual division of the break even, and
25:22then there are the steps to get to the
25:24numerator, steps to get to the
25:25denominator, and steps to do after the
25:29break even sometimes.
25:31Now,
25:32another thing that I want to point out,
25:34and this is something that I did in this
25:36case that you definitely should
25:38incorporate to your skill set, and that
25:41is in the end, when finding the so what,
25:44the insights, and then the next steps,
25:47instead of comparing the number that you
25:49got to only one number, compare it to
25:52more than one number. In this case, I
25:53compared the number of stores opened
25:56that we're going to need to open to the
25:59number of previous stores opened, so the
26:01stores that we opened in the last year,
26:03the year before, and the year before
26:04that.
26:05And I also compared it to the number of
26:07stores we already had. So, I said it's
26:10a little bit more than 10% of stores
26:12that we have, but it's also less stores
26:15than we opened last year. And if you
26:17make more than one comparison, if you
26:19compare with more than one number,
26:20you're going to get to more nuanced and
26:22stronger insights, and it's going to be
26:25noticeable to the interviewer because
26:26everyone else is going to be comparing
26:29the number to either nothing or to just
26:33one single number and giving a
26:36one-dimensional conclusion to your
26:38interviewer. Of course, you should only
26:40do this if you can find more than one
26:43relevant comparisons. You shouldn't be
26:44comparing it to something that has no
26:46relevance to the case. Okay? But while
26:49you're practicing, it pays off to take
26:51some time to find several numbers that
26:54you can compare your final answer to to
26:57get to an insight.
26:59Now, one more thing that I want to bring
27:00up is a common mistake that many people
27:05would do in this case, and I've seen
27:07many people do it. And that is making
27:10assumptions that are sort of reasonable,
27:13but not making them explicit. So, in
27:16this case, the one I want to take as an
27:17example is
27:19assuming that 3.5 thousand euros per
27:22square meter in revenues per store at
27:24maturity is the number that we can use
27:28as, you know, revenues per square meter
27:31for stores that are mature.
27:33The reason I'm saying this is
27:37it looks a lot like this is the number
27:40we can use for mature stores from the
27:42table that we got from the data that we
27:44got, and it's kind of implied in the
27:46case question, but it could very well
27:50not be. It could be that the
27:52interviewers would say no. Since these
27:54stores are larger, we might expect less
27:57revenues per square meter. Or since
27:59these stores will be opened in less
28:01premium locations, or maybe we can
28:03expect more revenues per square meter
28:05because we're going to open them in
28:07better locations or whatever.
28:09But it could be different. You don't
28:11even need to ask, but you need to make
28:13this assumption explicit. Or if you're
28:16more comfortable with this, you can ask.
28:18Asking is definitely better than keeping
28:19quiet. But when you ask this or when you
28:22make this explicit, it shows to the
28:24interviewer that you're aware of the
28:26possible nuances around it. So,
28:28it shows them that if you were doing a
28:32real-life consulting project, you're at
28:35the client, and then
28:37there is this possible assumption that
28:39you can make.
28:40Kind of like this one. Revenues per
28:42square meter at maturity will be the
28:44same for new stores.
28:46That could be a curveball, and I am
28:48certain that your interviewer has gotten
28:50several of those curveballs in their
28:53time in consulting. And when they see
28:55that you will catch that if it comes to
28:57you, they want you to be the person
29:00working on the client side in the next
29:03project for him. Because you are the
29:05person that's going to catch those
29:07problems by yourself, and they're not
29:09going to need to fact-check and recheck
29:13everything that you do when you're
29:15implied assumptions, which is much
29:17harder to check than an explicit
29:19assumption. Okay? So,
29:22when making a sort of reasonable
29:24assumption,
29:25either ask whether that assumption is
29:27reasonable or
29:29tell your interviewer that you're making
29:30an assumption over there. But, asking is
29:33a little bit better. Okay? Now, one last
29:35thing that I want to talk about because
29:37yeah, you guys always ask me about
29:40alternative structures for the analysis
29:42cases that we do. And one alternative
29:45structure that is possible and just as
29:48good as this one, I guess,
29:50is within step one,
29:52instead of finding the goal in absolute
29:55value in revenue increase and
29:57subtracting it from the
30:00organic growth that is expected
30:03from the stores that we already have,
30:05you could have gotten the revenues that
30:07we will have, which is not uh 48
30:10million, but 168 million, cuz it's 140%
30:15of our current revenues, minus the total
30:18revenues of
30:19the stores that we have once they are
30:21mature.
30:22And what we're seeing with this
30:24alternative structure is the same
30:26pattern that we saw in the
30:30last drill that we did, which is a
30:33dichotomy between finding the difference
30:35of the totals and finding the total of
30:37the differences. Right? What I did here
30:40when calculating the organic growth
30:42expected instead of calculating the
30:45total revenues at maturity of the
30:48current stores that we have is finding
30:50the
30:51total of differences. The differences
30:53being the difference for each store tier
30:56between
30:58revenues per square meter right now and
31:00revenues per square meter in the future
31:03and multiplying that by the number of
31:05square meters that we have. Finding the
31:08difference of totals would be total
31:10revenues once these stores are mature
31:14minus total revenues right now.
31:17Okay, and that would be the organic
31:19growth that we can expect. And if you
31:20were to do that, of course, you wouldn't
31:22use the exact same structure within step
31:24one. What you would do would be
31:27finding first the revenues that we need
31:30to have once we reach our goal.
31:32So, 140%
31:34of 120 million. And then subtract from
31:37that
31:38the revenues that we will have once all
31:42of our stores are mature if nothing else
31:44changes. And this structure would also
31:47work. Now, there is an alternative
31:50structure that would not work. Kind of
31:52looks like it would work conceptually,
31:54but then when you get into the weeds, it
31:56doesn't. And that is finding This is for
31:58the whole case, not only for one step,
32:00but that is
32:01finding the total revenues that we need,
32:04140% of our current revenues,
32:07and dividing that by the revenues per
32:10store at maturity, and that would give
32:12us the number of stores total that we
32:14need to have. And then we can just
32:15subtract the number of stores that we
32:17already have.
32:19This seems like it would work, but the
32:20problem is the stores we have
32:25they all have different sizes from one
32:26another. So, the
32:2820 stores that are at 20 plus year old
32:30on average have 1.2 thousand square
32:33meters per store. The ones we're opening
32:35have 1.3
32:37thousand square meters per store. So, if
32:40you divided this by the average size of
32:42stores that we have now, you wouldn't be
32:44finding the right number of stores that
32:46we need to have cuz some of them we're
32:48going to open are going to be larger and
32:50therefore have more revenues per store.
32:54So, it doesn't really work. What you
32:56could have done
32:58it seems like a stretch to me, but what
32:59you could have done
33:01is finding
33:03the total revenue needed divided by the
33:06revenues per square meter
33:08at maturity.
33:10And then, once you have that, you can
33:13subtract from that the number of square
33:15meters that we already have, and then
33:17you'd find the number of square meters
33:19that we still need to open in stores.
33:21And then you divide that by the number
33:23of square meters per store that we are
33:25going to open. That might work. That
33:28would work. And it would be it would be
33:30a clever way to structure this case, not
33:33necessarily better than this one,
33:35probably a little bit harder to explain,
33:37but no problem if you did it that way.
33:39All right, guys. This is it for today.
33:41I'll see you in the next video.

About this transcript

This page contains the full transcript of Case Interview Fundamentals: Lesson 26 [Drill: Sports apparel retailer] by CraftingCases, generated from the public captions YouTube serves with the video. The transcript has 5,368 words across 839 segments, with the original timestamps preserved so you can click any line to jump to that moment in the embedded player.

What you can do with it

Use the transcript to take notes, quote the speaker, build a study guide, generate a summary with ChatGPT or Claude via the YouTube Summary tool, or export it as a timed subtitle file with YouTube to SRT. You can also re-open it in the transcriber to choose a caption track available on the video.

Free YouTube transcript tool

YouTube2Text is a free YouTube transcript generator — no signup, no daily limit. Paste any YouTube link and get the full transcript instantly, with timestamps, click-to-jump, caption language selection, AI prompts for ChatGPT, Claude, and Gemini, and exports to TXT, SRT, VTT, or Markdown.