Hello!

Precisely for the high amount of questions (1) asked by my coachees and students and (2) present in this Q&A, I created the “Math & Formulas - Economic and Financial concepts for MBB interviews”, recently published in PrepLounge’s shop (https://www.preplounge.com/en/shop/prep-guide/economic_and_financial_concepts_for_mbb_interviews).

After +5 years of candidate coaching and university teaching, and after having seen hundreds of cases, I realized that the economic-related knowledge needed to master case interviews is not much, and not complex. However, you need to know where to focus! Hence, I created the guide that I wish I could have had, summarizing the most important economic and financial concepts needed to solve consulting cases, combining key concepts theorical reviews and a hands-on methodology with examples and ad-hoc practice cases.

It focuses on 4 core topics, divided in chapters (each of them ranked in scale of importance, to help you maximize your time in short preparations):

• Economic concepts: Profitability equation, Break even, Valuation methods (economic, market and asset), Payback period, NPV and IRR, + 3 practice cases to put it all together in a practical way. 
• Financial concepts: Balance sheet, Income statement/P&L and Performance ratios (based on sales and based on investment), +1 practice case
• Market structure & pricing: Market types, Perfect competition markets (demand and supply), Willingness to pay, Pricing approaches, Market segmentation and Price elasticity of demand, +1 practice case
• Marketing and Customer Acquisition: Sales funnel, Key marketing metrics (CAC and CLV) and Churn, +1 practice case

Feel free to PM me for disccount codes for the guide, and I hope it helps you rock your interviews! 

This is the solution offered by McKinsey. (The link for the whole case is http://www.mckinsey.com/careers/interviewing/globapharm)

Investment would need to increase the probability of success in Phase II from 40 to 80 percent (that is, increase of 40 percentage points). There are multiple ways to approach this calculation. One method is shown here:

• If a candidate drug passes Phase II, then it has a 50% x 90% = 45% chance of being successfully marketed and sold. Since a successful candidate drug is worth $1.2 billion, a candidate drug that passes Phase II is worth 45% x $1.2 billion = $540 million.
• To break even (that is, to make the $150 million investment worthwhile), the value of the candidate drug that passes Phase II would need to increase to $540 million + $150 million = $690 million. This means, the probability of combined success in Phase I and II would need to increase by (150/540) = 28 percentage points.
• So the current probability of Phase I and II, that is, 70% x 40% = 28% would have to increase by 28 percentage points, to 56%. In order to come up to 56%, Phase II probability would have to increase from 40% to 80% (70% x 80% = 56%).
• This seems like a very big challenge, as an increase by 40 percentage points means that the current probability of 40% needs to double.

Hi,

the case seems like a relatively straightforward case of expected returns.

You know that the outlay of R&D cost $150m is real money. Therefore that money has the same value, as the payoff you get from drugs that make it through all phases (because that is also real without any discount for expectation)

You need to go backwards from the expected payoffs, and estimate the value of all drugs in trial in the various phases (of which you know some are not going to make it.)

In Market: 1.2b
In Phase 4: 1.2b / 90% = 1.33b
In Phase 3: 1.33b/50% = 2.66b
In Phase 2: 2.66b/40% = 6.66b
In Phase 1: 6.66b/70%= 9.5b

Now, the value of the drugs in the first phase does not change. However, we need to break even, meaning we need to make back the $150 investment in our 'in Market' phase. Therefore, the new value for In Market is: 1.35b.

Applying the same backwards logic results in:

In Market: 1.35b
In Phase 4: 1.35b/90%= 1.5b
In Phase 3: 1.5b/50%= 3b
In Phase 2: 3b/40% = 7.5b
In Phase 1: 7.5b/70% = 10.7b

As I mentioned above, the value of 10.7b is irelevant, as this would imply that we give more drugs into the development funnel. However, the question is to broaden the funnel, i.e. how do we get with the potential market of 9.5b (if all drugs tested became a success through all phases) to 1.35b (what we need to recoup investment). We are given the fact that the improvement happens in Phase 2, so we solve for the formula:

9.5b*x = 7.5b, x=0.79

Therefore, the answer shold be that the success rate in phase 2 would need to increase from 40% to 79%, an increase of almost 100%, to recoup the $150m investment.

On a sidenote, maybe worth mentioning that the drugs that make it through all phases have an NPV of 1.2b. That means it can take quite a long time to recoup the money (at 5% interest rate, it is about 20 years worth of returns, of around 60m each year. It depends whether the company has the same risk appetite for return on their investment cost, i.e. is the NPV value of the last stage a valid measure of the return. I assume it is in this case scenario, but in real life it may differ).

Cheers,

The sucess rate of Phase II need to be 0.800 to break even the extra investment. Here is my thinking process using the concept of expected value (EV).

The concept of EV can be used to calculate the net expected earning of a particular gambling game, given the investment (INV), profit, and the success rate (SR):

• EV= -INV + SR x Profit

,where SR=SR1 x SR2 x SR3 x SR4 accounts for the four phases in this case. Straightfowrdly, one would have no change in the expected value (dEV=0) if,

• dINV=dSR x Profit

,where "d" denotes the change "delta". Here we know the profit is 1.200B and the change of investment is dINV=$0.150B, which gives dSR=0.125. With the unchanged sucess rate in phase I, III, IV, the change of sucess rate in phase II dSR2 need to be:

• dSR2= dSR / (SR1 x SR3 x SR4) = 0.125 / (0.700 x 0.500 x 0.900) = 0.400

to offset the extra investment. Therefore, the sucess rate of Phase II need to be 0.800=SR2+dSR2=0.400+0.400.

(edited)

The logic behind is a decision tree where on first stage you have probablity to move further of 70% an get 0 (or lose investment) of 30%. Then again 40% to move and 60% to have 0 -> 50% to move 50% to have 0 -> 90% to win $1200 and 10% to have 0. THen if you put $150 as investmetn you start to have -150 instead of 0 on each end. By multiplying % on win/lose of the branch and sum up results you go backward from 1200 to the beginning: 1200*0,9+(-150)*0,1=1065 -> 1065*0,5+(-150)*0,5=457,5 -> 457,5*0,4+(-150)*0,06 and so on...

Hope it's clear enough..

(edited)

Looks like there should be some information on initial R&D invetments for the product. Because if you assume all initial investments as 0, it's alreade profitable to try.