How would you approach a consulting case on London students rental market dynamics?

Great question! And it’s much deeper than it looks at first glance.

Most candidates make the same mistake here: they jump straight into spraying out “buckets” like market, competition, customer, financials.
This feels structured. But in reality, it is not a logic. It’s just a list. And lists don’t solve cases.

A partner at McKinsey or BCG doesn’t care whether you can recite buckets.
They care whether you can cut through a messy problem with a clean, deterministic logic that guarantees you’ll reach the right answer.

I’ll show you how to do exactly that.

1. First: Recognize the Case Type

Your example prompt is:

“A real estate firm wants to expand its student accommodation portfolio in London. Should they enter, and if so, how?”

This is a classic Type A: Strategic Go/No-Go problem.

The pure, distilled client question is:

“Should we invest more into London’s student rental market?”

Everything else flows from this.

2. Define the Criterion to Answer the Question

For ANY Type A case, we first ask:

On what basis can we say ‘yes’ or ‘no’?

Assuming the client’s objective is maximizing profit (if not, clarify!), the answer is:

The firm should expand IF doing so creates enough additional profit to justify the investment, AND the firm can execute (capabilities) AND manage risks.

This leads to the three conditions:

1. Financial sense (most important)
2. Capabilities
3. Risks

But do not treat these as buckets.
Treat them as necessary conditions in a logic chain.

If Condition 1 fails → we stop.
If Condition 1 passes → we test 2 and 3.

This is real consulting thinking.

3. Build the Logic That Tests Condition 1 (Financial Sense)

To know if the expansion “makes financial sense,” we must verify:

Will additional yearly profit from London student housing > investment cost over the investment horizon?

This is the heart of the case. Your analysis must prove or disprove this inequality.

So we break “additional yearly profit” into a driver tree:

Additional yearly profit = Additional revenue – Additional operating costs

And additional revenue depends on:

• # of units filled
• Price per unit
• Occupancy rate
• Length of stay
• Possible ancillary revenue (laundry, services, etc.)

Operating cost depends on:

• Maintenance
• Utilities
• Staffing
• Financing costs
• Repairs
• Management fees

But - and this is where strong thinkers differ - 
these drivers are only relevant insofar as they influence profit, and cannot appear randomly.

4. Translate the Market-Understanding Into the Profit Drivers (This Is Where Most People Fail)

Most candidates throw “market analysis” into a separate bucket.
That’s not rigorous.

Every qualitative element must connect into the math.

Here’s how to do it properly:

A. Demand side → affects “# units filled,” “occupancy rate,” and “pricing ability.”

You would examine:

• Growth of student population in London (domestic & international)
• University expansion plans
• Postgraduate vs undergraduate mix
• Visa policy trends (international students are price-inelastic but volatile)
• Housing stipend availability
• Demand seasonality

Every point ties directly to future volume or price, the two revenue sub-drivers.

B. Supply side → affects expected occupancy and achievable rent.

• Existing PBSA (Purpose-Built Student Accommodation) capacity
• Planned developments (pipeline analysis)
• Competing private landlords (Airbnb, HMOs, build-to-rent)
• Regulation in boroughs (HMO licensing, development restrictions)

Again, this isn’t a “market bucket.”
These factors influence occupancy, price, or cost.
That’s why we analyze them.

C. Price and affordability → affects revenue per unit.

• Current price points for studios, ensuites, shared flats
• Price segmentation by zone (Zone 1 vs 2 vs 3)
• Student willingness to pay
  (international > postgraduate > domestic undergraduate)
• Inflationary environment and parental income trends

Again, everything connects to the profit drivers.

D. Operating model & cost structure → affects operating cost

• Staffing & on-site management
• Maintenance (high for PBSA)
• Utilities and energy efficiency standards
• Security requirements
• Cleaning and common-area maintenance
• Financing cost (interest rate environment matters massively)

All linked to cost per unit.

E. Investment cost (CapEx)

• Land acquisition or property purchase
• Construction or refurbishment cost
• Planning permissions and timelines
• Fit-out cost

This directly impacts the left side of the inequality:
Investment cost vs. expected profit over time.

5. Test Condition 2: Capabilities

Once financial sense is established, you test:

• Does the client know how to operate student housing?
• Do they have local partnerships in London boroughs?
• Do they understand regulations (HMO licensing, planning rules)?
• Do they have construction/refurbishment experience?
• Do they have talent for PBSA management?

Capabilities don’t help you decide what to analyze.
They are simply a risk of failure even if the business case is attractive.

6. Test Condition 3: Risks

Key risks include:

• Regulatory shifts (visa restrictions, landlord regulation)
• Overbuilding (especially in Zones 2–4)
• High interest rates pushing up financing costs
• Concentration in certain universities (e.g., UCL vs QMUL)
• Exchange-rate risk (international students pay in foreign currency)

You outline risks only after financial sense is validated, not before.

7. How You Would Present This Structure in an Interview

Here is how a top-tier candidate would actually verbalize it:

“Our client’s core question boils down to:
Should we expand our student accommodation portfolio in London?”

“I believe the answer is yes if and only if three conditions are met:”

1. “The expansion makes financial sense - meaning the additional yearly profit clearly exceeds the required investment over the investment horizon.”
2. “We have the capabilities to build and operate student accommodation in London.”
3. “And we can shoulder the risks associated with this market.”

“Given profit maximization is the primary objective, I would prioritize the financial sense condition.”

“To verify this, we need to quantify additional profit: this means estimating occupancy, achievable rent, operating cost, and comparing the resulting yearly profit to the investment cost.”

“To estimate revenue, I will assess the drivers of volume and price, including student demand trends, university growth, international student inflow, supply of PBSA, and competitive intensity. Each of these factors ties directly to expected occupancy and price points.”

“On the cost side, I will analyze operational cost per bed and required CapEx, which will depend on building type, location, planning requirements, and financing conditions.”

“Only if the resulting profit meaningfully exceeds the investment cost would I proceed to test capabilities and risks.”

Why This Approach Impresses Interviewers (And Real Partners)

Because:

• You start with the type of question
• You craft a logical decision criterion, not buckets
• Your structure guarantees an answer
• Every market factor explicitly maps into numerical drivers
• You sound like a consultant, not like someone who memorized Case in Point

This is how strong candidates separate themselves from the 95% who rely on generic frameworks.

Hope this helps!
Sidi

___________________

Dr. Sidi S. Koné

Honestly, you'll get the most out of this Q&A if you provide a suggested answer and then we can give you feedback on it. 

High level, what you should emphasize is tailoring. Meaning, think about the specific of student accommodation and what that entails, what are the specific customer needs associated with that, and even more so, the specifics of it being in London. This should inform your structure. 

Best,
Cristian

You always need to understand first how do they make money. That will be the case of your framework. Also critical to understand whether they just buy and sell property vs. build out from scratch.

Imagining it's the second, they will have a certain income (rent + property value increase) and cost (building + operating + financial costs).

Framework should consider what these are and their drivers. Drivers of the income part are, as you mention, supply and demand of real state.

hey there :)

For a London student rental case, start with a clear structure: first assess market attractiveness, student population trends, demand vs. current supply, pricing, and occupancy rates. Then evaluate the client side, what’s their cost structure, construction or acquisition costs, and target return. Don’t forget competition analysis and regulatory aspects like planning permissions or rent caps. Finally, run a simple profitability or ROI check and consider risks like changing student numbers, Brexit effects, or alternative housing options. Always quantify where possible and be ready to compare scenarios.

best, Alessa :)