Challenges in Pricing a House

*Long Read*

Overview:

Housing prices all over the world are subject to a lot of interest. At their best, they can be a strong leading indicator of the economy and at their worst, they can cause bubbles that cripple the entire financial system. In India, Housing prices have been much maligned for increasing the cost of living, especially in Tier 1 cities. There is a lot of bargain involved and the prices are murky at best, with hidden challenges as well. This article tries to summarize the problems and gives an understanding as to why pricing a House is extremely challenging (with a few comparisons with FMCG/FMCD sector)

Basis: 

Real Estate comes under the 'alternate investments' category. Other alternate investments include atypical investments like Wines, Arts, etc. 

A thread that binds this class of investments every SKU is different. A Van Gough painting is different from a Picasso painting. Also, all Van Gough paintings are different. Houses follow the same logic. No two houses are the same. Below is a broad categorization of factors which cause these differences:

Project: 

a) Location

b) Master Plan

c) Designing Elements

d) Construction Technology

e) Delivery Timelines

Product:

a) Floor

b) View

c) Vastu

d) Tower/Wing

e) Specifications

(Note: For the sake of simplification, I am ignoring some key factors like Brand, Geography, Product Mix, etc.) 

This classification is trying to differentiate two similar different products, A 1200 sqft 2BHK in project X in location Y on the Ground Floor of Tower Z will be very different from the 2BHK at the 10th Floor of the same project and tower.

This makes Housing units nonfungible, which should logically help us derive the conclusion that the pricing for these two SKUs should be different. This is the premise of this article. However, several challenges prevent this from happening. We will try to study them in some detail.

Challenges:

I) Inefficient Market:

Indian Housing Market is extremely inefficient. Unlike a stock market, where participants have good to great information on the product they are wanting to invest in, Housing Market is a shy away. Some of the key issues are:

a) No MRP Concept:

If you have ever bought a house, you must have haggled for the price. But if you wanted to buy a car, you will not negotiate. If you want to buy a biscuit pack, it doesn't matter whether you buy it from a mall or a Kirana store. So why negotiate on the price of the house? Because everyone knows that there is a difference in the quoting price and selling price for houses. Even the prices offered for the same unit by different distribution channels can vary. 

Housing Market behaves more like a Sabzi Mandi rather than having a professional approach. Considering the high ticket size investment (a house is going to be the biggest financial decision in most people's lives), this approach is extremely deterrent for the consumers. It creates challenges for builders in benchmarking as well. 

b) Different cost structures of Land:

Land cost is one of the major cost drivers in a RE project. It depends largely on the location, but two lands in the vicinity can attract very different prices based on the type of deal (outright, JV, DM, etc.). In fact, it can be said that housing prices follow the story of land prices. Every land needs to be negotiated for and the Land Market is even more inefficient than Housing Market.

II) Pricing Strategies for underwriting:

In an efficient market, the majority of the companies will earn 'standard profits', which are mostly derived from a 'Cost Plus' approach to pricing. Any alpha returns will be earned either by Cost Leadership or Market Leadership approach. These are moats that companies develop over a while (excluding the cases where patented breakthrough technology is itself the moat).

But most of the underwriting is done by a mix of 'Cost Plus' and 'Market Pricing' approach. Cost Plus method helps in closing transactions. It gives the required hurdle rate for the project. As we saw in the last section that the cost structures can vary due to the deal type, 'Cost Plus' approach ends up giving different prices for similar projects.

'Market Pricing' approach benchmarks competitors. Again, as we saw in the last section that since there is no MRP concept, getting accurate information about competing projects can be a challenge. There is always a +/- 5% deviation from the pricing derived through this method.

Both the methods have their flaws, and when combined to derive a project pricing, the flaws are multiplied.

III) No Pilots

I have tasted weird flavors of coke that have never hit the market. Product testing is a critical aspect before going full-on with a product. It gives valuable customer insights on price, quality, acceptance, etc.

But there is not much scope for testing a Housing Project. By the time anything is visible to the customer, the design of the project has been frozen and approvals have been obtained. No builder will go back to the design table after the launch. 

The pre-launch period is used by most builders for price discovery. But this is not a price discover but more of a +/- 1/2 % correction since the project is already underwritten (and no one wants to accept a bad underwriting)

IV) SKU Pricing

Assuming that the builder has managed to decode the correct project price, the greatest challenge comes in pricing individual houses. Remember, each house is an SKU. The reasons for this have been highlighted in the Overview section. 

Incorrect SKU pricing leads to a lopsided demand and preference. Some units will sell and some units just don't move. But by the time this is realized, preferred SKUs are already sold and there is not much one can do to change the prices of the unpreferred units apart from taking a hit on the margins.

V) Unclear Tipping Points

Understanding the elasticity of demand in a project to its pricing is a brave man's game. Housing distribution channels are slow to absorb new prices and elasticity can't be measured since all units are different. A broad level elasticity measurement might also take 1-2 months of testing. And since inventory is limited, experimentation is not favored as the derived logic can't be reapplied.

Ending Notes:

The idea of writing this post came to me when I was talking to my friend who was evaluating a purchase decision. Once I started explaining to him the process of selecting a house, he dropped the idea after he understood how excruciating this process is going to be. The buying experience should be the smoothest and Housing Market is not exactly customer friendly. And I haven't even mentioned the waiting period for the product delivery.