$10 Billion IPO, Facebook

Facebook announced today about its intention to float $10 Billion IPO. Only 10 times there has been an IPO of more than $10 billion. The biggest IPO by an Internet based company was from Google, that was less than $2 billion. So how is Facebook so different from others? Its revenue almost doubled from last year and in current fiscal year its projected revenue is $4 Billion.

There are two moot question about Facebook IPO

1) Is $100 billion valuation correct?

2) What Facebook plans to do with $10 Billion?

IPO generally is backed by a need of financing some project or need of expansion. It is unclear why Facebook needs so much of money.

About valuation, its difficult to imagine a $100 billion internet company, whose core competency is to help people connect. Yes it has more than 500 million users who log-in daily. But does that makes it so much valuable. Its earnings has been very small until recent years. Even if we use very optimistic approach and say Facebook advertisement revenue will keep growing at average 15% and lets assume that its cost of capital is around 20%, then also its valuation only comes to $80 billion.( used perpetual growth model). $100 Billion is just a relative valuation done based on investment into Facebook.

To me Facebook looks overvalued and it don't need money. IPO is just way for its investors to make money.

Comments

Process Reengineering and Optimization Tools – Part 1

Processes are ever evolving. They keep changing to suit business and their goals. As an analyst weneed to keep finding ways to improve it, make it more relevant and optimal. Business process management only talks about lifecycle of a process, it doesn’t gives us tools to optimize. There are very few tools that help an analyst to think in a structural fashion. One such tool is “Lean”. Lean essentially talks about reducing waste and in turn make a process more efficient and optimal. Lean is specifically very relevant for process optimization as it talks about flow of process. Although it was first applied in manufacturing, but we as an analyst can take a lot of clues from it, to optimize process in any sector. Toyota, which was pioneer in Lean manufacturing, talks about three kinds of wastes. Muri – Related to design of process, it talks about what we can proactively avoid while designing the process. Mura – Related to implementation of process and elimination of fluctuatio...

How Kirana stores can handle Organize Retail in India

Organize retail formats include departmental stores, hypermarkets, supermarkets and specialty stores. Any store having more than 500 sq. feet is counted in organized retail. There are more than 14 million retail shops in India, organized retail accounts for only 4-5% [i] , but it is growing at 40% per annum. Organized retail in India will grow faster as regulations loosen up. Government will sooner or later give in to demand of better FDI regulations, in favor of big corporate houses. Time is not far away when Kirana stores will walk the path of obsolescence. So how can these small stores save themselves? SWOT Analysis Kirana Stores Organized Retail Stores Strength Well connected to community, Customized service, Near to customer Bargaining Power, Allows customer to choose, Volume Sales, Financial strength, Bigger display area, Trendy Weakness Outdated, relatively costlier, Less display area, Higher cost per SKU ...

Predictive Model (Using Trend Analysis, Univariate Analysis and Binomial Logistic Regression)

Predictive models have been in use since advent of various statistical tools. Both marketing and financial institution uses it extensively. This article tries to look under the hood how a predictive model is created. I will try explaining it using simplest available statistical tool like Trend analysis , Univariate Analysis and slightly complex tool called Binomial Logistic Regression . Lets assume company want to know how much attrition will happen in current quarter, so that it can start hiring process. First step of model is find out what are the factors that can lead to attrition of an employee. To find these factors we simple take past data and holistic list of factors. Age, Income, Martial Status, Education Background, Work Rating, Number of leaves, Number of days came later than usual timing, Number of year in company, Business Unit, Business vertical, Past Work experience Indicative list of factors for Company Attrition Model On each list...

Exception Handling!!!

Search This Blog