I have known Tata since I was a child. I rode Tata buses to school, soaped myself with Tata soaps, stayed in Tata hotels and probably lived in houses supported by Tata steel. More recently both my brother and my wife worked for a Tata company. But the Tata I knew then was different than today's Tata. The global, competitive, aggressive, and ambitious Tata.
India's Tata group has become very well known in Europe recently after taking over UK's Corus and Ford's Land Rover and Jaguar businesses. It is also in talks to buy T-Systems from Deutsche Telekom in Germany. If you add to all this the excitement of the €1800 Nano car designed by Tata, you have got a credible Asian multi-national company in the world's eyes.
Many question the business sense of taking over Landrover and Jaguar given that the premium attached to these brands has a minuscule market in India, where a Hyundai Sonata is considered a luxury salon car! Others question the ability of the Tatas to control unionized European operations.
But I am bullish about their recent acquisitions and their ability to turn these into strategic wins. The foremost reason for my belief is the relative professionalism in the way Tatas conduct their business. For example, top Tata managers of the holding company, Tata Sons, are selected and groomed through the Tata Administrative Service (TAS), admission to which is based on a merit-based, competitive and through screening process. So we can be certain that folks running the acquisition show from the Tata side will be competent and highly trained.
The second reason for my bullish assessment is the value of the technology transfer from Jaguar and Landrover to Tata. About 8 years ago Tata motors rode a huge success in the "Tata SUMO", a rugged diesel-powered 4x4 that looked like a SUV but cost a lot less. The SUMO was an instant hit because it rode well on India's broken roads and because the government of India subsidizes diesel, it was highly cost effective. I still remember seeing caravans of hired SUMOs on highways during weekends and vacations.
Then Toyota came and stole the show with the Toyota "Qualis". This gem had more to offer: Toyota quality, quieter engine, superior interiors, and better fuel efficiency. Although the Qualis was priced slightly higher than the SUMO, it quickly overtook the latter. Tata had lost out because Toyota had superior technology. Lesson learn t for Tata: India had stepped out of its socialist past and now quality and technology mattered to Indian customers.
Jaguar and Landrover will fill this important gap for Tata. Another example where Tata can benefit from better technology is Tata's subcompact "Indica". I have ridden this car and can confidently state that it is noisier and bumpier than its Suzuki counterpart on Indian roads. Jaguar and Landrover technology will perfectly compliment Tata technology. A company that produces some of the cheapest steel in the world (because Tata owns iron and coal mines in India) combined with an established brand and distribution network in India will be unbeatable with the infusion of the latest technical know how from the acquisitions.
Saturday, April 19, 2008
Sunday, April 6, 2008
Beyond desktop search...can we make user-PC data more valuable?
I ordered an 8GB flash disk last week (turns out there is a 16GB one around, but I am modest ;-) ). Since I don't have a whole lot of media content to put on this fat-stick, I will instead end up putting all my work over the past few years on it. If I factor in the emails, I should easily fill up 8GB with a couple of years' worth of data. Wow. I remember having a hard time filling a DSDD 5.25 inch 576 kB diskette back in the early 90s.
The low down is that we have *lots* of data. 7MP pictures, podcasts, email archives, documents and web-downloads, not to mention audio/visual media - all this can quickly add up. Fortunately storage has kept up, or perhaps the pace of storage encourages more data generation in the first place? Whatever the truth, we have a situation where we have a whole lot of data sitting in our computers.
There have been many instances of large volumes of data in non-PC computer scenarios. For example, real databases have routinely run into terabytes. The key difference between user-PC data and these databases is the heterogeneity and the lack of structure in the former. User-PC data comes in various formats and is generated by completely different applications. Even when the same application generates the data (e.g. an email mailbox file) the goal has never been to store the data in a way extract global information later.
Desktop search software is the first step in mining information from User-PC data. But search is really a very preliminary tool because it only flags the existence of the information sought via the specified key-words. There is very little cognizance of the bigger picture. Data mining - that power tool which works so beautifully for databases and other highly structured data - does not exist yet for User-PC data.
Isn't it time we started building algorithms beyond just search to help users extract useful information from their gigabytes of data?
The low down is that we have *lots* of data. 7MP pictures, podcasts, email archives, documents and web-downloads, not to mention audio/visual media - all this can quickly add up. Fortunately storage has kept up, or perhaps the pace of storage encourages more data generation in the first place? Whatever the truth, we have a situation where we have a whole lot of data sitting in our computers.
There have been many instances of large volumes of data in non-PC computer scenarios. For example, real databases have routinely run into terabytes. The key difference between user-PC data and these databases is the heterogeneity and the lack of structure in the former. User-PC data comes in various formats and is generated by completely different applications. Even when the same application generates the data (e.g. an email mailbox file) the goal has never been to store the data in a way extract global information later.
Desktop search software is the first step in mining information from User-PC data. But search is really a very preliminary tool because it only flags the existence of the information sought via the specified key-words. There is very little cognizance of the bigger picture. Data mining - that power tool which works so beautifully for databases and other highly structured data - does not exist yet for User-PC data.
Isn't it time we started building algorithms beyond just search to help users extract useful information from their gigabytes of data?
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