February 2000. Pets.com, a company which sold pet supplies online, made its Initial Public Offering on the US stock market. Shares began trading at $11 but reached a high of $14. Pets.com were on a roll. In the New Year they won numerous advertising awards for their website, and were ranked number one by USA Today’s AD Meter for their first national commercial. However, just 9 months later pets.com hit rock bottom. In November 2000 they had a share price of $0.19 and were liquidated.
The story of pets.com was part of a wider period popularly termed the dot com bubble, when the phrase “get large or get lost” was a mantra of the times. Many dot com companies like pets.com were able to raise large amounts of money through IPOs without ever having made a profit, or in some cases even earned any revenue at all! In the case of pets.com, despite its success in building brand recognition, there was little to suggest it represented a good investment. For a start, before launching the venture there was no research into whether there was a viable market. There was certainly no workable business plan; the company lost money on almost all its sales because it was selling at a rate lower than the cost of purchasing the products. Added to this was its extravagant advertising bill. During its first fiscal year in 1999 pets.com revenue was $619,000 and yet it spent $11.8 million on advertising. However, in the excitement of the promised returns from technology investors looked past traditional business metrics such as P/E ratio as indicators of performance rushing into investments. When the bubble burst many companies failed completely or lost a large proportion of their market capitalisation leaving investors seriously out of pocket, and wondering what the fuss had been all about.
And yet one gets the feeling that the same thing is happening all over again. The hype over data and the possible riches it is said to bring can be seen everywhere. Companies are launching head first into data solutions to win the race to harness the power of data. However, by rushing into processes, companies are at risk of losing out in the long run. Here are three reasons why.
Companies do not know what they want from their data
Companies are tumbling over themselves in the pursuit of data, but just putting a data system in place can gain little if it is not aligned with the organisation needs and wants. Data on its own is useless, especially if you collect the wrong data.
Companies are making shortsighted investments in data systems
A product of the first problem, because companies are rushing to get data rather than taking the time at the start to think about the overall process, they are ironically taking longer and more expensive routes to get to the benefits data systems can bring. For example, many companies are going down the data warehouse route costing them time and money (see our blog: “An alternative to the data warehouse approach to HR analytics”) They are missing the easy wins, and the value add which can be gained quickly from a focused approach towards data.
Companies think they can solve all their problems in one go
There is not necessarily one golden path to getting value from data. Companies are placing their faith in one system to provide the ultimate solution. However, different needs and thus different data may need specific systems and processes.
The risk is that companies will rush into investments without fully understanding the as is situation, and what is feasibly possible. Like the dot com bubble companies may find themselves down the line with little to show for their investment. However, this is not to say that there aren’t huge wins to be got from data. As Fred Wilson, a venture capitalist at the time of the dot.com bubble said, “A friend of mine has a great line. He says ‘nothing important has ever been built without irrational exuberance”. The mania around data is spurring companies to come up with new, improved systems and processes for maximising the gains to be got from data. After all, although much of the capital invested in the dot.com bubble was lost, a lot of it went into further underlying development of the Internet such as databases and server structure. (Andrew Smith, Totally Wired; On the trail of the Great Dotcom swindle, 2012).
The point therefore is to step back. Rise above the hype and focus on your needs and wants, not what the market demands. Ask the questions: What do we want from our data? How do we focus? What type of data are we dealing with? How does this relate to our overall strategy? By taking the time to answer these questions you can ensure you get the right data system for the right job and that you are maximising the value your data has to offer.
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