In recent years, the term Big Data has become the talk of the town, or should we say, the planet. By definition, big data analytics is the complex process of analyzing huge chunks of data, trying to uncover hidden information — common patterns, unusual relationships, market trends, and above all, client preferences. All these are taken into careful consideration and big decisions are made based on the calculations, with high hopes of success.
When described as such, it seems that an average entrepreneur would simply jump at the opportunity to use big data for their startup, yet that is not as common as one may expect. Why is it so?
We’re going to offer several possible explanations for why startup owners are not keen on investing in Big Data .
Obsolete and Infinite Mindset
According to Dr. Tom Davenport, a renowned academic researcher, entrepreneurs are not analytical by nature. Hence, they can oversee the importance of data analytics. Dr. Davenport argues that most startup leaders rely on the good old gut feeling when it comes to making decisions. In addition, he claims that the change of mind regarding Big Data most probably occurred due to the successful examples of companies using analytics to their advantage, such as Amazon, Netflix, Facebook, or Google. Another reason would be that a startup’s niche is such that analytics has become inevitable for any company working with it.
Therefore, the shy attitude of some startup owners towards data analytics is explained as something that is in their character. However, while it is true that there is quite a number of entrepreneurs that are used to the “old ways”, we’d say that nowadays a self-aware, modern entrepreneur with an infinite mindset will think of Big Data advantages at the very moment when they’re founding the startup, or even before.
On the other hand, if a startup leader is studying any of the leadership traits for the 21st century, then they are well aware of the Big Data downsides too. An entrepreneur may avoid it because they are very well informed.
Overwhelming for the Inexperienced
Another reason why a startup company may be missing out on valuable information on their clients’ behavior lies in the fact that not each startup company has skilled staff.
A startup, as the name says, is a company at the beginning of its exciting journey. Thus, there is a number of positions in the company that are yet to be filled out by professionals. Data analytics, if anything, is overwhelming to research and analysts. It is often too unstructured.
Of course, there is always the option of hiring a professional to do detailed analytics. However, that requires extra funds. Open source technology relies heavily on staffing, maintenance, hardware, and so on. Going over budget is quite common for data analytics, so the companies providing data are pressured into charging more for the services as well.
Doing it on your own also comes down to big costs. First, there’s the software tool you’ll be using. Then, all that data needs to be properly stored, which is another expense. The workforce managing this also costs money.
Big Data has two sides. It provides insight into someone else’s data, but it may leave one exposed too. Startups are especially vulnerable unless they have established a strict policy and training on cybersecurity from the very beginning. Otherwise, their own data may be manipulated.
Even worse, should the client’s privacy be invaded, that would automatically harm the company’s reputation, potentially leading to fines and lawsuits. A data breach can have grave consequences for the startup.
Time Management Issues
Moreover, it takes some time to discover customer and market trends regarding a particular company, so it does not provide quick results that can be used immediately. For a startup, fast progress is extremely important. Why risk it then that the data collecting lasts longer than the startup itself?
Next, technology is changing at an extremely rapid pace. One may invest in certain software that will become obsolete in a couple of months. That means a startup would have to wait longer for the results, but also that the final results could be totally wrong, or incomplete.
The Bottom Line
Startups are a specific type of company that has to be risk-taking and careful at the same time. Big Data services are very appealing and popular for a reason. They help overtake the competition and earn higher revenues. Nevertheless, it may be a wise decision not to invest too much into data analytics until a startup gains some firm grounds.