Big Data: Your Company Is Small – So What?!


Big Data Is Not For Big Players Only 

Let’s imagine a hypothetical scenario where the main actor is a small company that gives out loans via a website. The first thing that can help drive profit up is low operation cost, and overall process optimization. So, naturally, the company wants to reduce the number of redundant tasks, and invest in channels that will bring them new clients, and keep the existing client base enthralled and satisfied. 

But, the more you think about it, the more questions arise. Should you invest in Big Data now? Do you need to hire specialists and experts to help you get there? How will this investment scale up in the long run? Having doubts is one thing, and it’s natural, but staying behind because of them is crippling, and potentially fatal to your business. 

Do you think Uber and Venmo would be where they are now if they hesitated to jump on board and embrace the tech side of business?

Now, let’s be real for a moment – the workers of the future will be different from the workers of today. No, we are not talking about fashion and aesthetics. We are talking about different educational backgrounds. 

The workforce of all economic sectors is already starting to fuse with IT and statistics, and experts suggest that this is happening thanks to Big Data expansion and popularization. 

Your Company Is Small – So What?!

One of the most common mistakes when approaching this complex subject is thinking that the big players are the only ones that can afford this transformation. This could not be further from the truth. Since IT companies and startups are the ones changing the rules – tools and platforms became available to everyone. 

Not so long ago, huge loads of client data took a quartal (or sometimes even longer) to analyze. This required a dedicated team or a large department devoted to going through every piece of paper, every transaction and every bit of info, all in hopes of making a valuable prediction for the upcoming period. Due to the scope of projects like these, companies used to make unnecessary gambles by putting their resources into analytics. 

Bankers worldwide want to have live analytics of their users’ behavior, because, let’s be real – waiting is a liability in today’s market’s dynamics. To put things in perspective, in 2016, a sum of just under $21 billion was invested in Big Data development and utilization solely by the banking sector globally (IDC, 2016). Nowadays, Fintech companies develop solutions that do this (and more) in a matter of days, bearing low operational costs, with no need for hiring new IT staff. All this quickly results in a powerful impact on your business.  

You do not have to be big to progress – that is the main point of the digital era: ideas and innovation win, not size, and definitely not a traditional business approach. The most beautiful part of Big Data is its accessibility. You do not need to pay extra for a team of analysts in order to get a clear picture of your client base. The main focus is on shifting to digital solutions that allow talent redistribution and overall fresh value development.

What Can You Do?

It is important to tackle this issue from both sides – reducing operational costs and securing a safer execution of tomorrow’s plans. Through a stable platform, you can weaponize Big Data to do both. The biggest asset that is both successful and scalable, no matter the size of your operation, is client behavior prediction. After you establish the base, you slowly develop other benefits of implementing quality IT solutions and Big Data combined. Some of the most impactful effects are:  

  • Unlocking and realizing the full potential of data-driven marketing 
  • Creating custom offers for your clients based on their habits 
  • Significantly increasing the effectiveness of risk assessment and management 

Fintech, and IT in general, is already turning the tides of the financial sector, especially when it comes to Small and Medium Enterprises. 

The only question is – What are you waiting for?


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