With the ever-changing technology, big data initiatives have grown in popularity owing to its compelling traits, which help clients’ to uncover valuable information about customers and other business insights.  It has proved to be an amicable solution, reaching every nook and cranny at the rampant pace. Over the past few decades, Big Data has moved beyond the hype and proved out to be a true source of major competitive advantage. In this light, a study conducted by a leading research firm illustrates that around 60% of organizations are planning to invest an average of $8 million on Big Data initiatives.

However, in today’s data-driven world, building a prolific ROI equation is not easy for data center and cloud hosting service providers in India. It needs fortitude analysis of facts and technology so as to reach the success brink. 

In this blog, we will figure out each of the reasons that affect ROI and represents how they can be mitigated to maximize the chance of achieving high ROI.      

Where is the ROI in Big Data? 

As the technology has rolled down with promising benefits, companies have started acquiring the Big Data solutions to gain positive ROI. According to the mega research conducted by TeraData, titled as “Betting on Big Data”, which involved 316 senior data and chief IT decision-makers at companies that scored average revenue of $500 million, have revealed that about two-third of companies have encountered solid results from their investments, however, in contrast, about one-third companies are still seeking a return. As per the research, in several companies, businesses are drawing huge revenues, so why some companies are are lacking in gaining the advantage from Big Data initiatives.   

As per Teradata Survey, Big Data Analytic’s impact on revenues can be seen through this graph: 

[Source: Datanami.com]

Some of the obstacles that restrict companies in seeking the tremendous benefits of Big Data Technology are: 

- Immaturity of tools        
- Shortage of skilled personal 
- Least focus on technology 
- Lack of expertise in extracting data from multiple data silos 
- Unorganized business case for Big Data  

As data volume is growing exponentially at an alarming velocity of petabytes of structured and unstructured data streams, many business leaders and chief technocrats who have anticipated enhanced outcome with Big Data Technology solutions are figuring out what potential lies herein. The driver of most technology investments is of course ROI; else, there is no point of investing your capital if you don’t get the return. 

To turn your business into a big success story, derive value from the high volume, variety and velocity of Big Data. Here are three key principles that companies must focus upon in order to derive profit motif:

Extensibility: The procedure of formulating analytic models from existing unstructured data silos should be extensible so that they can efficiently address problems spanning across different verticals. This, in turn, eliminates the need of repeating the same action i.e. design->extract->model->train process for every business solution.  

Flexibility: To address the accelerating market dynamics, a solution is needed that can quickly adapt without remolding or redesigning the solution pattern. In addition, new data sources and models are required that can be further incorporated with respect to the changing conditions.   
  
Cost Effectiveness: Every company makes substantial investment in an enterprise data warehouse or data infrastructure. However, incremental investment approach based on advanced analytics can give business leaders a pause if it doesn’t recognize any augmenting ROI path. In essence, the real fact is building on top of cost-effective and often open source solutions.  

How do you fundamentally outline ROI back to the initiative?

Depending on the size of a company, if you can save up to single digits in your operational efficiency or you are able to derive revenue without producing new products or channels – this indicates that you are on the track of making profit. Calculating the ROI and the value derived from Big Data investments is a priority task for most of the leading chief level executives. 

Let’s focus on the key characteristics that help companies to derive valuable ROI: 

- Firstly, organizations of all sizes need to concentrate on business value of their IT investments. Unquestionably, ‘Big Data Sandbox’ (which enables a company to understand its actual investment value in Big Data) has the capability to take the ground, but to seek management attention and generate value; you need to produce trustworthy results. So, picking up the right business problem is imperative. 

- Get top management support in managing Big Data initiatives. It requires a data-driven culture, that’s why it needs effective push from the top management level. 

- Next thing is manage your Big Data initiatives like portfolio. Start with smaller yet achievable projects as it ensures success. Consequently, acquiring COTS (Commercial-off-the-shelf) analytics platform can bring momentum. Besides, experienced and skilled data integrators/ consultant can boost up the process.
 
- The most critical thing is managing data as a corporate asset. Data silos are continuously creating obstacle in the path of Big Data analytics initiative.  Though you may never reach to an equilibrium state, yet at least discover ways to augment data integrity. 

- A right combination of technical ability, business insights and intellectual zeal is important if you want to fast track the ROI.  Acquiring and nurturing the right talent is the key to interpret the data, which in turn augment your ROI.  

So, what is there for Big Data in 2016?  

Over last few years, companies have matured significantly the way they manage volume of data. By incorporating right technology, talented consultants, data scientists, technology experts and tools, they can exponentially drive and engage in the execution of Big Data initiatives and thus generate enhanced business throughput. 

Moreover, it is believed that companies that lead the evolution in the digital disruption will be those that consider data maintenance and management as their top priority.