Big Data Analysis: This Could Be a Business Saver

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Big data refers to data that can be used to extract value and understand trends.

In 2008, McKinsey reported that an average US company with around 1,000 employees stores around 200 terabytes of data. In 2010, Eric Schmidt, executive chairman of Google,mentioned in a conference that the amount of data being created every two days was equal to data created from beginning of human civilization to the year 2003.

Today, ‘big data’ is not just a buzzword; it is a reality and businesses are increasingly dependent on it. In fact, businesses that do not adopt big data run the risk of being obsolete. Research also shows that six million developers are involved in big data analytics currently. Moreover, IDC predicts that worldwide revenue from big data analytics will reach $203 billion by 2020.

Big Data

Companies are leveraging the power of big data to analyse trends, make predictions and hence serve their customers in a better way. 85% of companies are trying to capitalize on data. However, only 37% of them have been successful. 2017 big data survey shows that big data initiatives are usually taken to reduce costs, develop new products and explore new opportunities.

Here are how businesses can harness the power of big data analytics to gain a competitive edge:

1. Improve Customer Experience

Technology allows companies to gather a huge amount of data about their customers’ lives such as where they live, what they prefer, what their online behaviors are etc. When mined, this unrelated data gives some invaluable insights that allow companies to predict exactly what their customers want. The ‘recommendation’ feature that you see on Spotify and Netflix is there because of big data.

Through big data, companies can also identify the pain points of their consumers and act accordingly. Big data helped Delta Airlines pinpoint that lost baggage was their customers’ major concern. Delta Airlines came up with a ‘Track my bag’ feature that allowed customers to monitor their luggage throughout the journey.

The best thing about big data is that it allows companies to collect and respond to customer data in real time. For instance, when a customer calls with a complaint, the company should be able to make informed decisions based on the customer’s buying history.

Gartner research shows that when firms are equipped with the contextual knowledge, the time needed to address customer concerns reduces significantly. This not only increases customer satisfaction, but reduces costs by 25%.

2. Reduce Costs

Big data analytics allows companies to cut down their costs significantly. The example of Intel is quite relevant here. Intel has been using data analytics to reduce its chips’ market time. The company has been able to streamline information with its testing procedure successfully.

According to Ron Kasabian of Intel, now they run tests on specific chips instead of running them on all of 19,000 chips. This allowed the company to save $3 million in manufacturing costs.

The oil and gas industry are also benefitting from big data analytics. Rising production costs, fluctuating prices and squeezing margins are increasing the industry’s reliance on big data.

According to research, unplanned downtime costs the industry $49 million annually. However, McKinsey proposes that effective use of big data can reduce capital expenditures by 20% and cut upstream operating costs by 3-5%.

Healthcare industry is yet another beneficiary of big data. Lab results, data from devices, reports and financial data is growing exponentially. When all of this information is captured and consolidated it gives a complete picture, which improves care coordination.

Predictive analysis turned out to be a savior for Centers for Medicare and Medicaid Services as it prevented frauds worth more than $210.7 million in one year.

3. New Product Development

GE’s 2014 Innovation Barometer shows that 60% of executives say they cannot come up with disruptive innovations.

An increase in competition has made it difficult for companies to introduce products that can grab significant market share.

In fact, a study by Booz & Co. shows that 66% of the products fail within 2 years. Another research by Deloitte shows that 96% of the products do not give any return on investment. Big data proves to be quite useful in this regard by indicating potential disruptions.

Also, predictive analysis allows innovators to create products that are relevant for the future. In short, big data tools allow innovators to be proactive rather than reactive.

Signals Analytics has developed an app based on big data analytics to promote innovation. The team has worked for years to bring data in one place in real time. The app brings together knowledge about customers, which is then combined with Signal’s data science capabilities to help with new product development.

The market is full of big data analytics tools that can be used to generate valuable insights. Hadoop has become synonymous with big data. It is an open-source software framework that has the ability to store large amounts of data.

MongoDB is yet another tool that can handle semi-structured or unstructured data. It is used to store data in apps, and content management systems. Tableau is an easy-to-use tool that allows you to create intelligent reports with graphs and bar charts without requiring any special programming skills.Unlock Insights is yet another tool that allows you to structure data and gain valuable insights for tangible results.

Data is being created every second at an exponential rate. However, data that is unrelated and does not make any sense is of no use. The idea behind big data analytics is to convert this data into invaluable insights and knowledge that allows companies to act in an intelligent manner.

Big data allows companies to see what customers want today and in the future.

It has helped companies adapt to changing customer demand. Customer analytics are changing the game for e-commerce websites. Not just that, it has made businesses more efficient by reducing operating costs. It would take a while before big data becomes an everyday term. However, the sooner companies adopt it, the better.

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