The price of light is less than the cost of darkness.
-Arthur C. Nielsen, Market Researcher & Founder of ACNielsen
In today’s world, data is the most approved form of administrator for businesses. The organizations are taking various steps to improve the ways of data collection as well as analysis of the data collected.
Big Data involves having more data than one can handle with the computing power available commonly.The definition of Big Data therefore continues to evolve with time and advances in technology. Big Data will always remain a paradigm shift in the making.
Why so much Hype Now?
Data usage in business for decision making has been a prolonged activity. Analytical data has been used in businesses since the mid 1950’s. But it is only now that it has become a buzzword. Why?
- Data Creation: Earlier the data sources were small and not very well structured as today. Perhaps Google CEO Erik Schmidt said it best: “Every two days now we create as much information as we did from the dawn of civilization up until 2003. That’s something like five exabytes of data.”It is that massive amount of exponentially growing data that defines the future of Big Data.
- Data Management: Data had to be manually stored in company’s warehouses . But now the data can be easily stored in databases. In the past, big data was a big business tool. Not only were the big businesses the ones with the huge amounts of information, but they were also the ones who had sufficient capital to get big data up and running in the first place. Cloud computing changed all of that. It turned out to be the perfect solution for many companies. It doesn’t require any on-premise infrastructure, which greatly reduces the startup costs. Big data in the cloud has been one of the key components in its quick ascent in the business and technology world.
- Cultural Shift: The biggest challenge for acceptance of data analytics in businesses was of making the evolution from a knowing culture to a learning culture—from a culture that largely depends on heuristics in decision making to a culture that is much more objective and data driven and embraces the power of data and technology.This has mostly changed only because of power of fear of being left out (a.k.a FOMO) in the new competitive word. This has led oneself to think and act differently today and to ask questions. So it’s this mind-set change from an expert-based mind-set to one that is much more dynamic and much more learning oriented, as opposed to a fixed mind-set, that has been a major stimulus.
And today we have now come to a stage, when all biggest companies are talking about it.
“Across the three years of our comprehensive study of big data analytics, we see a significant increase in uptake in usage and a large drop of those with no plans to adopt,” according to Dresner Advisory Services. This is likely an indication of an ever increasing shift in equilibrium between supply and demand for big data technologies. Not just tech companies but retails, financial institutions, manufacturing industries and many others are being affected in some way or the other.
How Biggies Are Using Data Analytics?
The American Express Company is using big data to analyse and predict consumer behaviour.By looking at historical transactions and incorporating more than 100 variables, the company employs sophisticated predictive models in place of traditional business intelligence-based hindsight reporting. This allows a more accurate forecast of potential churn and customer loyalty. In fact, they are able to predict 24% of accounts that will close within four months.
Domino’s has been investing in multiple technologies in an attempt to improve its business. In autonomous delivery, the company has been testing delivery robots in Europe. In AI, Domino’s has invested in a virtual assistant that’s integrated in its mobile application, which aims to expedite and simplify the ordering process. Domino’s has also utilized AI to better route deliveries in real-time by tracking its drivers through GPS, which also happened to reduce driving incidents by 50%.
Caterpillar, a 93-year-old stalwart of heavy earth moving equipments, began integrating artificial intelligence into its business a few years ago. One key use case for AI in Caterpillar’s business is in preventative maintenance of its equipment, which can reduce downtime and cost of operation. Additionally, Caterpillar invested in Airware, a drone-tech startup that helps companies plan flights and analyze images gathered for insights, as well as other frontier tech startups.
Customer experience was the starting point for AT&T. That’s what matters most. They took up the problem to simplify workflow for customers care solutions. So how do they simplify the process for both the customer-care agent and the customer at the same time, whenever there’s an interaction?
They used big data techniques to analyze all the different permutations to augment that experience to more quickly resolve or enhance a particular situation. And it worked! They turned complete process into something simple and actionable.
So What’s Next? The Future.
According to a study by NewVantage Partners, more than 80% of them say their Big Data investments have been successful, and almost half say their organizations can measure the benefits from their projects. Only 1.6% of respondents deemed their Big Data initiatives failures, which is an impressively low number.
Why are these executives so positive about Big Data?
They report a variety of positive outcomes, including cost reduction, establishment of a data-driven culture, and various benefits related to innovation, new products and services.
Companies that started with early-stage centers and a small team of analytics specialists tackling business cases in bespoke fashion, today, rotate business leaders into a new type of analytics center, where they learn the basics about new tools and how to apply them. This will accelerate adoption—particularly as analytics tools become ever more frontline friendly—and create the big impact that big data has promised.
Sahil Bansal is the co-founder at Correst.io. Correst is an India-focussed data platform that aggregates an array of heterogeneous sources to build a cohesive view of the business landscape. It uses proprietary algorithms that run atop a large business directory to mine for high-quality analytics.
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