Indian oil and gas industry embraces predictive analytics

Bigger the industry, larger will be the quantity of data, higher will be the requirement of processing data and greater will be the necessity for an advanced solution to deal with it at a faster rate. Being one of the core industries, oil and gas (O&G) industry has a significant impact on all the other sectors of the economy.

The amount of data generated by O&G companies is starting to explode and the speed of making it almost impossible to interpret. With rising market demand, the O&G industry faces several other challenges, such as rising costs of extraction, difficulties of exploration, economic downturn, fluctuating prices, untamed competition, and turbulent state of international politics.

Due to these big problems, significant players of O&G industry are turning to predictive analytics and big data hoping to find solutions to these demanding issues.

80% of Indian oil and gas industry CIOs believe that increase in their analytical and big data capabilities would optimize their businesses.

Several reports reveal that around 80 percent of Indian O&G industry CIOs believe that increase in their analytical and big data capabilities would optimize their businesses. CIOs believe that there is a growing urgency for O&G companies to embrace predictive analytics and big data to drive positive business outcomes through actionable insights.

Alok Khanna, DGM IS at Indian Oil Corporation believes that the use of big data analytics in businesses becomes an academic exercise if it is not data-driven, and has a monetary impact.

“The O&G industry is going towards a customer-centric approach and therefore it’s required to have advanced analytical tools to understand patterns and customer behaviors. We, at Indian Oil, have started taking gradual steps towards the same and slowly extending it to relevant business lines,” he said.

He further added, “We use predictive analytics for our business process and it is surely increasing efficiency in areas like stock data and financial data analysis, graphical reports and data visualization. This is aimed at analyzing and making sense of bulk-structured and unstructured data in our systems.”

Predictive analytics and big data are helping O&G companies to analyze huge volumes of data at a reduced cost and quicker than ever. They are also using big data analytics to monitor equipment, identify patterns, and enable proactive maintenance. This helps in understanding operations and risks and opens up new opportunities.

According to Mahendra Kumar Chaudhary, Executive director and CIO at ONGC, the patterns and insights gathered through analytics can help businesses in making influential decisions, reduce losses, and increase oil production.

“Analytics is penetrating all the possible sectors of the country including O&G industry, and we believe that there is a bright future lying ahead,” said Chaudhary. “To deal with the competitiveness in the market we use predictive analytics especially for optimizing oil and gas production and monitoring conditions.”

O&G companies that understand the importance of leveraging big data technologies will be the most streamlined and successful of all their peers, agreed analysts. In fact, analysts believe that big data analytics is a key investment priority for both large and small O&G companies.

The penetration of big data analytics isn’t severe, but in future its usage will be mainstream.

Bhavish Sood, Research Director, Gartner, believes that the O&G industry is hardly resistant to adopting newer technologies. As this is a data-driven industry and is involved in production and operation, analytics would definitely make a significant impact on this sector.

He said, “Forecasting, analyzing, energy trading, buying, selling, trading off, and managing risks are the few specific areas where O&G companies should start deploying their predictive analytics. However, Indian O&G companies have already started deploying analytics for cost-effectiveness, remote monitoring, and maintaining pipeline networks.”

Creating an advanced analytical capability takes time and investment, and it can only happen with a sustained focus on the business. “The penetration of analytics isn’t severe, but in future its usage will be mainstream. This year and next, businesses will likely turn increasingly to digitization, analytics, and robotics to lower above-the-ground costs,” concluded Sood.