Chevron Corporation, a global energy company, realised that each drilling miss can cost the company upward of $100 million. But the seismic surveys it uses to evaluate potential drilling sites ? each up to 50 terabytes of data ? take an enormous amount of time and computing power to analyse. Chevron?s geologists always knew they wanted to do more, but were restrained by one of the biggest challenges organisations face in using analytics: a lack of bandwidth to focus on analytics. In the summer of 2010, the US federal government temporarily suspended all deep water drilling permits in the Gulf of Mexico, regulation that essentially shut down all oil exploration in the region for nine months. Rather than sit idle, geologists at Chevron seized the opportunity. Using recent advances in computing power and data storage capabilities, as well as refinements to their already advanced computer models, geologists were able to improve the odds of drilling a successful well at certain of its deep water prospects to nearly one in three, up from odds of one in five or worse. The intensive review led the company to change the next year?s drilling schedule to explore several higher probability wells first.
The above example perfectly illustrates the advances made in computing technology and how this combined with analysing the available data can come out with sophisticated predictable models and can make all the difference between success and failure for any business enterprise. This is further amplified in an increasingly interconnected world where enterprises have to take decisions much faster than before and analytics plays an important role in governing such actions.
International Business Machines (IBM), the global technology giant, has been in the forefront in espousing the need for integrating the philosophy of analytics and the use of advanced computing power in any business enterprise to get decisive edge. According to Asif Mohammad, executive director (Business Analytics and Optimisation), IBM Global Business Services, ISA, ?Over the last five years, we?ve spent some $16 billion buying analytics companies. And now, IBM has almost 9,000 business analytics and optimization consultants, and eight global analytics solution centers in Berlin, Beijing, Dallas, London, New York, Tokyo, Washington and Zurich.?
Analytics is not merely a technology tool which is used to crunch huge amount of data but its ability lies in using this information to come out with models which make an actual business impact. ?Senior executives now want businesses run on data-driven decisions. They want scenarios and simulations that provide immediate guidance on the best actions to take when disruptions occur ? from entry of unexpected competitors to an earthquake in a supply zone to a customer signaling it may switch providers. Executives want to understand optimal solutions based on complex business parameters or new information, and they want to take action quickly,? says a joint study done by IBM Institute for Business Value along with MIT Sloan Management Review.
However, this would not mean that analytics as a tool can be just implemented within an enterprise without having a strategy in place. ? For analytics driven insights to be consumed ?that is, to trigger new actions across the organization ? they must be closely linked to business strategy, easy for end users to understand, and embedded into organisational processes to take action at the right time. That?s no small task. It requires painstaking focus on the way insights are infused into everything from manufacturing and new product development to credit approvals and call center interactions,? says the study.
It is also seen that data or technology has not been the biggest obstacle while using analytics but barriers which are largely related to management and culture. The biggest roadblock obstacle to widespread analytics adoption is lack of understanding of how to use analytics to improve the business, lack of management bandwidth due to competing priorities.
Given this background, it is no surprise that larger number of Indian enterprises which are increasingly globalising their operations are using analytics to gain that edge in a hyper competitive marketplace. Mohammad says, ?We are seeing tremendous response for our analytics solutions across verticals. The key question that we hear from clients these days is ?how do we extract the business value of analytics and apply it to the enterprise?? It is a clear indication that analytics is being increasingly used and adopted by companies for decision making.?
The early adopters in the application of analytics is in industries that are focused on end-customers like BFSI, telecom and retail. For example, through IBM?s analytics solutions Airtel, India?s leading mobile services operator was able to increase the ability to process 2.5-3 million new customers a month. Further, the team was able to conduct deep segmentation and apply analytics to develop a customer lifecycle management system and activate new mobile accounts 90 percent faster than before.
Similarly, working with a leading public sector bank, IBM increased the bank?s visibility into non-performing assets, significantly reducing the ratio of NPAs to the bank?s total loan assets. The solution provided 100% increase in automated reporting for about 248 reports daily, while reducing labour costs through the complete elimination of manual processing. It also enabled the bank to create targeted marketing campaigns, with automated e-mail capability once correct target audience is defined.
? From our client engagements, we notice that clients are increasingly aware that the ability to use the available information is either their greatest opportunity or one of their greatest threats. Clients understand that analytics can give them the initial informed intuition to be the primary coping mechanism. And, in order to differentiate and grow, they view the deployment of business analytics as a mandate and imperative, not an initiative,? says Mohammad.
