Companies adopting Big Data analytics to deal with challenges

Spending on Big Data hardware, software and services is expected to grow to around $34 billion in 2020 from $4 billion in 2011. But is building an advanced analytics capability really worth the investment?

By Bhanu Singh, Travis Pearson and Prashanth Aluru

The Economic Times

Companies adopting Big Data analytics to deal with challenges

By Bhanu Singh, Travis Pearson and Prashanth Aluru

First published on noviembre 20, 2013
min read


This article originally appeared in The Economic Times Samsung uses it to power the content recommendation engine on its smart TVs. US-based Progressive Insurance relies on it to capture driving behaviour and determine customer risk profiles. Bharti Airtel depends on it to help create more than 5,000 targeted campaigns a day to increase monetization. It, of course, is Big Data: the mining and processing of petabytes of information to gain insights into customer behaviour, supply chain efficiency and other areas of business performance. Industry analysts and media observers say Big Data is the next big thing, and some companies are rushing to climb on board. Spending on Big Data hardware, software and services is expected to grow to around $34 billion in 2020 from $4 billion in 2011. Indian IT and BPO services players are bolstering their capabilities in Big Data: take, for example, Wipro's $30-million minority stake in Opera Solutions this year. But is building an advanced analytics capability really worth the investment? Early adopters of Big Data analytics have gained a significant lead over the rest of the corporate world. Examining over 400 large companies globally, we found that those with the most advanced analytics capabilities are outperforming competitors by wide margins. The leaders are twice as likely to be in the top quartile of financial performance within their industries; five times as likely to make decisions faster than market peers; three times as likely to execute decisions as intended and twice as likely to use data very frequently when making decisions. To get in the Big Data game, a company needs three kinds of table stakes: large quantities of information in a format allowing for easy access and analysis; advanced analytical tools, such as Hadoop and NoSQL; and people capable of putting those tools to work. But many companies have not yet laid the groundwork. But having these table stakes alone won't help you win, because Big Data isn't just another technology initiative. Let's look at what's involved. Leading companies begin the embedding process by spelling out their ambition — for instance, incorporating advanced analytics and insights as key elements of all critical decisions. They also answer the question: how is Big Data going to help us? There are four areas where analytics can be relevant: improving existing products and services, improving internal processes, building new product or service offerings, and transforming business models. For example, Humana, the US health insurance provider, uses claims data to determine who is likely to end up in a hospital for preventable reasons and then intervene early. With ambition defined, Big Data leaders work on developing a horizontal analytics capability. They learn how to overcome internal resistance, and to create the will and skill to use data throughout the organisation. It's a big job. Leading companies typically define clear owners and sponsors for analytics initiatives. They provide incentives for analytics-driven behaviour, ensuring data is incorporated into processes for making key decisions. They create targets for operational or financial improvements, and work to trace the causal impact of Big Data on the achievement of these targets. Big Data leaders then create an organisational home for their advanced analytics capability. Companies with deep analytics skills and an emphasis on experimentation and innovation, such as Google and Progressive, can rely on a generally decentralised approach. Many others have found that a centre of excellence (CoE) offers the most advantages and the fewest limitations. A well-functioning CoE enables cross-business-unit access and data-sharing. At the corporate level, the CoE serves as the go-to organisation for analytics strategy and insight support. It sets the road map, and establishes and maintains privacy policies. How to get started in Big Data? A good first step is to benchmark your industry and determine your company's position in analytics compared with that of your chief rivals. This will help you determine the investment necessary to improve your relative position. If you are significantly behind the competition, you will have the kind of burning platform often required to create and sustain change. The writer is a senior partner at Bain & Company. The article was co-authored with Travis Pearson, a Bain partner, and Prashanth Aluru, a senior principal at the firm.

This article originally appeared in The Economic Times

Samsung uses it to power the content recommendation engine on its smart TVs. US-based Progressive Insurance relies on it to capture driving behaviour and determine customer risk profiles. Bharti Airtel depends on it to help create more than 5,000 targeted campaigns a day to increase monetization.

It, of course, is Big Data: the mining and processing of petabytes of information to gain insights into customer behaviour, supply chain efficiency and other areas of business performance. Industry analysts and media observers say Big Data is the next big thing, and some companies are rushing to climb on board. Spending on Big Data hardware, software and services is expected to grow to around $34 billion in 2020 from $4 billion in 2011. Indian IT and BPO services players are bolstering their capabilities in Big Data: take, for example, Wipro's $30-million minority stake in Opera Solutions this year. But is building an advanced analytics capability really worth the investment? Early adopters of Big Data analytics have gained a significant lead over the rest of the corporate world. Examining over 400 large companies globally, we found that those with the most advanced analytics capabilities are outperforming competitors by wide margins.

The leaders are twice as likely to be in the top quartile of financial performance within their industries; five times as likely to make decisions faster than market peers; three times as likely to execute decisions as intended and twice as likely to use data very frequently when making decisions.

To get in the Big Data game, a company needs three kinds of table stakes: large quantities of information in a format allowing for easy access and analysis; advanced analytical tools, such as Hadoop and NoSQL; and people capable of putting those tools to work. But many companies have not yet laid the groundwork. But having these table stakes alone won't help you win, because Big Data isn't just another technology initiative. Let's look at what's involved. Leading companies begin the embedding process by spelling out their ambition — for instance, incorporating advanced analytics and insights as key elements of all critical decisions. They also answer the question: how is Big Data going to help us? There are four areas where analytics can be relevant: improving existing products and services, improving internal processes, building new product or service offerings, and transforming business models. For example, Humana, the US health insurance provider, uses claims data to determine who is likely to end up in a hospital for preventable reasons and then intervene early.

With ambition defined, Big Data leaders work on developing a horizontal analytics capability. They learn how to overcome internal resistance, and to create the will and skill to use data throughout the organisation. It's a big job. Leading companies typically define clear owners and sponsors for analytics initiatives. They provide incentives for analytics-driven behaviour, ensuring data is incorporated into processes for making key decisions. They create targets for operational or financial improvements, and work to trace the causal impact of Big Data on the achievement of these targets. Big Data leaders then create an organisational home for their advanced analytics capability. Companies with deep analytics skills and an emphasis on experimentation and innovation, such as Google and Progressive, can rely on a generally decentralised approach.

Many others have found that a centre of excellence (CoE) offers the most advantages and the fewest limitations. A well-functioning CoE enables cross-business-unit access and data-sharing. At the corporate level, the CoE serves as the go-to organisation for analytics strategy and insight support. It sets the road map, and establishes and maintains privacy policies. How to get started in Big Data? A good first step is to benchmark your industry and determine your company's position in analytics compared with that of your chief rivals. This will help you determine the investment necessary to improve your relative position. If you are significantly behind the competition, you will have the kind of burning platform often required to create and sustain change.

The writer is a senior partner at Bain & Company. The article was co-authored with Travis Pearson, a Bain partner, and Prashanth Aluru, a senior principal at the firm.