Big Data & Advanced Analytics: Success stories from the front linesAnisha Mukhija
Big data and advanced analytics can transform the business. Even though sometimes the company have not able to capture the true potential of analytics, some companies are already seeing significant values. These companies which incorporated data and analytics into their operation show productivity raised by 6% compared to the peers. Following are the three stories that show how companies have used advanced analytics to their advantage and had an impactful delivery.
1. Asking the right questions
As a business grows, more data-rich the business becomes and hence this increases the importance of asking right questions. These questions are encouraged at the start of any analytical process because the scale of data makes it easy to lose the way and get trap in the endless round of analysis. Good questions identify a specific decision that data and analytics will support so as to drive positive business impact. For example, two simple questions helped one insurer find a way to grow its sales without increasing the marketing budget. First, how much investment should be in marketing. The second was to which channels, vehicles and messages should the investment allocated. This helped in developing a proprietary model to optimize spending across channels by guiding the company as it is triangulated between three sources of data.
2. Be creative
More data can hone models of consumer behaviour. This allows for accurate views of opportunities and risks. One telecom company recognized the data could solve a longstanding quandary which was faced by financial service companies. How to meet the need of millions of low income earning individuals for revolving credit which is similar to the credit card but without the credit risk model. Telecom executives realised this that payment histories of their mobile network could be used to solve the problem. So the company created an innovative risk model to asses potential customer’s ability to repay loans. After this, companies are now exploring an entirely new line in emerging market consumer finance which uses this analytics as a core asset.
3. Optimizing spend and impact across channel
Business is all about trade-offs between price and volume, between cost of inventory and chance of a stock out. In the past, such trade-offs were more of gut instinct and less of data. In the age of cookies and click through, it is not easy to optimize spending allocations. Big data and advanced analytics eliminate much of the guesswork. One transnational communications company had spent heavily on traditional media to improve brand recognition and invest in social media. Traditional marketing does not measure the sales impact created due to social buzz. Combining data from traditional media, sales and customer use of key social-media sites yielded a model that demonstrated that social media had a much higher impact than company strategists had assumed. More critically, company analysts found that the primary driver of social-media sentiment was not its television commercials but customer interaction with the company’s call centers—and in fact, that poor call-handling was subtracting almost as much value as the TV spots were adding. By reallocating some media spending to improve call-center satisfaction, the company increased its customer base significantly and gained several million dollars in revenues.