Big Data and Advanced Analytics: success stories from the front lines
1. Asking the right questions The more data-rich your business becomes, the more important it is to ask the right questions at the beginning of the analytical process. That’s because the very scale of the data makes it easy to lose your way or become trapped in endless rounds of analysis. Good questions should identify the specific decisions that data and analytics will support to drive positive business impact. Asking two simple questions, for example, helped one well-known insurer find a way to grow its sales without increasing its marketing budget: First, how much should be invested in marketing, and second, to which channels, vehicles, and messages should that investment be allocated? These clear markers guided the company as it triangulated between three sources of data, helping it develop a proprietary model to optimize spending across channels at the zip code level. (For more on this, read “What you need to make Big Data work: The pencil”). 2. Being creative with what you have More data can hone models of consumer behavior, allowing for more accurate views of opportunities and risks. One telecom company in emerging markets recognized that its data could solve a longstanding quandary faced by financial service companies: how to meet the need of millions of low-income individuals for revolving credit, similar to credit cards, without a credit-risk model. Executives at the telecom realized that the payment histories of their mobile network could be used as a way to solve that conundrum