When is real-time analytics the right analytics?

In today’s dynamic business environment, most firms are focusing on agility, responsiveness and customer centricity in order to remain competitive.

A leading industry survey suggests that 70 percent of executives regard data analytics as a core component to achieve these objectives. However, only 15 percent of businesses report deploying their data analytics project to production. This is primarily due to the difficulty in quantifying the ROI and to budget constraints.

How do you understand your organization’s true requirement for speed? Is real-time analytics an essential component of speed across your organization?

There are three key considerations for improving the speed of the organization to meet the speed required for business decisions:

Technology decisions need to match the speed of business:

The increasingly faster pace of business has increased the demand for real-time, automated decisions and actions. Business leaders today expect results in vastly shortened response times, to support faster (and more dynamic) business decisions.

For example, a typical online retailer has 40,000 price changes in an hour compared to 15,000 price changes per hour for a typical physical retailer. In the digitally connected world, the speed of business decisions needs to match the speed of information. The expectations from technology by business leaders, in turn, are also evolving. The emphasis is now on greater speed and flexibility.

Speed of business varies for functions within an organization

Customer-facing departments such as sales and marketing need real-time analytics and decisions to provide the best customer service and engagement. For example, retailers such as Walmart and Carrefour use geo-fencing/beacon technology and corresponding analytics to enhance in-store customer engagement through proximity based discounts and product information. These applications require real-time analytics and automated actions based on the data. Customer engagement using real time analytics is known to have increased as much as 400 percent.

Backend operations such as supply chain can benefit extremely by high-frequency batch processing of information. They do not require real-time analytics and the scale and agility of technology infrastructure associated with such systems.