ROI on Analytics – Now We Have Numbers

A recent study by the Nucleus Research says that Analytics pays back $10.66 for every dollar spent. The study is based on data from 60 case studies and relates to investments in Business Intelligence, Performance Management and predictive analytics. Not surprising are the areas where they saw ROI increase – revenue, gross margin and expenses.

Enterprises have used various metrics to track the effectiveness of Business Analytics. Cycle Time to Information (CTI) is a metric that measures the elapsed time between the occurrence of a significant event and the time this information is available to a decision maker who has to act on that information. Cycle Time to Action (CTA) is variation of this metric which measures the elapsed time to act on information after an event occurs.  These metrics are useful to track the efficiency of a Business Analytics infrastructure and the elimination of manual processes to increase productivity. As the volume of data increases in an enterprise, automation in data management will become more complex in the future.

The primary purpose of Business Analytics is to improve the quality of decision-making. Better decisions directly impact the business. Target, a hundred year old retailer, is using Predictive Analytics to expect shopper behavior (See Target Your Shoppers – Retail Predictive Analytics). Concept One, a manufacturer of apparel and accessories,  has used analytics to be more selective about renewing their licensing agreements.  Procter & Gamble is increasing their analytics staff fourfold while reducing IT spend in other areas (See Proctor & Gamble – Business Sphere and Decision Cockpits).

Yet, Business Analytics adoption in enterprises has not reached its potential. A IBM/MIT study in 2010 cited that the most common barrier to implementing an analytics solution are lack of understanding of how to use analytics to improve the business. Time spent on analytics competes with other priorities for business users.

An ROI analysis is a very useful tool for business managers who are trying to allocate scarce resources to get the biggest bang for the buck. Now they have something to talk to CFO.

Further Reading

• Research Note by Nuclear Research (November 2011)
• Climbing the Ladders of Business Intelligence
• Biggest barriers to business analytics adoption: People
• Predictive Analytics 101 (quick overview)