Businesses have seen tremendous increase in complexity of their operations and processes over the last few years. Optimizing operations for topline/bottomline impact and personalizing services for customers are fundamental drivers that have led to increase in complexity in businesses.

Organizations are thus trying to become more intelligent about their customer’s preferences and their operations. As part of this, they are trying to efficiently manage and mine their business data (of customers and operations).

However, today the data within organizations has exploded beyond the regular capabilities of most organizations. There is a clear need for a lot more sophistication in the management and analysis of data.

That is where Analytics is emerging to play a vital role. The primary objective of Analytics is to help organizations leverage data in this information age for scientific and efficient decision making, enabling them to reach the right customer through the right channel, with the right product, at the right price, and at the right time.

As Thomas Davenport describes, Analytics—the application of systematic quantitative methods to solve business problems—may be applied to a variety of business problems, including customer relationship management, supply chains, and financial performance. He rightly points out that Analytics will enable organizations to serve customers according to their profitability, will allow optimization of supply chains for minimizing disruptions and in-process inventory and will enable making accurate forecasts of future performance so organizations can react in advance of situations.

As we realize where Analytics can be deployed in organizations, one is tempted to ask: Is Analytics really going to impact businesses? According to a recent study by the IDC Consulting Group, Analytics generates an average five-year ROI of 431 percent! Their study confirmed that the usage and benefits of Analytics deployed within the marketing function directly correlated to marketing performance and overall business results. The value of Analytics is further corroborated in another survey released by Accenture, where nine out of 10 executives from the largest U.S. companies said they needed stronger business intelligence and Analytics capabilities that provided better analysis of and insight into their customers and operations.

One can clearly see how important Analytics is becoming in today’s organizations. It is no wonder that the Analytics market is expected to experience a 35% compound annual
growth rate over the next five years!

However, our experience shows, organizations are at different stages of Analytics deployment. While some are limited to the capability of generating MIS reports through OLAP tools, others are relying on basic forecasting techniques to understand future events pertinent to their business; and some organizations are deploying cutting edge Analytics tools and techniques for dissecting their data on several dimensions through sophisticated predictive modeling and segmentation techniques thereby making optimal business decisions. Barclays Bank, for example, increased its revenue per active account by 25 percent, while reducing delinquent accounts by 23 percent, by following its
analytically oriented “Information Based Customer Management” strategy.

Why is there a significant gap across organizations in the level of Analytics deployment?

We believe the key reason is the "push" it receives from "C" level executives. The adoption of an "Analytics driven decisioning" approach to business, requires significant changes in mindset and skills within an organization. Such changes need a persistent and well communicated drive from the top.

We believe that the second most important reason for this gap is the availability of high quality data across the entire organization. While organizations of select industries and
geographies have built capabilities to capture and extract all data from their interactions with customers, other organizations are not able to integrate data across different systems and departments or ensure consistent high data quality across systems, resulting in suboptimal customer information quality. Lack of good quality data obviously results in a “garbage-in garbage-out” situation.

Clearly the above two ingredients are essential for organizations to advance through the stages of sophistication in their Analytics deployment.

While we realize the importance of Analytics in today’s businesses, we need to keep in mind that there is no shortcut to building an organization that deploys sophisticated Analytics for optimal decision making. This capability needs time and patient / persistent support to develop as a lethal weapon for the organization in competing with others. We at Inductis have been providing Analytics support to several clients over the last six years and have seen them develop sophisticated capabilities over this time. We know organizations need to be persistent and iterative in Analytics deployment initiatives. This takes time and complete commitment but the cumulative impact can be highly significant.

We hope that your organization is able to achieve similar levels of Analytics sophistication (if not already there) and reap the corresponding business benefits.

References:

1. Getting the Most out of Customer Data- Amy Valley and Joe McGee.
2. Analytical Life Stages Using Loyalty Analytics to Grow from Data Infancy to Adulthood.htm
3. Competing on analytics - Thomas Davenport.
4. IDC White Paper- Marketing Leaders Use BI to Rise to the ROI Challenge.
5. Anticipating Consumer Behavior With Analytics.htm
6. Companies Need to Improve Business Intelligence Capabilities to Drive Growth, Accenture Study Finds.htm
7. Building profitable customer relationships with data mining- Herb Edelstein, President Two Crows Corporation.
8. Analytic Intelligence in Retail- A SAS white paper
9. http://www.igate.com/whitepapers/Banking_on_Analytics.pdf

1. Govind Choudhary, Manager, Analytics Services
2. Megha Gupta, Analytics Services