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The Value of Data in Business

Up until just a few years ago, organizations collected and stored limited amounts of data, typically transactional in nature, and used the information for measuring operational performance and forecasting future needs. Today, however, businesses have access to vast amounts of data from an ever-growing array of sources such as social listening tools and the Internet of Things.

According to the research firm IDC, the market for Big Data and analytics technology will grow to over $34 billion by 2017, up from just $3.2 billion in 2010. This treasure trove of data and high-tech analytics platforms give business executives powerful new tools to increase performance across every segment of an organization. Here are three ways today’s business leaders are harnessing the power of data to deliver value across their organizations.

Improving Performance Management
Data-in-Business
Image via Flickr by NEC Corporation of America

At the organizational level, data-driven performance management focuses on integrating information across multiple departments such as human resources, sales, customer service, and manufacturing to produce deep, real-time insights into how a business is performing. Once problems are identified, managers can use PM tools to model various solutions and support decision-making.

At the granular level, companies are using analytics tools to drill down into the behaviors and activities that separate high-performing employees from less successful ones. Armed with that knowledge, managers are able to set new best practices and coach new behaviors to improve productivity throughout the company’s workforce.

Utilizing Predictive Analytics
The top reasons business executives use predictive analytics are to better understand their customers, predict trends, inform strategic decision-making, and improve overall business performance, according to research firm TDWI Research.

Retail giant Target used predictive analytics to grow revenue by capturing the “new baby” market. Statistician Andrew Pole identified a group of 25 products that he used to assign a “pregnancy index.” Once a customer reached a threshold score on the index, Target sent personalized mailings with coupons for pregnancy and new baby-related products. Sales in this category skyrocketed.

Informing Decision-Making
The decision scientist is a new breed of data statistician who combines business, IT, applied math, and behavioral sciences to help organizations make data-driven, informed decisions. One of the newer tools they employ are social listening and analytics tools to gain real-time insight into customers’ opinions and behaviors.

Whirlpool used new decision models and social analytics to improve customer satisfaction and loyalty and decrease churn. Using Attensity360, a social monitoring platform, they analyzed what people were saying about the brand on social channels such as Facebook, Twitter, and customer review sites. The results gave the company deep insight into its product development process and resulted in much improved customer satisfaction and increased responsiveness across the organization.

The key to any data-driven solution is acquiring high-quality, highly usable data. According to one study, a median Fortune 1000 business could generate an additional $2 billion in revenue just by improving the usability of its data by 10 percent.

The costs associated with data collection and analysis are rapidly decreasing due to the emergence of scalable cloud-based applications. Business leaders who implement a strategic Big Data program will gain a competitive advantage.

SOURCES LINKED TO IN THE ARTICLE:

http://www.idc.com/getdoc.jsp?containerId=prUS24542113

http://www.inc.com/daniel-enthoven/how-big-data-will-reinvent-performance-management.html

http://www.forbes.com/sites/forbesinsights/2015/01/05/why-you-should-be-using-predictive-analytics/

http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/

http://www.analytics-magazine.org/web-first/900-executive-edge-why-some-data-scientists-should-really-be-called-decision-scientists

https://community.informatica.com/mpresources/docs/Attensity_IDC_Spotlight.pdf

http://www.forbes.com/sites/homaycotte/2015/01/27/quantifying-the-value-of-effective-data/