- Chapter Objectives
- Prescriptive Analytics in Action: Success Stories
- Introduction
- Implementing Business Analytics
- Business Analytics Domain
- Challenges with Business Analytics
- Exploring Big Data with Prescriptive Analytics
- Wrap Up
- Review Questions
- Practice Problems
This chapter is from the book
This chapter is from the book
This chapter is from the book
Prescriptive Analytics in Action: Success Stories
There is no doubt that organizations have become more competitive through the use of business analytics. A 2013 study by the MIT Sloan Management Review indicates that 67% of companies use data analytics to gain a competitive advantage compared with only 37% in 2010.6 Almost any business—be it focused on consumer products, the entertainment industry, healthcare, or fast food—is using mountains of data to improve customer service, operations, supply chains, or product designs.7 Business analytics is no longer a buzzword. A recent survey of Gartner Inc. conducted in June 2013 indicates that over 30% of companies in each sector, such as media and communications, banking, and services, have already invested in data analytics.8 The same survey stated that over 50% of companies in transportation plan to invest in the next two years in data analytics. The number of investors in data analytics is currently 41% in health care, 40% in insurance, 39% in retail, and 38% in government.8
The analytics can be implemented in almost all business functions. Currently, according to the survey, almost 55% of respondents indicated that business analytics is used to improve customer experience, 49% use business analytics to increase efficiency, 42% use it for marketing purposes, and 37% use it for cost reduction.8 In the same survey, 70% of respondents indicated the use of business transactions as the source of data; 55% use log data, 42% use machine sensors, 36% use source e-mails and documents, and 32% utilize social media.
The use of business analytics for productivity improvement has expanded not only to large corporations but also to smaller companies. First Tennessee Bank, for example, lowered its marketing cost by 20% and increased its return on investment by more than 600% by using data analytics for better customer marketing.9 The following bulleted items briefly discuss how Target and LinkedIn use business analytics to reach more customers:
- Target—Retailers have collected customer information for decades. This information has helped retailers to increase their sales and create targeted promotions based on specific customer segmentation. However, Target has moved data analytics into a new stage. Instead of advertising to customer segments, Target now is able to “laser target” each customer with his or her specific needs for specific products. In early 2012, the New York Times reported the story of a Target analyst who was able to determine if a customer was pregnant based on the pattern of previous purchases. That information was then used to advertise targeted products.10 Target’s sales skyrocketed, and the company’s revenues have grown by $23 billion since the new data-informed strategy was implemented.11
- LinkedIn—LinkedIn, the social networking website, was founded in December 2002 and was first launched in May 2003. In 2006, the data scientists at LinkedIn started to investigate connection patterns and profile richness of their 8 million users. They tested what would happen if a user was presented with names of people with whom they had not yet connected but seemed likely to know. And, it worked. “People you may know” ads achieved a 30% higher click-through rate than the rate obtained by other prompts 12 and the campaign generated millions of new page views and the LinkedIn membership network grew significantly. In May 2014, LinkedIn had 300 million registered users worldwide.13