Deriving Innovation from a Data-Driven Mind-set: Part 3
Take a glimpse at how organizations worldwide apply big data analytics to innovate solutions
The first two installments of this three-part series provided an overview of big data analytics and showed how to apply analytics to innovate fresh ideas—the fuel that helps accelerate innovation for business growth. This final part offers a range of case study summaries that demonstrate practical use of big data analytics to help spark, guide, and sustain innovation.
Crafting customer experiences
Founded in 1984, eircom Group Ltd. provides communications services such as fixed-line, mobile, and broadband services. The organization uses advanced analytics to craft customer experiences that help improve satisfaction and retention. Because of fierce industry competition that increased the churn from customers easily switching service providers, eircom experienced an annual loss of EUR1.5 billion. The company used sentiment analysis and predictive modeling to determine which factors contributed to unfavorable customer experiences and to identify customers most likely to switch communications service providers.
As a result, the organization saw a 6 percent increase in customer retention by identifying the most effective ways to enhance customer experience. By combining multiple sources of data and using predictive analytics modeling, eircom determined which factors influenced customer churn and discovered effective ways to enhance customer retention.
Gauging social media input
The city of Toulouse, France deployed social data analysis that it used to enhance understanding and meeting the needs of its citizens. The analysis took into account factors including context, content, and sentiment. With full visibility of residents’ concerns and expectations, the Toulouse city government strengthened its public relations, urban planning, and policy development.
In the first year of implementation, the solution collected and analyzed more than 1.6 million comments to identify 100,000 unique comments pertaining to Toulouse. The analysis enabled the city to precisely identify specific problems. As a result, the city can now respond to pressing issues in a timely manner. For instance, it has accelerated its average response time to road maintenance by 93 percent, from 15 days to 1 day. Supplementing citizens’ feedback channels with data from the social network helps the city to gauge sentiment and mine the data for concerns to responsively change service delivery.
Accelerating knowledge transfer
Inefficiency causes 40 percent of late-stage cancer treatment trials funded by the US government to be abandoned before completion. The IBM Watson™ platform helped a cancer center accelerate knowledge transfer from research to practice. This cancer center is working with IBM to train the IBM Watson platform on discovery of new insights into the most effective treatments for patients in a variety of clinical situations. The solution provides evidence-based insights to help researchers understand the effects of therapies on certain patient cohorts. In addition to evidence-based insights, unstructured data is used in analyses through natural language processing, and overall analysis continues to improve iteratively over time through machine learning.
Applying discovery to gain insight
MultiView, Inc. wanted to enhance the relevancy of search results for its buyers’ guides to help increase revenue. However, its existing search and navigation software required significant customization, which could be time-consuming and costly. Using IBM® InfoSphere® Data Explorer software, the company can provide highly accurate and relevant search results for data stored in internal databases and advertiser websites.
Data Explorer enables MultiView to apply navigation and discovery capabilities to its sales and customer relationship management (CRM) systems so staff can gain insights into customer needs. The software’s rich analytic capabilities help staff measure success and refine search results, and it allows the organization to leverage advanced discovery capabilities for associations that enhance gathering, managing, curating, and sharing content.
Enhancing traffic flow
The Dublin city council delivers housing, water, and transport services to 1.2 million citizens in the Irish capital. The roads and traffic department manages the city’s road network and a fleet of roughly 1,000 buses. The city council sought to find a way to dynamically monitor the movement of each of the city’s 1,000 buses.
The city deployed an intelligent traffic control solution that uses geospatial data from global positioning system (GPS)-equipped buses to visually display the near-real-time position of each bus on a digital city map. Using the solution’s dynamic digital map and camera feeds, controllers can quickly identify congestion in its early stages and gather the information needed to help mitigate the impact on affected areas.
By making underlying bus fleet trends more transparent to planners, the Dublin city council can also more effectively manage resources and optimize bus routes to help save energy and reduce pollution. Instrumentation using GPS signals, the dynamic digital map, and camera feeds enable controllers to visualize and gain insights on traffic patterns.
Exploring astronomical imaging
Headquartered in Dwingeloo, the Netherlands, ASTRON is the National Institute for Radio Astronomy. The institute needed to develop a resource- and energy-efficient way for astronomers to analyze an unprecedented amount of unstructured data from what is designed to become the largest radio telescope ever built.
ASTRON built a streaming analytics platform that runs on energy-efficient exascale supercomputing technology. The solution also accelerates the identification of relevant images and data by approximately 99 percent, making the information available to astronomers for analysis in minutes as opposed to days.
It is expected to collect data from 3,000 dishes composing the telescope network and use advanced algorithms to correlate radio signals with existing astronomical data. The information can quickly provide astronomers around the world with relevant new images of galaxies, dark matter, and the universe. By analyzing this information, the institute expects to gain insight into answering major astronomical questions.
The IBM Success Stories site provides expanded versions of these and other case studies that demonstrate how organizations are implementing big data analytics to spark, guide, and sustain innovation that helps them remain competitive or advance objectives. Please share any thoughts or questions in the comments.