The power to predict, transform and optimize business

Writer and Content Strategist, IBM Information & Analytics Group

The transformative impact that data has on industries empowers knowledge workers to explore vast volumes of data from a wider range of sources than ever before. Organizations that make the most of unprecedented data-driven insights—social sentiment trending, buying propensities and the impact of weather conditions on distributed supply chains—can tip the balance of competition in their favor.

What if your organization could personalize loyalty and retention offers for individual customers in real time? What if you could resolve maintenance issues before they disrupt operations? Or imagine how you could improve your bottom line if you were able to detect and interdict fraudulent transactions before they do real damage.

No one doubts the critical importance of finding insights in structured and unstructured data and using that knowledge to successfully anticipate upcoming actions. But how can you do so effectively, consistently and across all your business processes and decision points? 

One way is through data science, which is the practice of extracting knowledge from massive amounts of data through methods such as data mining, machine learning, predictive analytics and statistics. The data science discipline is revolutionizing the way organizations solve problems and gain competitive advantage. transformative power of predictive analytics

Predictive analytics is perhaps the most far-reaching and significant method in the discipline of data science. It enables organizations across sectors to reinvent the way they conduct business by identifying what is likely to happen in the future and determining how they will respond to it. Organizations that adopt predictive analytics can accomplish several objectives. Consider several recent use cases.

Optimizing operations and processes

An auto insurance company knew 80 percent of claims were minor and the risk was negligible. The goal was to determine which cases fell into the precious 20 percent of major claims so they could be prioritized. To that end, IBM built a system that can determine in real time which claims to fast-track. When customers called in, the claims person had all their pertinent data, which made for more positive interactions. This approach had an amazing impact on customers, so the company modified the call center process. As a result, customer relations improved and claims closed faster than ever with less staffing and reduced fraud—all of which resulted in huge cost savings.

Prescribing the next-best action

telecommunications company identifies high-value customers who may be at risk of churn because of dissatisfaction with service quality. The company uses predictive analytics to correlate the health of customers’ modems with the results of satisfaction surveys, enabling it to predict which dissatisfied customers are at risk of churn and intervene with the appropriate solution.

Automating and simplifying processes

An oil and gas company uses predictive analytics to identify potential equipment maintenance problems across its vast network. It also uses a predictive analytics approach to conduct pattern matching and analysis across all relevant data streams and generate warnings and notifications for engineers and operators in the field. Without the ability to automate the analysis, the majority of these problems could otherwise go undetected.

Data science everywhere

The power of data science is in its ubiquity. It is not a crystal ball. But by anticipating the most likely outcome or behavior—who will buy a specific product, default on a loan or credit card, file a fraudulent claim or require a certain medical procedure—firms can significantly improve the accuracy of many decisions made every day.

How can your organization benefit from data science? Find out by attending a webinar presented by Eric Siegel, founder, Predictive Analytics World, and author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die (Wiley, February 2013). The webinar takes place 14 December 2016, where Siegel shares real-world examples of how organizations across industry sectors are transforming their business processes, and he offers a glimpse under the hood to help you understand how data science works. Whether you work in financial services, healthcare, insurance, manufacturing, the public sector or retail, discover how to use the vast amounts of data you collect to improve your business and keep your competitive edge in a constantly evolving world.

Attend the webinar Predictive Analytics: Transforming industries through data science