IBM has introduced 20 new predictive analytics solutions across 12 industries, all tailored for specific use cases within those industries based on data IBM says it has collected from 50,000 client engagements. Credit: Thinkstock Drawing on a history of more than 50,000 analytics-focused client engagements, IBM today debuted 20 new behavior-based predictive analytics solutions tailored to address 12 industries and use cases within those industries. “We have seen companies trying to take advantage of new big data and analytics technologies for a while now to apply them to various different business use cases,” says Marc Andrews, vice president, Industry Analytics Solutions, IBM. “They continue to struggle with how to get started. There’s a lack of skilled resources. They have to spend a lot of time customizing and maintaining the solutions they build out.” [ Related: 5 things CIOs should know about prescriptive Analytics ] SUBSCRIBE TO OUR NEWSLETTER From our editors straight to your inbox Get started by entering your email address below. Please enter a valid email address Subscribe That’s where IBM comes in, he says. Big Blue is using the real-world data gained from its client engagements to create predictive analytics solutions that clients can use out of the box, with prebuilt dash boards and interactive applications. Clients can just inject the data and start leveraging the existing interfaces, he says, though they do have the ability to tweak or modify the solutions as needed. “We’re getting down to a level of specificity to these individual use cases and business questions that I don’t think anyone has really gotten to before in delivering these types of solutions,” he adds. [ Related: How UPS uses analytics to drive down costs ] For instance, one of the new solutions for oil and gas companies is aimed at helping them manage submersible pumps, with analytics to predict outages before they occur and optimize production. For automotive there is a solution for welding robots and another for painting robots. Other solutions will help telcos analyze how customers are using their phones, how long their calls are, what time of day they’re most likely to place calls and which cell towers they’re using. Other industries and solutions covered include the following: Retail. These solutions are designed to help retailers understand the potential overall revenue impact of individual products and lines to make smarter decisions about what products to carry and how best to promote them. Banking. The goal of these solutions is to help banks use customer spending patterns to predict financial and life events and deliver more relevant offers. Wealth management. The solutions for wealth management firms are designed to help them understand behaviors associated with higher profit clients to determine who they should target and how to drive increased activity. Media & Entertainment. These solutions aim to help media and entertainment companies better understand their audience and viewing behaviors to deliver advertisers higher value micro-segment targeting capabilities. Andrews says the new solutions include pre-built predictive analytic modeling patterns and interfaces for focused industry use cases, along with data preparation capabilities to manage unique data and streamline collection and prep of data. The majority of the new offerings are already available or will be within the next two to three weeks (with the remainder rolling out by the end of summer), Andrews says. He notes that they have been built with out-of-the-box integration with IBM ExperienceOne, Big Blue’s integrated portfolio of cloud-based and on-premises offerings intended to help clients deliver more valuable customer engagements by bringing together marketing, sales and service practices. In addition, IBM Maximo Asset Management has been pre-integrated to provide enhanced capabilities around work management, job plans, work order tracking, service requests and reporting. Follow Thor on Google+ Related content feature Gen AI success starts with an effective pilot strategy To harness the promise of generative AI, IT leaders must develop processes for identifying use cases, educate employees, and get the tech (safely) into their hands. 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