Magellan brings machine learning and BI to the masses
Enterprise content, the Internet of Things, social media, real-time, and digital transactions all have one crucial thing in common: generating vast quantities of data at ever-faster rates. With terabytes, petabytes–and soon, exabytes–of data from sensor networks, customer activities, or internal business applications, enterprises have enormous opportunities to gain intelligence about nearly anything they want to track.
The problem is that there is too much data, and much of it is not important. Picking out relevant information from mountains of non-relevant or badly formatted data and assembling these points into meaningful patterns to guide decision-makers is a tall order, even for the most powerful business intelligence and analytics software. Another limiting factor is that the software can’t act on its own; dozens of expert analysts and data scientists may be required to set it up, and then spend weeks or months sifting through its findings.
Enter cognitive computing systems such as OpenText Magellan, an artificial intelligence-powered analytics platform that blends enterprise-grade business intelligence with cognitive computing to enable machine-assisted decision-making, which in turn helps enterprises automate repetitive tasks, gain extra value and insight from their data stores, and operate more effectively.
Key business applications of cognitive computing?
The driving business case for cognitive computing is that it transforms content or data into not just data points on a graph but potential actions. It can spot patterns, identify the tone, sentiment, and specific emotions of written content, predict trends, and recommend the most productive next step.
In fact, many market analysts believe “machine-assisted decision-making” is the sweet spot for cognitive solutions. Instead of science fiction clichés of out-of-control computers taking over the world, picture well-trained assistants who gradually develop the judgment to make suggestions to their boss, and then can be granted the responsibility to make small, repetitive decisions in cases that would be too boring or time-consuming for a human to handle.
Temperature or pressure monitoring, such as in a factory or utility line, is one example. Sensors can deliver new readings dozens of times a second, but it wouldn’t be an effective use of a worker’s time to have them just staring at gauges. Instead, a cognitive system could be trained to detect when a temperature is far enough from the norm to alert a human–and to recommend the best way to address the issue. (For example, either “there are no other signs of distress, and all other readings before and after are normal, so this is probably a random blip” or “this is problematic–maybe open the release valve.”)
Such machine-assisted decision-making could also apply in many other industries that require frequent checks but only occasional human intervention, such as?detecting fraud, managing investment portfolios, or directing traffic flow through a downtown, stadium, or airport. And it can contribute to higher-level goals, such as improving customer satisfaction, reducing inefficiency, or identifying the best new products for given markets.
OpenText recognizes the current value and potential of cognitive computing across a wide range of industries and business functions. In fact, that’s why we built Magellan and its machine learning functions on the framework of our industry-leading OpenText Analytics Suite, which offers sophisticated business intelligence functions, easy-to-use query and display functions, and the ability to process enormous volumes, and a nearly unlimited range of data types. The following are some typical Magellan use cases, reflecting the experiences of our early adopters worldwide.
Increased customer satisfaction?
Magellan can monitor all sources of enterprise data in real-time, detecting and learning patterns, then make decisions based on the data and take appropriate action automatically, all within a split second. This can be applied to behind-the-scenes operations that directly affect customer satisfaction, and therefore, organizational revenues.
A large Asian airport was able to leverage cognitive analytics to increase operational efficiency and competitiveness. Like many global airports, this one suffered from inefficiencies associated with security line backups, foot traffic bottlenecks, malfunctioning escalators, and broken washrooms. These inefficiencies cut into customer satisfaction, costing millions of dollars every year in lost passenger revenue.
The airport used Magellan to analyze data captured from around the facility and make faster decisions to alleviate problems. For example, by analyzing foot traffic data captured from hallway/doorway sensors and security cameras, and combining it with weather data and real-time flight arrival data from the control tower, Magellan helps the airport manage gates by automatically opening those closest to connecting gates, dispatching gate crews, and alerting facilities staff when and which washrooms to clean for disembarking passengers.
Integrated insights?
Cognitive systems can find relationships between data from across the enterprise, even if it comes from disparate functions. Using Magellan, a law firm was able to find relationships between staffing and billing from its data. This helps the firm monitor and analyze the profitability of cases with a real-time comparison with similar cases. Magellan also helped improve the firm’s discovery process by digging through its archive of legal contracts, tracking pertinent documents, and incorporating news and social media to support a case. Predictive analytics can anticipate the behavior of judges, juries, and venues based on past cases showing similar environments.
Enhanced sales and marketing?
Cognitive systems help marketing campaigns succeed by observing real-time reactions of targeted customers most likely to take an interest in products or services, merged with campaign history data. These systems also help enhance brand and product management through social media analysis.
A consumer brands company uses Magellan to examine customer preferences based on data collected through a variety of interactions, including social media comments. The company also wants to deepen its understanding of its customers so that it can better nurture them through the purchasing funnel. Magellan can play a role in automating purchasing processes. It can also track data from orders, inventory, and shipments to predict and ease potential bottlenecks and assure rapid, event-free product delivery.
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The system includes data on customer relationships and incorporates natural language processing plus a rules-based inference and calculation engine. Dimensions and metrics such as historical purchases, financial activities, mergers and acquisitions, regions, customers’ profiles, and industries are used to pinpoint customer behaviors and tendencies, detect patterns, or help target specific markets or customers that could be hard to surface using classic methods.
Magellan’s tracking and analytics capabilities can also monitor customers’ attitudes about products, brands, or loyalty programs. Blended with data from finance, sales, engineering, legal, HR, and IT, profitability evolution over time can be analyzed. Predictive analytics also support decisions such as the best timing for upselling or cross-selling.
Improved quality of service?
Cognitive systems can help assure higher-quality service delivery through knowledge management, and the blending of various data sources inside and outside organizations. A governmental organization in Asia turned to Magellan to improve services provided to its citizens by monitoring key topics of citizen interest and gathering relevant information from a variety of diverse sources, including newspapers and social media postings. Magellan then calibrates this information against the operational data the government agency acquires from its healthcare system and other government service systems. Quality of service is based on monitoring the sentiment and emotion shown by data provided by citizens.
More accurate compliance?
Cognitive systems can play a role in ensuring corporate compliance. For example, enterprises can offer user interfaces to manage compliance mandates. Such systems can digitally examine documents such as contracts, partnership agreements, or marketing materials to detect and flag areas that may be affected by laws, regulations, or existing corporate policies. As a result, compliance staff time is freed up for more pressing or strategic business problems, versus being tied down with manually scanning all corporate materials. A U.S. defense agency that is going digital sought to better interpret and understand the content of its contracts. The project is massive, with hundreds of thousands of contracts being digitally encoded into the agency’s contracts management system. The agency turned to Magellan to examine contracts for terms, key concepts, and numerical terms and provide deep insights.
The Road to cognitive computing success?
Organizations have only taken the first steps on their cognitive computing journeys with OpenText Magellan. This emerging way of managing and digesting information has no limits and is capable of every critical function from managing contracts to enriching customer interactions. With today’s data-aware environments and infrastructures–such as OpenText Magellan, which is built on the cutting-edge platform Apache Spark –cognitive algorithms can work within a single system to realize a broad range of business use cases. By processing and analyzing enormous amounts and varieties of data, cognitive systems will find patterns and deliver insights, in real-time.
Magellan brings machine learning and BI to the masses?
Magellan is a flexible artificial intelligence (AI) and analytics platform that merges machine learning, advanced analytics, and enterprise-grade business intelligence (BI) with the ability to acquire, merge, manage, and analyze big data, both structured and unstructured.
Magellan offers an easy-to-use, pre-integrated, and cost-effective cognitive computing platform to enable machine-assisted decision-making, automation, and business optimization for your organization. As a unified platform, Magellan dramatically reduces the time, effort, and expertise necessary to implement the technologies required for an AI and analytics solution, relieving organizations of dealing with installation and integration headaches, so they can immediately focus on what’s important: analyzing their valuable data.
This means businesses of all types have a cost-effective and timely method of leveraging machine learning to drive their critical decisions. Magellan discovers insights from big data and empowers IT teams, operational users, and business analysts to share findings, make more informed decisions, and take more effective action. Magellan includes the following features: