Today’s businesses face tremendous pressure to leverage technology for optimizing and unlocking the full value of their assets. Regardless of whether those assets are heavy machinery or intellectual property, workforce employees or trains and airplanes – rising capital costs and competition are driving higher utilization rates. This optimization drive is intense, and it runs throughout the asset ecosystem – from the original equipment manufacturer and supply chain; to operators, service teams and the end user.
Big data and cutting edge analytics solutions can address these pressures, but only when properly designed and executed in the context of new and disruptive business models. In particular, the explosion of sensor-rich Internet of Things (IoT) data has helped companies present offerings like “power by the hour” and long-term maintenance service plans for airplanes, trains and other complex equipment. These new models require visibility and insight down to sensor-level data to better understand and augment asset performance.
Leveraging Technology the Right Way
Optimizing assets helps organizations cut capital expenditures and drive revenue growth by improving total cost of ownership and extending the useful life of an asset. However, few of these benefits are realized if we can’t properly orchestrate our technologies and architectures. Point solutions leveraging sensor and machine data – processed both at the edge and in more centralized locations – reap critical insights, but only when viewed as part of a highly-connected information environment.
Teradata helps companies leverage all their IoT data for faster, better insights and decisions around valuable company assets. Our automated and scalable solutions create analytic agility to detect emerging issues and anticipate supply chain needs; predict equipment failures and reduce downtime; boost quality assurance from continuous improvement; and enhance product safety and regulatory compliance.
Teradata’s demonstrated track record includes assets optimization for some of the world’s largest companies. We partnered with a global aerospace manufacturer, for instance, to better assess remaining usable life and streamline airplane maintenance and overhaul operations. And we helped a leading industrial manufacturer save tens of million dollars and increase customer satisfaction through scalable predictive maintenance.
Proven Enterprise Capabilities
Let’s take a closer look at one use case involving Siemens, the global engineering giant. Teradata helped the company’s mobility unit position its high-speed trains to compete successfully with other forms of transportation—namely airlines. For one train route between Madrid and Barcelona, we helped build a predictive maintenance model to flag mechanical issues prior to breakdown. This allowed for preventive service and minimal down-time; we even applied machine learning to weed out false positives – a costly problem in an industry where false alarms outnumber real alarms.
Ultimately our efforts helped Siemens achieve a 99-percent on-time arrival rate which, in turn, gave the carrier confidence to offer full refunds to any traveler delayed more than 15 minutes. This became a huge differentiator that enabled Siemens to realize $100 million in opportunity gains by claiming 60-percent of airline customers who had been taking the same route!
Teradata remains an industry leader in assets optimization, with deep expertise in enterprise-grade analytics and a unique, data-centric approach. We help companies unlock asset value by breaking down silos and architecting the big data and IoT environment for maximum visibility and insight. The result is more efficiency in asset planning and operations, better decision making and – ultimately – a healthier bottom line.
Waseem Shaik is the practice lead for IoT Analytics at Teradata. He is responsible for defining the IoT strategy and designing business solutions for Teradata customers.He has over 16 years of experience in enterprise solution design, development and deployment in the areas of supply chain and analytics for fortune 500 companies across various industry verticals, globally. He holds a Masters degree in Operations Research and Industrial Engineering from UT Austin and a bachelors degree from Indian Institute of Technology, Madras.
Cheryl Wiebe is the west Americas lead for Teradata’s Think Big business focused on the Advanced Analytics Center of Expertise, and she leads the Analytics of Things practice across the various business units of Teradata.
She collaborates with business and advanced analytics professionals and clients on how they can accelerate their capabilities and professionalize their advanced analytics practices. She also advises many clients who are initiating their Internet of Things journey on how to align business strategy with analytics investments to get started on the road to being Competitors in Analytics of Things.
Cheryl openly shares her views and opinions publicly, and was asked to join the faculty of the International Institute of Analytics (IIA) in 2015 to begin talking about advanced analytics specifically for manufacturing companies and the Analytics of Things.