Role of Cloud & Big Data in railroad crew management software
One of the most gratifying things that any Big Data Analytics firm can be a part of is the transformation of an established company. Big Data helps in integrating new practices and insights generated by company’s data. Here’s an example of the digital transformation in railroads crew management which happened in the collaboration between CloudMoyo and a North American railroad operator.
Logistics are the lifeblood of a transportation company. This North American railroad company has been in operation even before the 1900s and operates in central U.S, Mexico and Canada. It has over 10000 freight cars, 1050 locomotives and their rail network comprises approximately 7000+ route miles that link commercial and industrial markets in North America. It has approx 500 trains running per day with an average of 800+ crew members daily across 180+ interchange points with other railroads. Add to this the complexities of repairs, re-crews, duty allocations, scheduling, incidents, services, people & goods movement, vacations, communications and it turns out to be a heck of a day. Needless to say, it’s a massive transportation and logistics business with mountains of data. In order to get its operations right, railroad turned to Big Data for a solution.
Why do you need a cloud-based rail crew management system?
Thanks to Cloud and Big Data analytics, CloudMoyo was able to come into this industry as a relative outsider and deliver a next generation, cloud native crew management system that addresses all the challenges of managing complex transit operations. In order to implement the crew management software, a 12-month schedule was created with the aim of turning the client from a company without a centralized or integrated system that relied on text messaging for duty notification into an information-centric, data-smart organization. As a result of the new system, 100% of all the train scheduling, as well as the deadheading (the movement of commercial vehicles or crews in non-revenue mode for logistical reasons) are managed through railroads crew management solution.
But while infrastructural efficiency has been greatly improved, that was only half the problem solved. As in most businesses, the improved management of the workforce is where the real value lies. Without a centralized and integrated system, all crew tracking was done manually, and there was a text-message based system of duty notification. Outdated processes and human error often came together to create train delays, spoiled goods and many wasted man hours for the nearly 2000 employees of the company.
CloudMoyo CrewCall System
CloudMoyo developed a CrewCall system, which was able to schedule crews effectively by managing crew availability, crew allocation order and train schedule compliance, as well as assigning crew to trains with a cloud-based notification and acceptance system. Attendance records, automatic crew selection, member availability and tracking were all new and vital aspects of crew management that were built into CrewCall and transformed the workforce management for the client.
Ultimately, the system uses Microsoft Azure cloud and the advances in mobile technology to balance crew and equipment needs in a cost effective way and enables quicker time to deployment for the operators, thereby leading to quicker ROI. Workforce and logistics management, which is delivered via a state-of-the-art user experience, leads to an improved work experience for all the crews involved, as well as a reduction in overtime and therefore cost savings, and a stricter adherence to labor laws.
A happier, more efficient and more productive workforce are all huge benefits derived directly from excellent Big Data analysis. That intervention allowed a company to look towards the future and expand its operations with the knowledge that they now have, all system in place which can scale easily and can carry them into the future effectively.
Click here to read more on how CloudMoyo helped a North American railroad to manage its crew efficiently.
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