This article is sponsored by CloudMoyo – Partner of choice for solutions at the intersection of Cloud & Analytics.
One of the most gratifying things that a big data analytics firm can be part of is the transformation of an established company as it integrates new practices and insights generated by its data. That is exactly what happened in the collaboration between CloudMoyo and a North American railroad operator, an organization which has been operating since 1887 across 10 central U.S states as well as northern Mexico and southern Canada.
Logistics are the lifeblood of a transportation company. It has over 13000 freight cars, 1044 locomotives and their rail network comprises approximately 6,600 route miles that link commercial and industrial markets in the United States and Mexico. It has approx. 500 trains running per day with an average of 800+ crew members daily across 181 interchange points with other railroads. Add to this the complexities of repairs, re-crews, allocations, scheduling, incidents, services, people & goods movement, vacations, communications and it turns out to be a heck of a day. Needless to say, its a massive transportation and logistics business with big data. The company had to get its operations right and it turned to big data for a solution.
Crew or Workforce management is another massive arena that has been disrupted by the cloud and big data. For a company to be able to harness the opportunities provided by big data, it is vital that the data analysis takes into account the volume, variety and velocity of the logistics-related data which is being generated.
For previous generations working at the railroad, the logistics of transporting millions of tons of grain were too complicated to process and forecast accurately. Couple those challenges with crew management issues mentioned earlier, the concept of forward planning felt like a bridge too far. But the turnaround in just a short space of time has been dramatic.
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 public transportation management system that addresses all the challenges of managing complex transit operations. In order to create the CloudMoyo Public Transport Management System (CPM), a 12-month schedule was created with the aim of turning the client from a data-poor 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) is managed through CPM.
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 developed a Crew call 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 railroad.
Ultimately, the system uses the Microsoft Azure cloud and the advances in mobile technology to balance crew and equipment needs in a manner that is cost effective 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 to expand its operations with the knowledge that they now have systems in place which can scale easily, and can carry them into the future effectively.