The transportation industry is witness to the rise of dynamic digital trends, leading to significant transformations within the space. Starting from planning and order fulfillment to warehouse management, the digital revolution has taken over critical operation-centric aspects for major transportation companies, which are now using Big data and analytics for real-time dynamic route planning, and MRO.
The 3PL (third-party logistics) and transportation industry has integrated digital technologies into their supply chain and logistics. By adopting a high unit of automation and operational data, transportation companies have transformed and streamlined their business operations to become more unswerving, well-organized and anticipated. As the transportation and logistics industry continues to digitalize, integration of new innovative technologies will not only improve process efficiencies but also enhance the quality of life for employees. Let’s explore some of the different real-time analytic and Big data technologies which are available to the industry today, and how they can help companies in the domain work better, smarter, and safer.
Acclimatizing to Digital Way
Customers expect a reliable and timely purchase experience every time they order goods through e-commerce. That same sentiments are valid for supply chain managers and manufacturers, and the market/customers demand immediate action whenever downtimes or delays occur.
To meet rising customer demands and respond rather than react to fluctuations, transportation companies need real-time data and analytics that can facilitate a live view of their inventory, on road vehicles and drivers. With this, transportation companies can quickly analyze and respond to time-sensitive data and adjust for greater efficiency, revenue generation, and business value.
Transportation service providers are implementing Big data for hyper connectivity, process optimization and IoT sensors to measure key performance indicators, avoid delays and predictively maintain vehicles. Sensors allow operators to have a relentless connection to their vehicles to monitor, compare, and benchmark operational data to optimize its lifecycle. As a result, operators can anticipate maintenance to reduce errors and deliver goods on-time, every time.
Big Data analytics and mobility are streamlining fleet operations by leveraging hyper connectivity to combine data. The major advantage that stands to be derived here is the ability to keep traffic and trade flowing seamlessly. With real time observation of delays from multiple fleets, terminal operators can optimize schedules in real time, leading to more efficient and effective cargo handling across the entire supply chain. This leads to decreased wait times and the movement of more goods for more customers. In the age of the “right now” customer experience, Big data is letting transportation companies respond swiftly, and ensure efficiency and stability across their entire supply chain.
Ensuring Safer Drive with Analytics
While productivity is important to manufacturers, keeping drivers safe and happy remains at the top of their priority list. Every year there are about 411,000 truck accidents, leading to injuries, fatalities, traffic congestions and higher insurance claims. To ensure drivers safety, transportation companies are leveraging the power of IoT, specifically IoT sensors, to gain access to influential, discerning data about how their drivers are performing. For example, there are IoT-powered sensors for trucks that measure temperature and vibrations in the fabric of a driver unit to monitor for variation points or changes in behavior. Using biomedical signals, supervisors can respond in real time to train drivers or warn them that it’s time to take a break. For drivers who are on the road for longer stretches, or have tight deadlines that need to be met, this real-time data warrants driver safety and alertness on the road.
Nuance arguments like these can also be observed for driver’s behavior while driving. With access to Big data technologies, superiors can monitor for near accidents or frequent stops, and train their drivers to better navigate their vehicle. Alterations in behavior also provides supervisors with a snapshot into potential turnover. For instance, routine driving patterns that suddenly turn into frequent stops or requests for time off could indicate health or physiological problem being faced by the driver. With Predictive analytics supervisor will be able to analyze these driver issues, so that reportative issues can be arrested.
Big Data - Future of Transportation
Although Big data and analytics have greatly improved how producers stay efficient and safe, there is still room to grow. With a snowballing shortage of truck drivers throughout the U.S., autonomous vehicles are rapidly rising as an alternative capable of plugging the gap.
Using real time traffic-intelligence, an autonomous vehicle can automatically choose and reroute itself to a non-traffic route with the least congestion, adjust its speed based on traffic signals, and find a parking space based on its surroundings without much difficulty. Considering that time is money in the transportation industry, an autonomous vehicle’s access to Big data provides alternative ways to save on travel time and fuel.
There is also the possibility to eliminate some transportation costs through 3D printing. for example, manufacturers must often distribute spare parts around the world. Maintaining inventory in warehouse close to the point of requirement is not always easy. Particularly if the equipment in question is moved periodically or hard to reach, such as oil-field assets. With on-demand supply chain services, such as 3D printing, manufactures can supply these parts faster, and at a lower cost.
Transportation and 3PL companies are constantly looking for ways to reduce costs, stay efficient and reliable while maintaining a high level of customer satisfaction. To compete in today’s digital market, transportation companies must ready themselves to look ahead, adapt their business models or adopt new ones, and ultimately embrace the transformative capabilities of Big data and associated technologies for the industry.