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Transforming transportation with real-time analytics

 Transforming transportation with real-time analytics

In today’s digital economy, technology trends are motivating businesses in every industry to transform their supply chain. From planning and order fulfillment to warehouse management, supply chain companies that utilize big data and analytics are seeing a profound impact on their growth and long-term success.

The transportation industry has long incorporated digital technologies into their supply chain and logistics; but today, technology innovations are making it possible to think beyond functional silos. By utilizing a high degree of automation and operational data, transportation companies become more reliable, efficient and predictable. As the industry continues to digitalize, new innovative technologies can not only improve process efficiencies but also improve the quality of life for employees. Let’s explore some of the different real-time analytic and big data technologies that are available to the transportation industry today, and how they allow companies to work better, smarter, and safer.

Adapting to the Amazon way

In the age of Amazon, customers expect a consistent and timely sales experience each time they shop. That same sentiment can be said for supply chain managers and manufacturers, who demand immediate action whenever downtimes or delays occur.  

To meet these growing demands, transportation companies need access to real-time data and analytics that provide a live view of their machinery, vehicles and operators. With this, they can quickly analyze and respond to time-sensitive data and make adjustments for greater efficiency, revenue generation, and business value.

In particular, transportation companies embracing big data are utilizing hyperconnectivity, process optimization and IoT sensors to measure performance, avoid delays and predictively maintain vehicles. Sensors allow operators to have a constant connection to their vehicle to monitor, compare, and benchmark operational data to optimize a vehicle’s lifecycle. As a result, operators are able to anticipate maintenance to reduce errors and deliver goods on-time everytime, while offering great value.

Big data analytics and enterprise mobility are also improving fleet operations by leveraging hyperconnectivity to consolidate data. One major benefit here is the ability to keep traffic and trade flowing smoothly. With a live view of delays from multiple fleets, terminal operators can manage schedules in real time, leading to more efficient and effective cargo handling across the entire supply chain. This leads to reduced wait times and the movement of more goods for more customers. In the age of the 'right now' customer experience, Big data is allowing transportation companies to respond quickly to ensure efficiency and stability across their entire supply chain.

Ensuring a safer drive

While efficiency is important to manufacturers, keeping drivers safe and happy remains at the top of their priority list. Each year there are approximately 411,000 truck accidents, leading to injuries, fatalities, lengthy traffic jams and expensive insurance claims. To keep drivers safe, transportation companies are leveraging the power of IoT, specifically IoT sensors, to gain access to powerful, insightful data about how their drivers are performing. For example, there are sensors available today that measure temperature and vibrations in the fabric of a driver unit to monitor for inflection points or changes in behavior. Using biomedical signals, managers can react in real time to coach drivers or notify them that it’s time to take a break. For drivers that are on the road for long periods of time, or have tight deadlines, this real-time data ensures they stay safe and alert on the road.

Inflection points like these can also monitor how an operator is driving. With access to Big data, managers can monitor for near accidents or frequent stops, and train their drivers to better maneuver their vehicle. Changes in behavior also provides managers with a snapshot into potential turnover. A usually routine driving pattern that turns into frequent stops or requests for time off could indicate that a driver is looking for a new job. To save manufactures and transportation service providers the cost of replacing and training a new driver, managers can act upon insights delivered by predictive analytics and take measure to retain drivers.  

The future of transportation

While big data and analytics have greatly improved how manufacturers stay efficient and safe, there is still room to grow. With an increasing shortage of truck drivers throughout the US, autonomous vehicles have the potential to fill the gap. Instead of losing time due to turnover or schedule changes, autonomous vehicles are a quick and easy substitute.

Using traffic-intelligence, an autonomous vehicle can automatically reroute itself to a route with the least congestion, adjust its speed based on traffic signals, and easily find a parking space based on its surroundings. Knowing time is money in transportation, an autonomous vehicle’s access to Big data provides alternative ways to save on travel time and gas.  

There is also potential to eliminate some transportation costs through 3D printing. Equipment manufacturers, for example, often must distribute spare parts around the world. Maintaining inventory close to the point of requirement is not always easy. Especially, if equipment, such as oil-field assets is moved periodically or hard to reach. With on-demand supply chain services, such as 3D printing, manufactures can supply some part faster and at a lower cost.

Transportation companies are constantly looking for ways to reduce costs, stay efficient and stay reliable all while maintaining a high level of customer satisfaction. To stay on course and compete in today’s digital market, transportation companies must continue to look ahead, adapt their business models or adopt new ones, and ultimately embrace the transformative capabilities of Big data for the industry.  

By Sachin Bapat, Industry Value Engineering Principal, SAP North America

 

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