The COVID-19 pandemic has sent shock waves across world, forcing leaders to develop short-term survival tactics, revisit existing operating models, and envision how they will deal with future pandemics.

Today, the transportation and logistics industry, like other industries across the globe, is already suffering as it tries to optimize measures designed to raise revenue, reduce costs, and enhance the customer experience. The advent of COVID-19 has just exacerbated the industry’s existing list of challenges. The trucking world, which depends heavily on big data, has been severely impacted by the effects of pandemic-driven social distancing and lockdowns in the major economies.

Why Revisit Current Models?

Big Data plays a critical role in the trucking industry. Factors such as verbal and non-verbal modes of communication, including sensors, mobiles, web sites, emails, and system applications are important inputs. Thanks to disruptors like the Internet of Things (IoT), Robotic Process Automation (RPA), Block-chain, and digitalization, data from these sources can be transformed easily into analytic models for effective operations.


Looking at the expanse of the trucking industry, one can easily see that this is an enormous amount of information to digest. With the virtual lockdown of large economies around the world, COVID-19 has changed the entire structure and respective volume of data. Models that were built on historical big data to reveal patterns and make predictions may prove inadequate for dealing with the current situation in the industry. Hence, it is imperative to look at scenarios built on data from the situation at hand to avoid misleading or incorrect insights.

How is COVID-19 Creating New Data?

Optimal Routing- To make overall operations cost efficient, it is imperative to have optimized routing for the movement of vehicles. With the magnitude that sensors and mobile phones are creating today, the application of Intelligent Transport System (ITS) is more viable. Data from these technologies shows the most cost effective route for the shipment. Routes can be Static, Dynamic, or Real-Time Dynamic, depending on an organization’s needs.

Lockdowns caused by the COVID-19 crisis have resulted in sealed borders and roads, changing routing data. Organizations have to be cautious when using data analysis from the pre-COVID-19 period; they need to ensure that their big data analytics model has been updated from Static or Dynamic to Real-Time Dynamic routing to provide optimized routes for delivering shipments to customers.

Route Optimisation through ITS

Proof of Delivery- Signing off the POD document by the customer on the driver’s device is a critical step to ensure that the goods have been delivered safely to the right party. But in today’s COVID-19 era, in order to maintain social distancing, the sign-off can be taken through a picture of the customer standing beside the goods delivered. This leads to a change in the type of data used for analysis. The analytic model will have to be updated with the new input: picture instead of sign-off.

Proof of Delivery

Blockchain- COVID-19 has made it all the more critical for trucking organizations to invest in maintaining the influx of big data captured through various sources of IOTs, applications, sensors, and tools that generate end-to-end transparency of deliveries and provide real-time visibility into any interruptions. The Blockchain model not only provides visibility but also leads to a more automated and digitized process with less human interaction. Also, cloud modelling would help access an entire shipment journey remotely, by different functional stakeholders. This kind of model would be effective now and during any future, unforeseen challenges.

Drivers and Vehicles Performance Data- Many trucking organizations use sensors and advancements like Electronic Logging Device (ELD) that are aligned with the vehicle to keep track of the driver’s actions, data which can be gathered and analyzed for new insights. These data points help capture an accurate record of duty status (RODS) and hours of service (HOS).

Organizations would see changes in data on the performance of drivers and vehicles during this COVID-19 period due to truck drivers having their driving hours extended either by government -- for example, changing guidelines by the United States Department of Transportation -- or increases in home delivery shipments driven by lockdowns and social distancing. These extended hours would lead to extra performance pressure on both the driver and the vehicle.


Drivers and Vehicles Performance Data

Real-time analysis of data generated from sensors or tools would help the operations manager keep track of the drivers’ login hours, breaks, and vehicle speed to avoid exhaustion and potential accidents, meet regulatory guidelines, and help in preventive maintenance of the vehicle. Hence, it would be wise to ensure that current analytic models reflect these changes and make adjustments, and, if required, provide accurate insights for action.

Operational Data- The current COVID-19 crisis is no doubt resulting in changes for the entire Transportation and Logistics industry. The pandemic has led to an increase in the overall demand for e-commerce. Consumers ordering faster delivery of goods may be the new norm for the trucking industry. Hence, operational data during and post this crisis is expected to change with regard to increase in volume, type of goods delivered, new customer base, and uncharted areas for delivery.

All these data set changes would generate new insights and may call for new strategic changes in operations. In order to forecast and build strategies, organizations may have to create new data models that segregate data preand post-COVID-19.

Last Mile Delivery (LMD) Data- Trucking companies dealing in LMD rely too much on big data to forecast such volumes and ensure efficient delivery of shipments. The consumer shift to e-commerce has resulted a in a surge in LMD volumes, creating a significant change in the data pertaining to volume and product type, as well as areas never explored from the delivery perspective. The volume is such that it has put extra strain on organizations and they are facing challenges meeting this requirement.

It is critical to use the current data intelligently for forecasting or capacity planning for the near future. However, in the longer term, this trend could be the new norm and hence, organizations may need to start thinking about new operating models, like partnering with other logistics companies to consolidate shipments. Autonomous Vehicles could also be a solution in the longer run. But, both these potential solutions would require extensive big data and analytics to make them successful.

Credit Assessment of Shippers– In addition to the data from credit- bureau and credit ratings, Transportation and Logistics companies may be using big data solutions to analyze data from shipping patterns, mobile records, granular customer payment and spending behavior, to help them in credit offering decision making.

Operational Data

COVID-19 lockdown and banks offering moratorium facility, have significantly impacted customers buying and payment patterns. It is imperative to revisit or edit the existing credit risk models to gauge the actual credit worthiness of the customers.

What Does Success Look Like?

Crises like COVD-19 require the leadership teams of the dynamic trucking industry to be more proactive than reactive. It is important for them to not only understand the enormous impact this pandemic is having on operations but also prepare themselves for the post-COVID-19 era. In order to identify the big data analytic models that have been impacted, organizations must review their business end-to-end, identify impacted technologies using big data, re-model their analysis, and revisit their vision to ensure success amid disruption.


Next Steps

The COVID-19 crisis has come as a test in many ways. It will bring changes in the way we run our businesses and societies. It is likely to bring an enormous surge in e-commerce and other online businesses and professions. Trucking companies have been continuously seeking ways to reduce cost, optimize operations, and enhance the customer experience.

In order to be competitive in today’s digital world, it is imperative to not only embrace but also revisit regularly big data technologies and analytic models. With the current pandemic effects of social distancing and lockdowns, companies relying on big data for meaningful insights must adapt to changes in the data the crisis has created. The following focused areas offer a way forward for trucking organizations.

Next Steps

The impact of this pandemic is going to be with us for some time, but today is the time for introspection and reevaluation in the trucking industry. We must assess our needs and gather useful information. Updated historical data, along with data capturing current trends, will provide new insights for operations. Also, there is no better time than now to start collating lessons and strategizing for the future crises to come.


Nitin Sharma
Manager, Process Excellence



Ganapathy Subramanian
Vice President, Finance Transformation

Deepti Sanyal
AVP, Account Management

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