Many of us understand that the trucking industry and trucking companies are changing at a rapid pace, and that is significantly impacted by the increased adaptation of technology. Trucking used to be considered an “old-fashioned” industry, but those days are long gone. The advances brought by technology are not a pipe dream.
With all this additional technology comes a plethora of data that is gathered – how do motor carriers organize and use that data to their advantage? We have got the answers! In this two-part blog series, we are going to take a deep dive into the following topics:
- How does blockchain influence trucking?
- How can fleets better utilize data?
- What is the timeline for fleets to implement data gathering?
- How can fleets implement data gathering and analysis?
We want to provide you with information on how fleets can leverage data to improve both the measurable and intangible aspects of managing a commercial fleet. It used to be that not every motor carrier was either capable or in possession of the resources necessary to use big data to their advantage. But those days have changed.
As costs have come down and technology scales, it is easier than ever before for fleets large or small to generate results from the data they gather. Even single owner-operator businesses can access cloud-based software systems for a fraction of the price they used to be offered for.
Yet, the anxiety often doesn’t come from a price perspective, it comes from a use perspective. Many trucking companies are more concerned if there will be problems with adoption or truck driver buy-in. What happens when there is an information overload?
How to Manage the Information Overload
We can help you manage the information overload. We will cover the following topics as we dissect this incredibly complex subject:
- Information Overload
- Leveraging Data
- Cost Control
- Safety
- Maintenance
- Data and Blockchain
- Interpreting and Implementing Data
- Setting and Monitoring Benchmarks
- Data Management
“Data” was one of the most popular buzzwords in almost every industry in 2018. While data is already enabling meaningful progress in trucking and beyond, it is important to remember that data on its own means very little. Data points are bits of information, not self-contained (or even visible) solutions. It takes data analysis, software, data-focused people, and a strategic approach to turn data points into improved fleet operations.
Far too many trucking companies assume that raw data by itself will solve all problems. Unfortunately, improperly managed data can actually do the opposite, wreaking havoc on operations and decreasing overall efficiency. The problem is magnified in today’s hyper-complex truck manufacturing environment.
Modern trucks and equipment are chock full of sensors and connectivity. Data science is advancing at break-neck pace. So why are many fleets slow to implement data-driven solutions? A single fleet can produce billions of data points throughout the year, which can be disorienting for fleet managers lacking a plan for data management.
The task for trucking companies now is now to put systems in place that not only collect data, but who are able to analyze the data points and put them to use. The industry focus has shifted from capturing billions of data points to helping improve fleet decision-making. For fleets, this means not just getting data, but determining actionable items from new big-data technologies.
Fortunately, plenty of companies have stepped into the void. Third-party vendor companies of all stripes and sizes offer customizable software solutions to help trucking companies parse the data and make better informed operating decisions.
How to Best Leverage the Data
In his white paper “Make Global Supply Chains More Effective with Internet of Things,” Dr. Shardul Phadnis divides the implications of IoT data into three broad categories.
- The first is information gathering: sensors will provide exponentially higher amounts of data, and more types of data, from a variety of sources.
- The second category is information sharing: non-serial data will be shared through Wi-Fi and cellular networks, instantly, without distortion or manipulation.
- The third implication of IoT data discussed by Dr. Phadnis is decision making. Decision makers will be able to leverage automatically generated data sets, algorithmic processes, and predictive models to make better operating decisions, the results of which will generate further data, which can be closely monitored to assess outcomes. This sort of feedback-based process opens the door for constant adaptation and optimization of the process being monitored.
As sensors have proliferated, so have AI systems, APIs, and other advanced interfaces to monitor and process outcomes. And even better, the systems are easier to use and more user friendly than ever before.
Data can be used to monitor many areas of a truck for maximum efficiency and cost savings. For example, Bridgestone offers the MEMS Evolution, a data-driven system that monitors the tire pressure in Earthmover tires, records temperature, and pressure conditions in real time, and sends alerts when pressure or temperature reach problematic levels.
While this technology is specifically designed for mining fleets, similar technologies have the capacity to soon be rolled out across the entire commercial trucking industry. For example, similar monitoring sensors are already being applied to a range of truck parts to monitor wear and performance. And you don’t need to have an advanced technical background to use the sensors and monitor the data.
Another area where data can help control costs is the current parking crisis, previously mentioned in the ELD mandates. Data can help to streamline parking and control costs through updated apps and websites. MAASTO (an interstate transportation association that includes Illinois, Indiana, Iowa, Kansas, Kentucky, Michigan, Minnesota, Missouri, Ohio, and Wisconsin) has now rolled out a data-driven parking solution among member states. It monitors more than 150 parking areas, relaying free information on parking availability to truckers via road signs, smartphone apps, and websites. That is a significant improvement over driving to each parking area to check.
While traffic congestion and equipment longevity can be accurately tracked to mitigate costs, one more temperamental factor affecting the commercial trucking industry is slightly more elusive: the weather. Currently, inclement weather costs US fleets nearly $9 billion per year. That is no small amount of money directly attributed to mother nature.
There are a number of data-driven offerings that help truckers plan for or avoid challenging weather conditions. If this sounds a bit like an overhyped weather forecast, it is not. Real-time weather data can be gathered from individual roadways and factored into existing weather forecasts. When you are running long-haul routes across the country, this kind of data can be critical to keeping you on time.
These insights can be combined with up-to-the-minute data about traffic, accidents, and road closures, and can serve alternative, time-saving routes to the driver’s GPS—a massive upgrade over a color-coded radar map. Moving forward, it’s likely that road-specific data will be gathered from every truck on the road—similar to current practices in aviation—to allow even more accurate forecasting across the industry.
Creating a Better Safety Environment
The efficient use of data can also make commercial transportation safer. Fleet managers can monitor a driver’s average or maximum speeds and take corrective action as needed. Truck drivers can receive alerts when they’re heading into heavy congestion—a big contributor to accidents—and reroute accordingly. Data reveals which drivers show consistently high speeds, heavy braking, or frequent lane departure engagements, allowing fleets to retrain drivers and incentivize safer habits.
Consider that there are also real intangible benefits to data gathering.
- Find correlations between weather and road safety
- Gather insights into truck driver behavior
- Generate time savings with clear route predictions
In 2018, the US Department of Transportation announced that it would be experimenting with all three of these ways to use data to improve safety, launching two research projects. The first tracked the speed of anonymous trucks and see how closely speeds and road conditions correlate to accidents. The second experiment used Waze, a crowd-sourced traffic and navigation app, in hopes of assessing the risk of crashes based on the reported hazards from Waze users.
Both studies revealed that trucking companies can take an active role in improving their safety profile by incorporating traffic apps, weather monitoring systems, route management software, and much more. By adopting advanced technologies, fleets saw their overall level of safety go up.
So, what is next for a trucking company who wants to find the best way to use data to their advantage? In Part II of our series, we are going to discuss maintenance and blockchain. Join us!