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24 NOVEMBER 2016 | FUEL OIL NEWS | www.fueloilnews.com One of the biggest challenges facing fleet managers is how to specify work trucks that will help their operations increase output and pro- ductivity in spite of declining budgets and reduced resources. Since most vocational trucks are not mass-produced, fleet managers often have just one opportunity to design an efficient vehicle for their fleets' specific needs, or be plagued with an inefficient truck for several years. The days of figuring it out with Post-it notes and Excel spread- sheets are over. Businesses are moving on from what has worked in the past and are coming to rely on big data to make strategic deci- sions. Accurate, well-analyzed data can enable managers to make decisions based on real-world and real-time information. BASIC DATA, DETAILED DATA To begin, one must have a data source. For most managers, this will be the operation's fleet information system, which stores vehicle maintenance, repair and fuel consumption data. At this basic level, the fleet manager can start looking at repair trends, component failures and overall asset usage. Based on any trends identified in this data, the fleet manager can make some top-level design decisions for the fleet's next work truck. Fleet managers today have access to technology their prede- cessors could only dream of. Data loggers, telematics, onboard diagnostics and advanced vehicle locator (AVL) systems provide real-time operational information. These systems track vehicle speed, engine loads, engine RPMs, hard stops and rapid accelera- tions, fault codes, and much more. This technology has matured over the past several years, making it possible to access data almost seamlessly through a data link or radio integration system. With their vehicles' unique data, fleet managers can design work trucks specific to their operational requirements and environments. This data can also serve as a cost justification tool when matching the right technology to the right application. DRIVE AND DUTY CYCLES Understanding the difference between drive cycle and duty cycle is the first step in measuring how a fleet's vehicles operate. These terms are often used interchangeably; however, each is a different metric. A drive cycle measures and defines how a vehicle operates. It includes factors such as average speed; maximum speed; idle time; power export time; continuous running time per cycle A duty cycle defines how much a vehicle is used, including; hours of use per day; days of use per week; total miles driven per measure- ment cycle; percentage of on-road vs. off-road driving; loaded vs. empty usage Understanding drive and duty cycle data will provide fleet manag- ers the information they need to design appropriate work trucks. For example, an analysis might identify whether there would be sufficient return on investment for E-PTO worksite hybridization, or the use of other advanced/alternative technology. It's important to consider seasonal changes that may affect a fleet's drive and duty cycles, as well. TELEMATICS Telematics is often thought of as a GPS tracking system; however, when properly leveraged, it can be so much more. Information pro- vided from telematics can give fleet managers the tools to streamline many operations, including routine maintenance scheduling, real- time vehicle utilization and improved routing. Telematics can be used to increase the efficiency of fleet opera- tions through route optimization. Driving fewer miles burns less fuel, a savings that directly impacts the bottom line. In a delivery fleet application, inventory and weight management can be as simple as scanning a barcode while loading vehicles to avoid overloading trucks. In addition to these basic benefits, telematics also can provide information for long-term planning. By leveraging specific drive- and duty-cycle data, fleet managers can design vehicles that match their operational environment. For example, vehicle speed data can be used in determining whether increasing aerodynamic efficiency will provide sufficient return on investment. Improved aerody- namic designs can be an effective option for vehicles operating primarily at highway speeds, but if a fleet's data shows new vehicles will be operated at low speed a majority of the time, investing in aerodynamic designs for those applications may not provide suf- ficient benefit to justify the cost. PROCESS IMPROVEMENT Data also can be used as a process improvement tool. From the moment vehicles leave at the beginning of the day, they are almost entirely in the hands of the operator. It is commonly accepted that the way a driver operates a vehicle can impact overall costs. Drive cycle data gives fleet managers the ability to tailor custom train- ing programs and engage in driver behavior modification where needed. Sometimes just making drivers aware of the cause and effect of how they operate vehicles can be incentive enough for them to change bad habits. Other situations may require a more hands-on approach, such as real-time feedback or incentive programs. Driver behavior modification can produce viable benefits, including; reduced crash incidents; improved fuel economy; extended brake life; reduced engine and transmission wear Pairing these strategies with a data-driven vehicle design can compound a fleet's savings in acquisition and operating costs. One of the greatest benefits of data is that it does not lie. However, it's important to be aware of bad data. Incomplete or unreliable data can be the basis of undesirable and costly results. With all technology, the results can only be as good as the input data. Additionally, if data is not used, it becomes useless. For additional information on these issues and others facing fleet managers, attend The Work Truck Show 2017 and Green Truck Summit, March 14–17, at the Indiana Convention Center in Indianapolis, Ind. Sessions begin March 14, and the exhibit hall is open March 15–17. For more details about these events, visit worktruckshow.com. l F O N Christopher Lyon is director of fleet relations for NTEA. Editor's note: This article was supplied by NTEA, the Association for the Work Truck Industry. Leverage Big Data to Spec Work Trucks