A big challenge in the Fleet Management industry is ability to harness the power of “big data”. Due to the many devices and applications throughout the automotive supply and demand chain that generate real-time data, at different time intervals, the ability to distill this data into consumable and actionable information that provides insight into business activities, and enable time sensitive decisions, is difficult to achieve.
With the momentum of the “connected car”, extending to the “connected fleet”, constant streams of data are generated from the many activities and devices involved in managing successful fleet operations. This data needs to be captured and analyzed to increase efficiency and allow fleet professionals the ability to use data to maximize efficiency and/or drive cost savings. The velocity, volume, and frequency of fleet data capture will only increase as time goes on. It is important to understand how to leverage this resource effectively and to know when it is necessary to engage fleet management companies with strategic consulting services.
Fleet managers receive data constantly from many sources. The challenge lies in aggregating and simplifying the data to produce meaningful analyses. This is a result of the data being generated from many disconnected sources. This data is generated at different intervals, includes unique identifiers and code values specific to the device or application generating the data, and includes many different data formats.
The consolidation of data and the ability to transform it into meaningful and actionable “information” requires specialized skill sets that separate the elite analytical companies from the rest of the pack. For example, fleet managers must prepare analyses in support of fiscal decisions or policy revisions that will elicit meaningful actions taken in managing vehicle availability, compliance, total cost of ownership, fuel efficiency, sustainability, driver behavior, and in support of other functional and cross-functional areas. Traditionally, these analytics were difficult, if not impossible, to create due to the time it has taken to capture, cleanse, organize, link, and develop meaningful analyses from this disparate data.
To streamline the process, data needs to be architected, modeled, and organized at the enterprise level in order to provide a total view of fleet operations. Often, this can mean significant investments in Enterprise Data Warehouse (EDW), analytics, and reporting platforms, or by partnering with a fleet management company that offers these services and expertise.
Mastering “big data” is essential in gaining insights into business activities. These insights are important because they will ultimately lead to informed, data-driven decisions. Fleet professionals need quick access to accurate, reliable, secure, real-time information.
"To streamline the process, data needs to be architected, modeled, and organized at the enterprise level in order to provide a total view of fleet operations "
They must be able to obtain it anywhere, anytime, and on any device in order to make informed, time-sensitive decisions.
These insights are important because they will ultimately lead to informed, data-driven decisions. Fleet professionals need quick access to accurate, reliable, secure, real-time information. They must be able to obtain it anywhere, anytime, and on any device in order to make informed, time-sensitive decisions.
This is accomplished by defining an Information Strategy that consists of a realistic and achievable roadmap that includes building a scalable and secure data infrastructure:
• An EDW is a starting point to ensure the fleet decision maker can interact with all data in a timely fashion. An EDW also ensures that the data itself is up-to-date, clean, accurate, and that there is no overlap in information, reinforcing the “one version of the truth” philosophy. This singularity is essential in making informed decisions so the decision makers can rely on the data they are reviewing.
• Security is also paramount, because cyber crime is a real threat that continues to grow each day any major financial services company and retailer today can attest to this as the number of data breaches hit an all-time high, in 2014, and continues at a rapid pace. It is vital to find a trusted partner, whose EDW has securities in place to protect important data assets from subsequent liability and exposure.
Fortunately, fleets do not have to walk alone. Many of the major fleet management companies have invested heavily in their technology infrastructure. Also, fleet data exchange is a common practice among customers, manufactures, fuel, maintenance, accident management, compliance, and telematics companies.
Once big data is collected and stored in the EDW, the effective use of that data depends on the ability to take immediate action. The data should be actionable and easy to comprehend with little or no analysis, and since corporate cultures vary, some fleets may benefit from outside expertise that has analytical capabilities to help drive positive change.
It is essential that fleet data be consolidated and distilled into analytical views in order to proactively manage total cost of ownership. This can be a time-consuming process. Some fleet managers may have the capability and time to produce their own custom data interface. However, many managers can benefit from custom data dashboards and reports prepared by industry experts. These dashboards and reports enable the fleet manager to control such critical assets as drivers and vehicles, as well as fuel and maintenance spend. With correct reporting, key performance indicators such as miles per gallon (MPG), cost per mile (CPM) and total cost of ownership (TCO), can be monitored against industry bench marks to ensure effective action is taken.
In addition to the importance of monitoring real-time performance, many fleet professionals can benefit from access to experts in predictive analytics. These analysts are often found at strategic fleet management companies. Analytics professionals can assist a fleet in determining what the future may hold and how to best meet upcoming challenges. Fleet managers should select predictive analysts based on their ability to not only understand the big picture of data, but also to issue actionable recommendations that drive positive change based on experience. This experience, coupled with the right analytics, result in sound and actionable recommendations a fleet manager can put into practice.
Big data does not replace human judgment. Analytics-driven technology combined with personalized fleet management expertise leads to success in translating big data into actionable steps. These steps allow an organization to optimize fleet performance and meet organizational goals. Even highly experienced fleet managers can benefit from working with analysts from a strategic fleet management company to increase efficiency and take their fleet further.