Managing your fleet requires a lot of important decision-making, from acquiring the right vehicles to replacing them at the right time, plus countless decisions in between. Unfortunately, the wrong decisions can cost your company excess time and money. So how do you ensure you're making the right ones? No, it's not a crystal ball. It's the next best thing—predictive analytics.
Predictive analytics can help you select the right vehicle specifications and models, reduce maintenance costs, and help you identify the optimal time to retire each vehicle. Additionally, predictive analytics can improve driver safety and satisfaction. To further explore the power of predictive analytics, we sat down for a Q&A session with Joe Voors, a national Client Partnership Manager at Mike Albert Fleet Solutions. He and his colleagues have helped a variety of clients in various industries use predictive analytics to significantly lower their expenses and operate more efficiently.
First off, how does predictive analytics help control maintenance expenses?
Consider this common scenario: one of your vehicles is en route to a service call when, suddenly, it blows a gasket leaving it—and your driver—on the side of a highway. Not only do you have an annoyed customer who now must wait longer than anticipated, but more importantly, your employee is at an increased safety risk. And you’ve likely lost income too.
Predictive analytics, in the form of anticipatory maintenance and breakdown planning, could have prevented this situation. That’s because predictive fleet maintenance relies on usage histories, vehicle part life cycles, and other methods to identify when specific components are at risk of failure. These parts can then be proactively fixed or replaced when other routine maintenance is scheduled.
How is it predicted when non-routine maintenance is needed to prevent a mechanical failure?
Financial planners are fond of saying past performance is not indicative of future results. But that’s not so when it comes to fleets. Past vehicle performance and established driving patterns can be quite revealing when predicting future performance.
For instance, Albert IQ, Mike Albert’s proprietary vehicle and driver monitoring solution, combines fleet telematics with the expertise of the ASE-certified technicians on our maintenance team. It detects problems well beyond what the warning lights on a dashboard reveal.
With Albert IQ, dozens of diagnostic trouble codes (DTCs) are collected from each vehicle, interpreted, and cross-referenced with data on multiple systems within the vehicle. Then, all necessary maintenance is prioritized in order of urgency. This alerts fleet admins and drivers to any issue that needs immediate attention before it creates costly problems for your company and inconveniences your customers.
In addition, Albert IQ can do some anomaly detection and identify those drivers or vehicles that are out of compliance with established tolerances. This is key to predicting high-risk factors and correcting them before they become a driver safety issue or, worse, an accident that puts the company at risk. In short, predictive analytics, like Albert IQ, can help you dial in on pending trouble spots before they wreak havoc.
Can’t the sheer volume of all this data become overwhelming?
Sure, it can, but it absolutely need not. We mine the data, and when a problem is identified, real-time alerts go directly to our ASE-certified techs for further analysis. For example, with Albert IQ, our team then codes these issues according to their severity as green, yellow, or red.
Fleet admins need not get overwhelmed by the data. It’s the findings and trends that the analysis reveals that are most critical and helpful.
Predictive analytics can help improve driver safety, right?
Absolutely. For one, it can help identify high-risk drivers. We run motor vehicle record (MVR) reports identifying drivers with problematic driving histories, such as a recent DUI or a revoked license.
Beyond that, predictive analytics significantly reduce major issues that send vehicles to the side of the road or that lead to accidents. Remember, it’s just not a matter of the repair cost and the vehicle’s downtime, but also increases in insurance premiums and the potential of high-cost litigation.
How can predictive analytics help determine when it’s best to retire a vehicle?
Predictive analytics can look back through time, examine current driving patterns, and then extrapolate what the picture will likely look like moving forward. In so doing, we can predict when a vehicle will reach its retirement criteria. Furthermore, this data can help us identify the most appropriate new vehicle to acquire. The key here is being proactive; while a vehicle may not be ready for replacement for another six to 12 months, the planning for it should begin now to ensure optimal resale and acquisition terms.
Regarding the decision when to replace a vehicle, it’s not just a matter of what condition a particular vehicle is in, but also looking at it from a total cost of ownership perspective. It may appear that a vehicle has another, say, 30,000 miles in its life cycle, but the data may show that when you factor in another set of tires or the best time to approach the used vehicle marketplace, it would be better to get out three months earlier than initially planned.
Can predictive analytics help with fleet budgeting?
Yes. For many companies, fleets can be a top-five expense. We’re talking significant numbers. By tapping into past data and projecting forward, we can paint a pretty accurate picture of your costs to come. For example, we can fine-tune the data to reflect an anticipated increase in driver mileage or rising prices for raw materials, certain vehicle parts, and fuel. Our clients have found this tremendously helpful when sharing—and defending—a budget forecast.
Speaking of budgets, how much can predictive analytics save a company?
It depends on the fleet size and to what extent some fleet analytics are already in play. But the savings can easily reach six figures and sometimes multiple times over—and that’s after factoring in the cost of predictive analytics services.
What do you say to those who claim “going with their gut” works fine for them?
I realize that some fleet owners feel they know their business best and that a more instinctive approach has worked well for them. My experience tells me that, in those situations, if they had acquired the right data to examine, they could have identified ways to decrease downtime, reduce maintenance costs, and exit vehicles at more opportune times.
Have you and the Mike Albert team been successful at changing this mindset?
Yes, we have. And it isn’t hard since we have the powerful duo of data mining and analysis to illustrate our case. Plus, we ask some probing questions that get to the heart of the matter: What if we could help you do a couple more jobs per week by not having vehicles out of commission? What if we could help you improve driver safety and satisfaction during this time when recruiting and retaining qualified people is a huge challenge? And, finally, wouldn't your time be better spent managing your business expenses or growing your business?
Did you enjoy this class?
Share it with your organization and colleagues.