Fleet optimization: one size does not fit all

By Kevin Price

Optimization: what does it mean for a fleet, and how can it be achieved?

Here’s one definition of optimization: “Finding an alternative with the most cost effective or highest achievable performance under the given constraints, by maximizing desired factors and minimizing undesired ones.”
That’s not exactly earth-shattering news, but still food for thought: have all constraints been taken into consideration? Have the desired outcomes been identified in detail? Which negative factors have the biggest impact on profitability?
For every fleet, optimization will mean something different. A big-city agency may be constrained by yard management issues—rows and rows of buses backed up in a crowded depot. A union shop must have technicians certified and available to work on the particular makes in the fleet. Regional topography and weather are huge considerations. A bus company in Canada needs to be especially cognizant of having the right gear on the right rig in the right season. A fleet near the ocean will be susceptible to saltwater corrosion and other effects. Start-and-stop traffic and mountainous roads will significantly impact fuel consumption and brake wear.
Not having enough data isn’t usually a problem; it’s more challenging to sift through all the data that is available to figure out what’s important to measure, and what matches an organization’s individual definitions of constraints, desirable outcomes, and undesirable factors. Warranty information is especially important so that both forced and voluntary recall work is done in a timely manner and the costs will be recouped from the manufacturer instead of diluting profitability.

Nearly all companies and agencies understand that having technicians enter information as they work is more efficient than entering it later. But the constraints around that practice are not always considered. Bus mechanics in the middle of a job, for instance, can have hands covered in grease, and stopping to enter data in the traditional way doesn’t work. Perhaps the method of entering it needs to be examined—such as offering a kiosk with pre-programmed options instead of a keyboard—or the data entry required needs to be reformatted as a checklist instead of a form.
Company culture is a compelling factor that is often overlooked as a constraint—in all industries. One oil and gas company identified what, on the surface, appeared to be a better way to collect data in real time: new hand-held devices for rig personnel. The devices needed to be rugged enough to be dropped on a steel platform, safe enough not to spark on that platform, and able to float. The company made a substantial investment—$15,000 per device—and yet nobody used them enough to justify the investment. The reason? The rig staff liked coming into the air-conditioned office to enter their inspection data. They didn’t want to be stuck on the hot platforms even longer by now having to enter data via field devices.
The point is that organizations need to identify their own personalized definitions of optimization, based on their own constraints—and then be able to measure the progress being made. The metrics tracked must also be customized, so that they show what an organization is doing, how well they are doing it, and how they can demonstrate that they are doing it well. While almost anything can be measured, that doesn’t necessarily mean it should be. The SMART method is one way of figuring out the usefulness of a metric:
• S – specific; clear and unambiguous
• M – measurable; able to be quantified against other data vs.
“yes/no” measurements
• A – attainable; reasonable under normal conditions
• R – realistic; fitting within an organization’s specific constraints
• T – timely; achievable within the given timeframe
An enterprise asset management (EAM) system can help fleet managers optimize according to their defined constraints and metrics. Knowing the asset’s history when scheduling maintenance or repair is invaluable: when the asset last ran, where it was running, what is needed now, who is needed to address it (taking into account union status, certifications and availability), and what materials are needed for the job (Refrigerant? Tires? Core work?)
A system should be able to schedule in increments of one minute for the greatest efficiency. It should facilitate better yard management through spatial capabilities that help determine which vehicles should be parked closest to or furthest from the exit, depending on recent repair issues or upcoming maintenance. It should generate campaign slips after a warranty review that can be sent to the manufacturer for reimbursement—and it should incorporate VMRS (Vehicle Maintenance Reporting Standards) numbers so the fleet organization and the manufacturer are speaking the same language.
Finally, a solution should be mobile, light, capable of being deployed in the field without requiring extensive data entry—allowing technicians to record as they work, saving up to 45 minutes per technician per day in the process—and flexible enough to work within the constraints of each individual organization.
Optimization is a worthy goal—but only worth embarking on once it has been clearly defined and constraints have been identified, with a solution for addressing them.

Kevin Price has more than 17 years in Infor’s asset management business, holding roles in sales and service, as asset solutions director for the Infor Public Sector group, and now product director for Infor EAM, MP2, Spear Technologies, and Infor Energy Performance Management. He is based in Greenville, SC. Kevin welcomes your feedback and questions. Please don’t hesitate to email him at kevin.price@infor.com