For the Sake of Your Flatbed Fleet — Model as Often as Possible

Kevin Zweier and Phil Melton continue their conversation with a wide-ranging chat on the absolute necessity of frequent flatbed fleet modeling.

Specialized equipment needs complicate flatbed fleet management

These needs, and the availability of given sets of specific equipment required by your flatbed loads, lead to capacity challenges. So with capacity concerns arising around your loads, it wouldn’t be unusual for you to maintain access to private or dedicated fleets.

Because of these load-specific complications, no general strategy or “rule of thumb” will work as a good starting point for you to optimize your flatbed shipping. There are too many variables in addition to your business needs and trends in the common carrier market. For example, recent months have seen tight capacity and rising rates, making dedicated fleets increasingly attractive. Conversely, if common carrier markets are soft, capacity easy to find and prices low, you’ll want to re-evaluate and possibly reduce the size of your private or dedicated fleets in the near term.

How do shippers optimize their network and properly size a fleet?

A constructive answer to this complex question requires in-depth analysis and optimization modeling. Back-of-the-envelope calculations won’t be sufficient if you want to make sure you’re not paying for idle capacity or have products sitting on the dock for lack of space. You need to understand both pricing within the common carrier markets and the total costs of running your trucks — whether you’re doing it as a private fleet or a dedicated fleet. Once you’ve decided to employ dedicated capacity, you need to keep it running. Otherwise it’s no better than overpaying in the common carrier market if it’s just sitting around.

Effective modeling requires an accounting of all involved data points

A modeling exercise should utilize a robust environment that possesses the optimization capabilities and algorithms to evaluate numerous strategies. Additionally, you must replicate the decision-making capabilities built into a TMS engine where the process is ultimately executed. For example, modeling tools like MercuryGate’s Multimodal Optimization (MMO) consider all the different pricing structures you’ll need to evaluate (cost per mile, cost per load, cost per unit) and fixed and variable costs that can fluctuate daily, weekly or monthly.

Information regarding origin and destination factors, like how much time it takes to load and unload, must be accounted for. Such operating characteristics have a lot more variability in flatbed than what one sees in dry van.

Then there’s the question of when a truck can access a location. Delivering to a job site is very different from delivering to a distribution center that is open 24 hours a day. The model needs to understand the relationships between all those different data points to develop a sensible “what-if” scenario around how to utilize a fleet.

Modeling needs to be frequent to be effective

Fleet modeling isn’t something to be performed once or twice a decade. Nowadays, your business changes too frequently, the truckload market changes too frequently and your and your fleet provider’s networks change too frequently. Therefore, modeling needs to be part of your strategic planning process. NTT DATA has some clients that do it once a year. Still, a growing number are evaluating the use of their fleet every quarter or even every month, so they have standing models built to facilitate those more frequent analyses. To understand the impacts to service and cost — before you make changes — it’s crucial to map out how changes in your business affect the moves you’re considering, what kind of consolidation opportunities exist and whether you should be growing or shrinking your fleet. You can’t wait for three, four, five or however many years to do that. It’s something you need to be looking at, at an absolute minimum, at least every two years. However, in the best interests of your business, you should be modeling your fleet far more frequently.

— By Kevin Zweier and Phil Melton