Opinion: What to Consider When Optimizing Routes

By Ken Weinberg

Vice President and Co-Founder

Carrier Logistics Inc.

Smart transportation companies, especially multistop carriers, are paying close attention to routing. They feel the improved productivity and efficiency with less backtracking that routing brings, as well as the more effective use of drivers — important in a time of driver shortages and stricter hours-of-service regulations — are crucial in today’s environment.

There was a time when freight carriers would have called in a phalanx of industrial engineers to help improve routing. The industrial engineers would have studied all the variables — driver shifts, traffic patterns, existing routes, frequency of pickups and deliveries at regular locations, etc. — and come up with an “optimum” plan for routing trucks throughout the day, throughout the week, throughout the month.

In the regulated environment that existed through the 1970s, carriers focused on efficiency and productivity because they could not compete on price and were restricted to where they could go. However, when the 1980s arrived and deregulation kicked in, truckers turned to price and expansion into new lanes as primary competitive tactics to win business, with many shifting their focus away from efficiency and productivity.

Carriers learned how to compete in a deregulated world, and many began again to look beyond rates and expansion. Then, a burst of new technological developments and a reduction in technology’s cost provided new options.

Many carriers invested in technology to streamline or “optimize” operations — routing, for example. Trucking companies today are making big optimization efforts in search of such benefits as lower costs, fuel savings, improved loading efficiency, more stops per day, and pickup and delivery of more bills of lading.

There is a danger to this. Trucking companies have discovered that optimization is more than just pushing a button on a computer. Achieving it can be more difficult and expensive than expected because of driver shifts, traffic jams, accidents and optimization expenses, leaving those handling computer programming frustrated. The variables may be too great in a multistop environment to achieve the level of optimization being sought.

Carriers trying to optimize routing can get blocked and not see a way to continue. They end up doing nothing and thus fail to achieve routing goals. While optimization — the industry calls it “dynamic” optimization because it takes place over time — should always be the goal, it can prove difficult to achieve.

There is a way around possible failure to optimize — by using “empirical optimization.” If you consider dynamic optimization as near perfection, empirical optimization will take you to somewhere near it, but not quite get you there.

Technically speaking, “empirical optimization” consists of making a system as fully perfect, functional or effective as possible based on observations and evidence accumulated over time: in other words, step-by-step improvements. It takes you to the place the industrial engineers would take you — when dynamic optimization is too difficult or too expensive to achieve, empirical optimization can be the way to get the best and highest routing results.

Some trucking companies have spent big bucks on systems to optimize their routing. These are good systems, but a great many of the companies that invest in them fail to realize one thing: It still takes work to optimize.

Moreover, even if you are tremendously diligent and do all the hard work, optimization still can be less than perfect if you factor in the human variable.

Let’s say you have a driver who has been making regular stops at XYZ Distribution Center. He has a good relationship with everybody at the location. They know him, and he knows his way around their facility, knows the shipping manager, knows everyone, knows what time to show up. But dynamic optimization may dictate that a different driver should make this stop.

With today’s heightened security concerns, sending different drivers to a single location on various days may be counterproductive.

Furthermore, personal elements and relationships can be lost in an optimization process that cares more about numbers than people.

To those who try to get routing on track, here is what I suggest: Jump right in with both feet and try to optimize routing. But if you cannot achieve dynamic optimization immediately, go one step lower on your target and try for “empirical optimization.” This way, the stall is not permanent.

After you have achieved empirical optimization, take another look. At this point, it is up to you. Is your routing now achieving what you want to accomplish? If so, perhaps you should stick with empirical optimization and avoid the expense and hard work to achieve dynamic optimization. It may be best for you to work on achieving other goals for your organization rather than trying to get from empirical optimization to dynamic optimization of routing.

However, if you have the desire and resources to continue to enhance the process, then by all means, set your sights on the dynamic optimization of your routing. This will take time and work, but an increase in efficiency is always an improvement.

The bottom line is this: Never give in to the temptation to do nothing. You can do something, even if it is one or a few small steps, to improve routing. Small steps can have big effects. And using what you have learned about optimization, you can go on to other functions of your business and improve them, as well.

Carrier Logistics Inc. is based in Tarrytown, New York, and is a transportation systems and engineering consulting company that develops technology systems for the trucking industry.