Plan Better Truck Routes: Long-range Itinerary Generation Enhances Operations

Not so long ago, route planning, fleet optimization, and driver allocation relied almost exclusively on the guile, instincts, and experience of operations managers and dispatch personnel. Long-range forecasting was theoretical at best. The tools used static data, and couldn’t handle the inevitable adjustments required by the dynamics of day-to-day operations. This is changing fast. While operations and dispatch personnel’s skill and knowledge will always be vital, the tools available today—long-range trend analysis and planning—make for better, faster, more cost-effective decision-making. This is changing the competitive landscape.

Dealing with Realities of the Road

Data is helpful only if it’s usable to make better decisions. The challenge all logistics companies have historically faced is the relevance of long-range trend data to short-term operational decision-making. With the tremendous evolution in analytical tools and ability to integrate decision rules and processes into tool sets, the foundation to create far more meaningful links between long-range planning and real-world agility is changing the paradigm.

Solving the Problem

HP was asked to look at ways to build route plans that would more efficiently use driving resources within a very large service area. There were a number of required business rules, including company and DOT driving constraints. It was very clear from the beginning that longer planning, using seasonal, volume, and trend analytics coupled with real-time data captured from multiple sources—sales, operations, maintenance, weather forecast, and road conditions—could satisfy the demand for capacity. And direct cost and resources needed to meet those demands could be optimized.

Like most logistics issues, the problem has three dimensions:

  1. Who—or a combination of several who’s in the case of team loads or tag, relay loads—should carry a given load?
  2. What order should they schedule loads?
  3. When—in this case—is the optimal sequence of geography, load balancing, customer delivery, and pickup windows?

To meet this challenge, alternative itineraries and resource maps were generated for each driver or load, derived through a rules-based decision support engine—and the optimal one was selected for each.

Gaining Ground with Long-range Planning

What are the benefits of looking farther ahead during the planning cycle? First, transportation companies can improve the ratio of revenue to empty miles. Expected savings from better routing will vary—depending on the firm’s business practices. But reasonably, they can be expected to range from two percent to 10 percent of total miles driven. For a 500-truck fleet, 2,500 miles per truck per week and $1 operating cost per mile translate into $1.3 million to $6.5 million in annual savings. This does not include the extra capacity now available because empty miles are not being driven.

Second, one surprising result was observed when implementing the long-range planning system: an increase in backhaul activity. The increase occurred because fleets got the right truck to the backhaul origin as a result of the increased visibility that long-range planning provides.

Long-range planning systems also make allocating and dispatching personnel more productive. While certain aspects of the driver-dispatcher relationship will not change, fewer dispatchers can support a larger number of drivers. Operators can move to a management-by-exception mode, with some assignments automatically accepted and forwarded to the driver for execution.

Increased driver satisfaction is another benefit. Some operations have trouble attracting and retaining drivers. Increasing driver pay is usually not an option, and the cost of finding and hiring drivers is high. Long-range planning allows drivers to be home when promised, increasing driver satisfaction and retention rates.

Total savings from these measures can be considerable. And additional savings can be realized by handling some loads on contracted or private fleet capacity, rather than a short-term, spot basis. Long-term traffic lanes, currently handled by outside carriers, can be assigned to in-house resources.

Drive Home Operational Efficiency

Investing in a rules-based, analytics decision-making engine that links long-range planning with the need for short-term agility is a compelling proposition. It holds the promise of better managing assets, preserving capital, and increasing driver retention and customer satisfaction, which all drive better margins and operational efficiency.

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