7 MISTAKES TO AVOID WHILE PERFORMING ROUTE OPTIMIZATION
Below, I am stating seven important mistakes that we frequently encounter while performing route optimization and that must definitely be avoided.
1. SETTING UNREALISTIC DELIVERY TIMES
One of the very most common mistakes made in route planning is defining delivery or visit durations without considering the actual conditions in the field. Theoretical distances on the map often do not reflect factors such as traffic congestion, road works, weather conditions, vehicle capacity, and the accessibility of the customer address.
This situation leads to both delays and an excessive workload for the personnel. It must be ensured that the durations used in this planning are updated with actual field data and even differentiated periodically as weekday/weekend or morning/evening. When sudden changes in traffic and weather are not taken into account, delays and fuel waste occur. Variables such as traffic, weather, and road conditions are not accounted for. The effect has led to delays and a decrease in customer satisfaction. The solution is that live traffic and dynamic route updates must be continuously maintained.
2. IGNORING THE CHARACTERISTICS OF VEHICLES AND DRIVERS
Every car may have differences in fuel consumption, carrying capacity, maneuverability, and speed limits. At the same time, drivers differ from one another in terms of regional knowledge, experience levels, and working hours. If these differences are not taken into account, route planning becomes both inefficient and, most of the time, unworkable in the field.
For example, directing a large vehicle into narrow streets or assigning a complex region to a new driver can put the operation in a difficult position. Therefore, when planning is done, the vehicle and driver profiles must definitely be entered into the system.
3. PLANNING LOAD DISTRIBUTION BASED ONLY ON DISTANCE
Some business owners create their routes based only on the shortest distance due to cost concerns. In reality, when criteria such as the type of product carried (e.g., fragile material, a product requiring a cold chain, or hazardous substances), loading and unloading times, delivery priority, and layout criteria like the warehouse are not taken into account, serious inefficiency arises.
4. NOT CALCULATING VEHICLE CAPACITY ACCURATELY
Every vehicle has specific limits in terms of weight, volume, and product type. Errors are made when assuming all products will fit in the vehicle or when calculating capacity manually, even if just a little, during busy periods. The reason this is critical is that the need for additional trips arises. Vehicles consume more fuel and, at the same time, experience wear and tear.
The damage rate of products also increases. Overloading creates a legal risk. Volume and weight constraints have not been considered. For example, a furniture distribution company planned 13 deliveries for one vehicle without taking the dimensions of large-volume products into account. Since half of the products did not fit, a second shipment is made; in other words, the cost doubles. If one is solution-oriented, the values for size, weight, and stackability features must be entered correctly into the system. Using 3D loading simulation in route optimization is an ideal thing. If vehicle volumes and weight constraints are ignored, the failure of products to fit, along with additional trips and cost increases, becomes a problem.
5. DISREGARDING DRIVER CONSTRAINTS
Every driver’s working hours, speed habits, experience, regional mastery, and breaks are different. While a uniform route is planned by assuming all drivers will perform the same way. One reason it is critical is that overtime costs increase. At the same time, a disconnect occurs between the automatic route plan and field realities. Another reason it is critical is that occupational safety risks increase significantly.
For a newly hired driver who is not familiar with the city center, a route that should normally be completed in 7 hours ends in at least 10 hours. Because the planning team does not take this difference into account, deliveries the next day are also disrupted. As a solution, driver profiles should be recorded in the system. As search managers, break times, working hour limits, and driving behaviors should be taken into account. The problem is that not all drivers have the same speed and experience. For drivers to be like this, it becomes easier for them to learn the route through practice.
6. FOCUSING ON A SINGLE METRIC
It is only distance and only time. Since route optimization is multivariable, sticking to a single duration lowers the quality of the decision. The margin of error is making plans focused only on the shortest distance or the shortest time. Why is it critical? Focusing only on distance leads to customer time windows being violated. Focusing only on time leads to ignoring vehicle capacity. Fuel consumption may be increased for the fastest route. In the shortest route, there may be traffic congestion.
For example, the shortest distance filter can be selected in a cargo company’s system. Because the navigation directs the driver to narrow streets, deliveries are delayed and the vehicle becomes stuck. If one is solution-oriented, multi-criteria optimization should be used; meaning, prevention is achieved in terms of driver profile, customer time window, fuel, time, and distance. A multivariable structure is calculated as one.
7. DATA POLLUTION
At the very foundation of route planning lies accurate data. That is, wrong data means a wrong route. As a mistake, incorrect customer addresses, outdated delivery times, missing stock or order information, and wrong coordinates are errors. The reason it is critical is that the operation requires manual intervention at every update. Deliveries are forced to be delayed or are canceled. The route software cannot produce a correct decision.
Wrong data in route planning is a very troublesome business; data must always be new and fresh. For example, a technical service company has old neighborhood numbers in its customer address list. If the field team is constantly directed to the wrong location, the average time per wrong job increases much more. Thinking solution-oriented, address verification and automatic geocoding tools should be used, and regular data cleaning should be performed. Route software must be constantly integrated.
Even though many businesses use route optimization systems, they still make their decisions based on manual experience. Performance reports should be analyzed regularly, and at the same time, the corporate culture should be directed toward data-driven decision-making. In route planning, if done correctly, the efficiency of operations can increase by 30-40%. However, making the mistakes listed above during this period causes even the most advanced software to become ineffective. The use of real-time data, focused on the correct processing of driver and customer constraints, capacity management, and a data-driven decision-making culture, forms the most fundamental goal of a sustainable optimization.
