Many small business owners think of a route planning software in terms of Google maps and similar applications – you input your destination, and then google tells you how to drive there in the fastest way. While useful, route planning software serves much broader needs of companies with delivery or field service operations. Let us first define route planning and figure out what main functionality a route planning software should have.
Route planning for organized delivery or field service operations is different than common application-based planning. Companies engaging in route planning often utilize a fleet of trucks and other transport options. Additionally, they need to plan multiple stops. There are generally a large number of orders to deliver or tasks to implement during the day. There is also either a maximum duration or a specific time window during the day when the order should be delivered or implemented. Hence, the company’s planner should figure out what stops different units should make to get deliveries done on time. It can quickly become a daunting task. The number of deliveries and the fleet required for their delivery grows after a critical mass of orders. This point is often reached when human cognition is outpaced by the complexity of large combinations of routes, orders, and time constraints. At this point, companies begin to increasingly miss delivery windows, mismanage capacity and incur increased transportation costs all while expanding working hours and increasing the stress and anxiety of planners.
Let’s see why this is happening and how well-designed routing software can help to solve all the mentioned problems.
As you may have noticed, several variables make the planning process complicated. The main problems are issues with;
- delivery models
- delivery frequencies
- delivery variables
Route planning software and route planning methodology can be radically different when one plans deliveries from a single location (a distribution center, a warehouse, a store, or a restaurant) vs. multiple locations. In academic literature, these are usually described as depot-based routing and pick up and delivery routing.
Their underlying logic can be quite different, so one should understand what operations the specific software or routing algorithms are built for. Many routing software systems might also try to optimize (minimize) either a driving time or the plan’s mileage. However, there might be other goals, such as the balancing of stops, route durations, or the number of orders between drivers. Thus, the business should also understand driver-specific, or other real-life, needs.
All delivery/distribution operations may be divided into three parts when considering delivery frequency:
- dynamic deliveries
- daily distribution operations, which are usually planned the day before actual deliveries, and 3) multi-day delivery planning
The 3rd is typical for b2b retail distribution or building materials distribution. The first is a common model for on-demand delivery operations such as grocery or food delivery. The second is the base model of wholesale (B2B) distribution operations. In this case, planners usually route all the deliveries the day before. Hence, for the second and third types of delivery operations, mileage optimization can be a priority because they involve longer distances, while for dynamic deliveries, the main priorities are maximizing the number of stops made and minimizing the delivery time.
There are a number of delivery variables that make the route planning process hard and usually inefficient. These are;
- delivery windows
- capacity constraints
- driving times.
Delivery windows may vary from industry to industry or customer to customer. Delivery windows might not be important when you are delivering groceries or food, for example. Maximum delivery time (usually under an hour) is much more important in on-demand delivery operations.
The problem arises when delivery windows are too tight, or some customers have overlapping windows, i.e., foodservice distributors may have many early morning deliveries to restaurants. The other problem is variable service times – larger deliveries require longer time spent at customers’ locations, which makes a stop planning process even harder. In addition capacity constraints (truck capacity) and variable driving times during different times of day make this task even harder.
The route planning process can be an extremely difficult task because it may include all the described constraints. When we add a delivery model and frequency specifics, it becomes almost impossible to do manually and a hard task for many route planning solutions. Choosing the wrong solution could result in delivery planning process difficulties and create suboptimal route plans. Thus, planners and managers need to identify all of the described operational characteristics and pick a solution that includes most of them.