With unprecedented demand for fast delivery at scale, businesses traditionally offering multi-day delivery are looking to expand delivery on demand, and delivery capacity – all with an eye to expenses. Balancing operational expenses with increased volumes and reduced times starts with good delivery planning: understanding the best way to use inventory, locations, fleets, drivers, and technology systems for optimal performance. This is why restaurants, groceries, retailers and logistics providers are looking for better routing solutions.
Great routing can not only improve your performance, but also provide the flexibility you need to grow your business. At Bringg, Route Optimization is an integral part of our Intelligent Dispatch and Routing solution which focuses on providing the optimal route to meet your growing requirements.
This post explores Route Optimization at Bringg, and how flexible route planning can help increase efficiency, reduce overhead, and help grow your business.
What is Route Optimization at Bringg?
The core of our Route Optimization is an intelligent routing engine that can run optimization several times a day, or several times an hour, making it ideal for supporting multiple commercial and operational needs.
The routing engine determines which orders go together in the same run, then plans the route based on these priorities as well as your operational constraints. There are dozens of different hard and soft constraints that can be taken into consideration, based on whichever the business chooses to prioritize.
Hard vs. soft constraints
A hard constraint is a question with a clear yes/no answer, one that the routing engine treats as a mandate before deciding on how to route the order. For example, if trucks past a certain weight are not allowed on a bridge, they will be routed through another road. If a grocery order can’t be left in the vehicle for more than an hour, then the order will be delivered on a route within that time frame – or moved to another driver, and another run, where the hard constraint can be met. This helps grocers support the cold chain, but it is also relevant for delivering anything whose quality is affected by time spent in transit.
A soft constraint is one which Bringg’s routing engine treats as a preference, and tries to apply whenever possible. It’s often the soft constraints which separate the ‘acceptable’ route from the optimal route. Businesses can set soft constraints around parameters like fleet, time and cost considerations, such as preferring to deliver with fleet X (the less expensive fleet, or the one with the best rating) over fleet Y, whenever possible.
Hard Constraints - strict requirements
Soft Constraints - preference
Custom parameters - variables that the business adds for consideration
Soft and hard constraints are typically combined to determine the optimal route. For example, when an order cannot be delivered within the requested delivery window because the refrigerated truck does not have the capacity (hard constraint), the business may choose to deliver it as close as possible to the requested delivery window (soft constraint).
Bringg also supports the ability to add custom parameters, which the routing engine can take into consideration when routing orders. For example, a business may want to take the customer’s lifetime value into consideration.
Common variables for deciding routes include:
- Vehicle capacity (based on 3D load planning)
- Vehicle road restrictions – bicycles cannot use highways, some trucks cannot use specific roads, highways or bridges
- Vehicle route preferences – avoid travelling through the city during rush hour
- Traffic and Timing – time on site, time in transit, time to base, time to park, total time to deliver
- Dangerous Areas – Avoid routes which go through dangerous neighborhoods
- Driver breaks and regulatory requirements
- Customer or order priority
Flexibility for optimal routing
The secret to creating the optimal route at scale is flexibility.
The more flexible the routing engine, the more optimal the results will be for each team’s particular needs.
What a flexible Route Optimization solution should support:
Planned and on demand delivery models with the same resources
Automated, manual and semi-automated routing
Internal and external fleets, and different fleet models
Planned vs. on-demand delivery services
Bringg’s Route Optimization supports multiple delivery models, from same-day and on-demand delivery, to routes planned days in advance. Businesses can include planned orders coming in from eCommerce sites alongside requests for home delivery from in-store orders. The in-store orders are added to the orders already planned, and the routing engine automatically recalculates the route, including that new order. This lets businesses plan routes based on what is optimal for each location or operation, and use the same resources – fleets, store staff, and inventory – to fulfill both types of deliveries.
Automatic and manual route optimization
As the above example shows, part of Bringg’s routing flexibility is the ability to run routing automatically, to suggest routes, or to provide dispatchers with the tools to manually plan out and optimize their routes.
Businesses can apply one or several different routing solutions per location, such as using a dispatcher for a large supermarket, but using automatic route optimization for smaller suburban locations. Some locations may want to run routes three times a day with specific cutoff times, while other locations may be entirely manual. Other organizations may want to standardize routing, which can be easily configured.
The decision on how much automation to apply is often based on order volume or speed. The largest volumes of orders, and the ones with the fastest promised times (i.e. on demand delivery) generally require automated routing.
Locations with only two or three delivery orders a day don’t need automation to decide order priority. However, smaller locations sometimes lack the manpower to have a designated dispatcher, again, highlighting the need for flexibility.
Businesses that want to offer on-demand delivery generally require fully automated dispatch and routing to get the orders out fast: automatically choosing the optimal driver and vehicle, from the optimal fleet, and calculating the best route based on your businesses priorities and promised delivery time.
Supporting manual Route Optimization – Some businesses have experienced dispatchers with an encyclopedic knowledge of routes who prefer to manage routes manually. In this case, our Route Optimization saves the dispatcher time by supporting their manual planning. Some dispatchers prefer to have the system suggest a route, and then to manually tweak the routes as desired. Others prefer to plan the entire route manually. Bringg provides the recommendations and insights to support both scenarios. For example, the dispatch dashboard’s preview map automatically recalculates ETAs, providing the insights dispatchers need to optimize their route.
Flexibility around fleets and driver models
Bringg’s routing flexibility is unique in that it supports multiple routing modes within a single environment, a single team, or even with the same resources.
- Pooled vs. tethered fleets – Businesses can create routes for drivers who serve a designated region, moving in between different warehouses, stores and customers, and for drivers who only pick up orders from a single location.
- Internal and external fleets -Bringg supports the use of both internal and external fleets. When a business provides their external fleets with Bringg’s technology, these fleets can also utilize the Bringg Driver App and even, when configured, allow drivers to optimize routes themselves, just like an internal driver. Alternatively, these fleets can work with their own technology, which they connect to Bringg.
Accurate, optimal routes based on data science
Bringg’s Routing Engine provides uniquely accurate routing times based on robust data science, extensive historical data and real-time data feeds. Machine learning algorithms accurately project the timing of the entire delivery run – the time to load, time to delivery location, time on site, and time back to the loading location – based on each business’s actual performance. These accurate predictions improve the suggested routes, and increase delivery capacity without expanding your resources.
Just as importantly, accurate timing predictions allows businesses to reduce or eliminate timing buffers, so they can offer customers shorter delivery windows. This can also be a differentiator in service plans, with premium plans offering shorter delivery windows than basic plans, and Bringg’s routing engine taking those different windows into consideration when planning routes.
This accuracy extends to the middle mile, including telling staging staff exactly which staging dock to go to, in order to increase delivery speed.
Routing is part of Bringg’s general approach to provide maximum flexibility to businesses, helping them achieve rapid growth and fast delivery at scale. For more about Bringg’s Intelligent Dispatch and Routing, click here.