Making smart logistical decisions requires the convergence of agile software platforms, rich sources of operational data, and use of smartphone mobile devices to maximize bottom line results.
Routing and logistics – one size does not fit all
Distributors have a wide selection of logistical software systems to choose from these days. So, which one should you choose? It all depends upon the delivery dynamics and product mix of your local delivery environment.
Solutions that provide basic truck routing, optimization, and mapping capabilities are perfectly suited for organizations with smaller fleets where routes are static (rural vs. urban) and customer demand for product is normalized and highly predictable. Under this option, trucks are sequenced and optimized one at a time.
For distributors with a high number of trucks, complex routes and customer delivery requirements, third party logistics systems are a great fit with bottom line results.
These solutions incorporate advanced software logistic algorithms and features designed to optimize multiple trucks at the same time while incorporating several delivery factors such as stop sequence requirements, customer delivery schedules and time windows, road restrictions and more.
Both options generate real and measurable outcomes – fewer miles are driven, truck operating costs are reduced, and more deliveries are made in the same amount of time using the same or fewer drivers and trucks. As a best practice, try to unify delivery operations on a single logistical software system regardless of your product mix; it’s a proven way to reduce operation complexity, labor costs, data redundancy, fragmented data analytics, and system security sprawl.
The evolution of operational data
With the right tools and technologies, every distributor can leverage their own operational data to become a more nimble and efficient company. Traditional delivery metrics tend to be well established and easy to record such as # routes, # deliveries per truck, # cylinder ships and returns, volume, revenue generated per order, etc. And now thanks to intelligent smartphone apps, brand new categories of operational data elements can be added to the pool of metrics for even greater operational insights. Here’s just a few examples.
Smartphone apps can utilize electronic forms (custom-designed user input screens that replace paper forms) to streamline business processes and capture a variety of data elements. Electronic forms can log daily truck checklists to measure and monitor truck maintenance and safety inspection requirements. This data is helpful with monitoring vehicle safety checks and forecasting truck maintenance issues. They can also be used to record the reasons (and digital pictures) why a cylinder was damaged by a customer.
Smartphones simplify and speed up the process of validating each cylinder that gets loaded, shipped, returned, and unloaded. The data collected can help minimize and eliminate unnecessary costs that stem from missed cylinder ships or returns that would otherwise lead to lost cylinders, theft, cylinder disputes, or billing issues with the customer.
Instead of maintaining a manual paper-based log of miles driven and arrival and departure times for each stop, smartphone apps can automatically capture this information for you. This data can then be analyzed against your existing delivery fee structure to determine if the proper rates are being charged on a customer-by-customer basis. Leveraging a smartphone’s GPS capabilities gives you complete visibility into a truck’s current location and breadcrumb trail.
The collective use of operational data can be compared against the decisions made by logistical systems for post trip analysis (actual vs. projected) to help fine tune ongoing routing and logistical planning. For example, how much time was spent driving vs. delivering? Did the driver make unnecessary stops and turns leading to extra miles driven and minutes wasted? Were projected delivery times in line with reality? Did we hit the mark maximizing truck utilization levels? Did we miss opportunities to make additional deliveries (or pick-ups)? As you can see, the more operational data collected and analyzed, the more questions can be asked, and answered!
The value of real-time mobile connectivity
Before the introduction of smartphones, obtaining real-time truck locations, individual delivery statuses, and truck utilization levels were a black box. Intelligent smartphone apps break down these barriers by enabling information to flow in real-time without any effort by the driver. As deliveries are made, delivery statuses are transmitted back to logistical systems in real-time. Truck inventory levels (cylinder empties and fulls) are updated after each delivery. GPS records the current location of each truck as well as the GPS coordinates for each cylinder ship and return. Order totals are computed for COD accounts. Credit card payments are processed on the spot to eliminate A/R.
Armed with this information, the entire organization is now riding in a “virtual seat” right alongside the driver answering customer delivery status calls with ease and dispatching additional orders to the right driver based upon truck location and truck stock availability without ever talking to the driver.
The next frontier
It’s clear that today’s use of logistical software, intelligent smartphone apps, and operational data can help solve real-world logistical challenges and generate higher levels of profitability for any distributor. But if we look to the future, the vast amounts of operational data being collected today will be used to create new forward-looking predictive models of tomorrow using machine learning and other AI technologies.
These new technology wonders hold the promise of outperforming decisions made by humans and existing software systems while generating even higher levels of efficiencies and profitability for distributors. Do you think this is true? We’ll have to wait and see, but the use of machine learning and AI technologies is starting to become widely used in other industries. It’s only a matter of time before it’s used in this one too.
This article was originally published by gasworld US in May 2020. The writer, David Schaer, is the president of Computers Unlimited.
Last updated December 10th, 2021.
