It seems that you can’t read anything related to technology without “Big Data” being mentioned at least once. There’s no argument that capturing, analyzing, and leveraging the large amounts of data your business produces to make informed decisions is vital in today’s business and should not be ignored – but does it always have to be big?

In the logistics and field service world, you need to be flexible and efficient at the same time. Flexible enough to react quickly when circumstances change – because more often than not, they will – and have processes in place to ensure that efficiency is not impacted when those changes do occur.

That’s where real-time data provides a huge advantage in the day to day world of logistics operations and fleet management.

While retroactively analyzing data allows you to review days, weeks, and months at a time to uncover trends in fleet efficiency, driver utilization, or customer cost-to-serve reporting; real time data lets you view the current, and sometimes urgent, scenario in order to make a quick and informed decision.

What is Real-Time Data?

To start – let’s quantify real-time data. Generally in this context, any data transfer in increments between 30 – 60 seconds is considered “real-time”.

With this in mind, data available in such a short time can make for drastic improvements in day-to-day operations.

Dynamic Dispatching

Traditional dispatching is an extremely inefficient and arduous task in that a phone call is the primary method of communication. A driver has to call into the office after each delivery to report that they’re done and on their way to the next stop. If there are changes to the schedule, a dispatcher has to call and inform the driver of adjustments.

GPS fleet tracking solutions enable data to be transferred in time increments of your choosing, down to every second if desired, allowing dispatchers to view the current location and status of fleet vehicles. This allows them to analyze any situation and make a quick decision.

For example, if you have a customer who needs an urgent, unplanned delivery, a dispatcher can locate the nearest truck to the customer site and adjust the driver’s schedule so their next stop is at that customer. The driver then receives a message on their mobile device with the delivery details and seamlessly completes the delivery.

Where this scenario may have taken a significant amount of time to resolve before, a few adjustments were made and customer needs were met with just a few clicks of the mouse based on current data and location information.

Reduction in Days Sales Outstanding

Through paper processes, delivery tickets and invoices are manually calculated and taken to the office at the end of every day. Depending on your industry, however, it could be multiple days before tickets are turned in. In this case, not only is that data unavailable until it is turned in, but data must be manually entered into the back office system before an invoice can even be sent to the customer.

When delivery and ticketing processes are automated, that field data is captured electronically through a mobile device, automatically calculated, and transferred directly to back office systems in near real time. Additionally, tickets and invoices can be created while still on site – eliminating the time between paper ticket deliveries to the office.

Informed Decision Making

While big data is vital to continually improve processes and performance over time, it shouldn’t be the only focus. If you’re only looking at the past week, month, or quarter; it’s difficult to keep a pulse on the current status of your organization and make quick decisions based on actionable data.

The best approach is to make both sets of data available to relevant groups within your organization ensuring there is a focus on both long-term strategy and immediate improvements.

After all, those small chunks of real-time data will eventually grow to become big…right?

Learn how your organization can benefit from valuable data collected and delivered through our FleetAtlas Framework.


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