When Data Science Meets Route Planning in Logistics

Let’s get straight to the point – Route planning is the lifeblood of the logistics industry and there is no denying it. Hundreds of drivers all over the US waste countless hours and immeasurable fuel to pass through conventional routes they know and are familiar with. Efficiencies are at stake and there’s not much of it in the logistics industry.

But, enter Data Science and all challenges vanish

How? Its interesting, so stick with us. In an era when our phones remind us of our cousins’ birthday, the entire practice of route planning seems to us like searching for a treasure map chased by pirates (competitors).

To begin, let us begin on a journey with data science and machine learning algorithms are not just buzzwords, but the very bedrock on which the future of logistics is being built. If a delivery driver in caught in chaotic road chaos, needs to deliver 50 parcels before sunset. In the past, you would rely on your knowledge of these routes or a static map. But data science and analytics has changed all that. The driver has a secret weapon- data science and analytics.

The new sheriff in town is determined to make your route-planning woes a thing of the past. Yes, Data Science is being adopted by logistics and supply chain companies like never before to optimize route planning across land and sea.

Data Science, the sophisticated cousin of Statistics, ingests humongous amounts of data in real time to analyze almost every facet of route planning that one could possibly imagine. What’s analyzed except traffic, you ask? Well, historical data, weather conditions, traffic conditions, safety conditions and a whole lot more to optimize the route for the driver, who probably doesn’t realize that the gentle non-stop cruise is because of millions of petabytes being processed in a data center somewhere that is working behind the scenes to make that happen.

Machine Learning Algorithms: The Crystal Ball of Logistics

But it is not data science alone that is rapidly evolving the logistics industry. As we have consistently said, data science is the solid foundation on which the grand fancy Machine Learning algorithms are built. Imagine, if you will, AI being further up the tower. While machine learning engineers are constantly trying ingenuous ways to further tune their models when it comes to transportation and supply chain. In fact, machine learning models form the heart of route planning and optimization, analyzing data in almost real-time and making the right choices for the driver. They predict traffic jams, expected delivery times, and suggest alternate routes as well. To be true, there is not much else help a trucker or a driver can get from their vehicle’s technology.

A Quick Use Case for the reader: Amazon.com

Amazon delivers packages daily, every hour, in almost every country, all over the world with their own predictions of traffic conditions, weather, road conditions, and any other bottleneck in passenger and goods transportation. It’s not Merlin or the more recent David Blaine making it happen. Its data science. Amazon analyzes past delivery data, including wait times, to deliver the sheer volume, which runs in millions every day, dispatches drivers in the most optimal way possible, and predict the most efficient route to take.

Peering into the future with a Kool Aid in hand, because we will need it, we look at an astounding future. From delivery drones to autonomous vehicles, with clinical precision, driving people and packages around. Amazon has achieved what perhaps no B2C company has ever achieved before. Kudos.

The Quantum Leap

Quantum computing is gaining ground and it is no surprise, given the age where compute power alone is considered a business advantage. Peering into the crystal ball of the future, we see data science and quantum computing converging. In this world, delivery routes may be planned days in advance and schedules remain fixed. Routing algorithms, empowered by Quantum Computing, could reduce the inefficiencies faced today. They can explore multiple potential realities simultaneously, optimizing not just for the present but for an infinite array of possible futures, simultaneously.

Idea seems far-fetched? Technologists have given it a maximum of five years for this to become a reality, and anyway, we’re kind of hazed every day now- Seeing today’s science fiction morphing into tomorrow’s reality.

And then there’s the capabilities to prove

We’re far beyond the point when professional certifications were “the in thing”. Let’s face it, it’s not anymore. It’s a necessity not just for employment, but for meaningful employment in a domain of your choice, if it is data science. Route Planning in Logistics, Supply Chain Management and Urban/Rural transportation are on top of only the tip of the proverbial iceberg.

In the Darwinian struggle of modern business, those who arm themselves with certified data science expertise will not just survive but thrive, charting courses of unprecedented efficiency through the choppy waters of global commerce. The future of route planning belongs to those who can not only read the data but also weave it into a tapestry of insight and action. And for that, my friends, certification is not just beneficial – it's essential.