Advancing from reactive thinking to predictive problem solving will create smarter transportation networks.
Today, companies mostly use data to explain what has already happened, a practice known as descriptive analytics.
“How will companies turn data into insights to make better decisions?”
The more advanced companies turn to analytics to predict what might happen next.
But just 3 percent of firms deploy prescriptive analytics, which goes beyond prediction and determines the optimal action to take.
Increasingly, businesses will use analytics. We’ll see them use analytics to diagnose – and solve – problems well before they even realize an issue exists. Imagine that.
Overall, data is expected to grow 50 times by the year 2020.
Using data to make better decisions
The question is how companies will turn that data into insights to make better decisions.
In the world of logistics, analytics will help us get packages to your doorstep faster and in a more personalized manner than ever before.
We’ve already seen the transformative power of analytics investments: I was part of a team that designed ORION, a proprietary routing software that helps UPS drivers select the most efficient delivery route.
ORION looks at all the things a delivery driver needs to do: the stops that day, required service times, even less-obvious issues like lunchtime.
No matter how outwardly counterintuitive at times, ORION spits out the ideal plan for a driver to follow.
“We need to move from wisdom to clairvoyance.”
But for problem-solving purposes, even this level of technology is incomplete. We need to move from wisdom to clairvoyance. I’m talking about foresight that would make Sherlock Holmes jealous.
By combining the power of predictive and prescriptive analytics in real time, systems will look clairvoyant to the user. That is the Holy Grail.
We’ll soon see systems so advanced they won’t wait for traffic issues before reacting. They’ll predict when and where gridlock will occur and communicate to smart vehicles, re-routing drivers as needed. Everyone’s commute improves.
Analytics will enhance the entire transportation network, rather than just improve an isolated step in the supply chain. This is transaction-by-transaction optimization.
For example, we’ll crunch the numbers to determine the specific trailer that can best transport an individual package to its next destination.
We would know the exact time a trailer should move, how far it should go, the specific moment it should stop and whether a package should go somewhere else.
A more flexible supply chain
But imagine a system in which we can predict, with near certainty, the fastest way to move any parcel between different modes of transportation – and in real time.
The data would even tell us who should drive the delivery vehicle.
A completely optimized network provides unlimited ways to get anything to any destination, making the supply chain more flexible.
In the process, we would eliminate chronic inventory problems by ensuring supply never outpaces demand.
Analytics also will revolutionize how logistics companies manage their fleets, providing the equivalent of a check-engine light on steroids.
Say you’ve ordered 1,000 alternators for delivery trucks. Big data will tell you exactly when the parts begin to deteriorate.
“The logistics of the future will tap into human resourcefulness.”
People always ask me about the next algorithm. I tell them that we have to get the data right first and make maps even more accurate.
These maps will include not just a street address but the exact location of your mailbox – and better yet, the distance between various mailboxes.
Coupled with every bit of available information about the weather and traffic patterns, logisticians will do more than predict the most efficient route for delivery.
They’ll know when and where to send trucks – and why they’re doing it.
This will become reality at some point in the next 10 years. The logistics of the future will tap into human resourcefulness and with an assist from analytics, help us find solutions not yet imagined. Once we gather the data, innovation will follow.
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