Hold on to your hats, because we’re about to make a bold claim: logistics professionals are time travelers. Not in the DeLorean-with-a-flux-capacitor way, but in a very real, very practical sense. Every day, logistics companies are manipulating time, predicting the future, and making yesterday’s impossibilities today’s realities.
Sound crazy? Stick with us. By the end of this article, you’ll never look at a delivery truck the same way again.
Let’s start with the most obvious example of logistics time travel: Just-In-Time (JIT) delivery. Imagine you’re running a smartphone manufacturing plant. You need 10,000 tiny screws to arrive at your facility at precisely 2:47 PM on Tuesday — not Monday, not Wednesday afternoon, not Tuesday morning. Exactly 2:47 PM Tuesday.
Why? Because those screws are going directly onto the assembly line. Too early, and you’re paying to store them. Too late, and your entire production line grinds to a halt, costing you thousands of shillings per minute.
Just-in-time logistics synchronizes the arrival of raw materials and components with production schedules, allowing companies to achieve minimal inventory levels. It’s about delivering goods purely on an “as needed basis” to significantly lower inventory carrying costs.
Think about what this actually means: someone, somewhere, had to look into the future, predict exactly when those screws would be needed, coordinate their manufacture, arrange their transport across potentially thousands of kilometers, account for traffic, weather, customs delays, and human error — and still deliver them at 2:47 PM on Tuesday.
That’s not logistics. That’s sorcery.
If JIT is the time machine, then predictive analytics is the crystal ball. And logistics companies are becoming frighteningly good at reading it.
Predictive analytics in logistics involves comprehensive collection and integration of diverse data sources including historical sales data, current market trends, economic indicators, and real-time weather forecasts. These systems use advanced machine learning models to forecast future demand with increasing precision.
Here’s a wild example: Amazon’s anticipatory shipping. The company analyzes your browsing history, purchase patterns, and even how long you hover over certain products. Then they ship items to warehouses near you before you’ve even clicked “buy.” When you finally make that purchase, it arrives impossibly fast — because it started its journey before you knew you wanted it.
This patent, filed in 2012 and granted in 2013, describes a method for what Amazon calls “anticipatory shipping” where packages are shipped to a destination geographical area without completely specifying the delivery address at the time of shipment. The system can even keep packages in near-continuous transit on trucks until a customer makes a purchase.
That’s not predicting the future. That’s creating it.
At Univar Logistics, we might not be quite at Amazon’s level yet (few are), but the principle is the same. By analyzing historical data, seasonal patterns, and current trends, logistics companies can anticipate what will be needed where and when — sometimes weeks in advance.
Remember when waiting a week for a package was normal? Our parents do. Now, 96% of consumers link “fast delivery” with getting something the same day. We’ve collectively decided that time should move faster, and logistics had to figure out how to make that happen.
The numbers tell a remarkable story. Average parcel delivery speed has accelerated by about 40 percent, going from 6.6 days in the first quarter of 2020 to 4.2 days in the second quarter of 2023. That’s not a small improvement — that’s a fundamental restructuring of how quickly goods can move through space and time.
But here’s the fascinating twist: survey respondents rank on-time delivery as more important to their satisfaction than speedy delivery. People would rather wait up to a week for an on-time delivery than have a delivery arrive later than expected.
What does this tell us? That logistics isn’t just about speed — it’s about control over time. It’s about making time predictable, reliable, manageable.
If you’ve ever wondered why your delivery driver sometimes takes what seems like a bizarre route, you’re witnessing another form of time manipulation: route optimization.
Modern logistics companies use algorithms that would make Einstein’s head spin. These systems analyze:
UPS’s ORION platform (On-Road Integrated Optimization and Navigation) recalculates individual package delivery routes throughout the day as conditions change. ORION analyzes over 200,000 routing options per driver daily, factoring in package details, traffic conditions, and even parking challenges.
The results are staggering: ORION has saved UPS more than $320 million as of 2015 and is expected to save $300–400 million annually at full deployment. The system reduces driver routes by an average of six to eight miles per driver, saving 100 million miles and 10 million gallons of fuel annually, while reducing CO₂ emissions by 100,000 metric tons per year.
What looks like a confusing route to you is actually a carefully orchestrated dance through space-time, designed to deliver the maximum number of packages in the minimum amount of time while using the least amount of fuel.
Your driver isn’t lost. They’re operating on a different temporal plane than you.
Here’s where logistics gets truly mind-bending. Companies aren’t just predicting one future — they’re predicting multiple possible futures and preparing for all of them simultaneously.
Demand forecasting aims to identify potential scenarios a company might face in its logistics needs, combining qualitative and quantitative approaches to create solid insights throughout the supply chain.
Imagine you’re managing inventory for an electronics retailer in Nairobi. You need to prepare for:
You can’t just pick one scenario and hope for the best. You have to stock inventory, allocate warehouse space, and position delivery vehicles for all possible futures. Then, as events unfold and one future becomes reality, you need to pivot instantly.
This is what logistics professionals do every single day. They live in multiple timelines simultaneously and adjust in real-time as the universe picks which one becomes real.
Of course, even time travelers face paradoxes. In logistics, these manifest as the terrifying scenarios that keep supply chain managers awake at night.
The Inventory Paradox: You need enough stock to meet demand (traveling to the future), but not so much that it becomes obsolete or expensive to store (stuck in the present).
The Speed Paradox: Customers want everything instantly (time compression), but ninety percent of customers are willing to wait two or three days for deliveries — especially if it lets them avoid shipping costs. So which future do you optimize for?
The Prediction Paradox: The more accurately you predict the future, the more you change it. If you stock up for a predicted spike in demand, you might cause that spike by making products more readily available, which then validates your prediction — but was it a prediction or a self-fulfilling prophecy?
These aren’t just academic questions. They’re daily dilemmas that logistics professionals navigate with a combination of data science, experience, intuition, and (let’s be honest) a bit of luck.
Kenya and East Africa have a unique advantage in this time-travel game: we’re building our logistics infrastructure now, in the age of advanced analytics and digital technology. While developed markets struggle to retrofit decades-old systems, we can leapfrog directly to cutting-edge solutions.
The Port of Mombasa handled 41.1 million tonnes of cargo in 2024, up from 35.98 million tonnes in 2023 — a 14% increase. The Mombasa-Nairobi Standard Gauge Railway has significantly reduced freight transit times. We’re not just keeping up with global logistics standards; in some ways, we’re defining them.
At Univar Logistics, we see this every day. We’re not just moving goods from point A to point B. We’re collapsing the time and space between “ordered” and “delivered,” between “produced” and “sold,” between “needed” and “available.”
Here’s the really wild part: you’re a logistics time traveler too, whether you know it or not.
Every time you check “where’s my package?” on a tracking app, you’re peering into the future — seeing where your item will be based on its current trajectory. When you select “deliver by Friday” instead of “deliver ASAP,” you’re literally choosing which timeline you want to live in. When you add something to your online cart and delay purchasing, algorithms are already predicting if and when you’ll complete that purchase.
Your refrigerator is a logistics problem. Your wardrobe is a supply chain. Your morning coffee represents a dance through time involving farmers, processors, shippers, roasters, distributors, and retailers, all coordinated to ensure that when you reach for that bag of beans, it’s there, fresh, at the right price.
So where is logistics headed? If current trends are any indication, we’re moving toward even more sophisticated time manipulation:
Hyper-Local Warehousing: Products stored so close to customers that “same-day” becomes “same-hour” becomes “same-minute.”
Drone Delivery: Not just faster delivery, but delivery that ignores traditional constraints of roads and traffic — literally flying through the obstacles that slow down time.
AI-Powered Prediction: 91% of organizations see AI as crucial in the next two years, and 72% warn that failing to invest now could threaten viability. Future logistics won’t just predict demand — it will shape it, respond to it, and fulfill it in ways we can barely imagine today.
Quantum Computing: Yes, seriously. When quantum computers become practical, they’ll solve routing and forecasting problems that are currently impossible. Quantum computing is earmarked as a key trend within the next five to 10 years in the logistics industry, essentially giving logistics companies the ability to calculate every possible timeline and choose the optimal one.
IBM worked with a commercial vehicle manufacturer to show how quantum computing could optimize delivery to 1,200 locations in New York City, factoring in 30-minute delivery time windows while recognizing truck capacity constraints. Quantum algorithms like QAOA have been shown to reduce travel time in logistics operations by up to 30% compared to classical methods.
Let’s get a bit philosophical for a moment. What is time, really, but the interval between wanting something and having it? Between needing something and receiving it? Between ordering something and unboxing it?
Logistics doesn’t just move things through space — it compresses that interval. It makes time feel shorter. It makes the future arrive faster. It makes yesterday’s luxury tomorrow’s expectation.
Timely delivery affects customer satisfaction, loyalty, and the decision to use a particular service. But it’s more than that. Good logistics creates trust in the future. It’s a promise that things will arrive when they should, that the world is predictable and controllable, that time can be managed.
In a world that often feels chaotic and uncertain, that’s no small thing.
So yes, logistics is basically time travel. It’s about:
The next time you order something online and it arrives exactly when promised, take a moment to appreciate the time-traveling wizardry that made it possible. Someone, somewhere, looked into the future, saw you needing that item, and set in motion a chain of events spanning continents, companies, and countless careful calculations — all to bend time and space in your favor.
Is that science? Is that magic? Is that time travel?
In logistics, it’s just Tuesday.
Ready to partner with East Africa’s time-traveling logistics experts? Connect with Univar Logistics and discover how we’re bending time and space to deliver your future, today.