Predictive Allocation: Detecting Network Chokes Days Before Traditional Systems

Introduction

In logistics networks, performance degradation doesn't announce itself. A hub congestion in one region, a delayed line haul, or capacity constraints ripple across hundreds of shipment lanes before anyone notices. By the time traditional systems flag the problem, you're already managing the fallout.

At ClickPost, we've spent years building Performance-Based Allocation (PBA), an engine that routes shipments based on carrier performance across specific lanes. Our system evaluates metrics like Average TAT (Turnaround Time, measured from pickup to Out for Delivery first attempt) to determine optimal carrier allocation for every shipment.

But we kept hitting the same technical constraint: data maturity lag.

We recently shipped two features that address this problem directly: the Choke Detection System and Last Mile TAT. These additions fundamentally change how our allocation engine operates. It is not just faster allocation, it is predictive allocation.

Related read: AI Carrier Allocation: The Next Step in Scalable Delivery Efficiency

The Data Maturity Problem

Here's the core issue: full performance visibility takes 7 to 10 days in most logistics networks. Until a batch of shipments completes its journey, performance degradation remains invisible in your data.

Take a lane from Mumbai to North-East India with a typical 5-day delivery window. If the network slows down due to congestion, you won't see it in your metrics until day 5 to 7, when those shipments finally mature. By then, hundreds of packages are already delayed. Any allocation change you make at that point is reactive damage control.

This isn't unique to one carrier or one region. Across our network of 500+ carrier integrations, we saw this pattern repeatedly: courier partners typically need 7 days to identify, verify, and respond to network chokes because they're waiting for shipment maturity before they have statistical confidence in the data.

The technical question we wanted to answer: can we detect performance degradation without waiting for shipment maturity?

Building the Choke Detection System

The solution required imputing TATs for in-flight shipments rather than waiting for them to complete.

Here's how it works. Every ongoing shipment's progress gets compared against historical performance patterns for that specific lane. We use those patterns to estimate the expected TAT for each immature shipment based on its current state and how the network is behaving in real time.

The system runs daily re-prediction cycles. As new scan data comes in, we continuously re-evaluate each unmatured shipment until it reaches delivery. This means we're not making a single prediction and moving on. We're updating our estimates as the shipment moves through the network, capturing even subtle shifts in performance.

When we detect statistically significant deviations from expected patterns, even if only a fraction of shipments have completed, the allocation engine automatically adjusts carrier distribution for that lane.

The result: we can now detect potential chokes 5 to 7 days earlier than systems that wait for full data maturity. The allocation changes happen before performance drops show up in delivery percentages or RTO rates.

From Lagging Indicators to Leading Indicators

This is not just machine learning, it is applied logistics intelligence.

Traditional allocation systems react to lagging indicators like delayed OFD or rising RTO percentages. Those metrics tell you what already went wrong. Our Choke Detection System uses leading indicators to forecast network degradation before it impacts deliveries.

For our customers, the technical capability translates to three operational changes:

1. Proactive reallocation. The system shifts volume to alternate carriers before performance dips become visible in standard metrics.

2. Reduced failure rates in high-TAT lanes. Early detection means fewer shipments enter degraded network paths.

3. Performance stability during volatility. The system maintains consistent delivery rates even during seasonal peaks or regional disruptions.

4. The allocation model is no longer reactive. It's anticipatory, continuously adjusting based on real-time network behavior rather than historical outcomes.

The Last Mile Problem

While solving the choke detection problem, our data revealed something else: the biggest variance in delivery performance doesn't happen in transit. It happens in the last mile.

The final leg from Out for Delivery to actual delivery attempt is where both carrier execution and customer behavior intersect. It's where address quality, rider allocation efficiency, and regional logistics capabilities all come into play. And it's where most customer experience issues surface.

Traditional TAT metrics measure the entire journey. We needed granular visibility into just that final stage.

Last Mile TAT: Isolating Destination Performance

Last Mile TAT measures carrier performance from the moment a shipment is marked Out for Delivery to the first delivery attempt. This metric isolates destination hub effectiveness from the rest of the supply chain.

Why this matters from an engineering perspective: it separates transit performance from last mile execution. A carrier might have excellent line haul efficiency but poor destination hub operations, or vice versa. Aggregate TAT metrics hide this. Last Mile TAT exposes it.

Operationally, this metric helps identify three things:

Destination hub inefficiencies. Poor address mapping, suboptimal rider allocation, or regional capacity constraints that don't show up in aggregate data.

Regional performance variance. The same carrier might perform very differently across different destination cities or neighborhoods.

Root cause clarity. Whether delays are logistics-driven (carrier issues) or customer-driven (unavailability, incorrect addresses).

By integrating Last Mile TAT into our Performance-Based Allocation Engine, we can now evaluate carriers on destination-level efficiency, not just origin and transit performance. Allocation decisions account for how well a carrier actually executes at the delivery endpoint.

The Combined Architecture

Together, Choke Detection and Last Mile TAT create a more responsive allocation system.

The Choke Detection System monitors upstream performance and predicts issues 5 to 7 days earlier than traditional methods. Last Mile TAT measures downstream execution at the destination. Between them, we have coverage across the entire shipment lifecycle with much faster feedback loops.

This means our customers can maintain higher delivery percentages and lower RTO rates even when individual carrier networks experience volatility. The system continuously learns from both leading and lagging indicators, adjusting allocation before problems compound.

What We're Building Next

The goal is to make logistics networks self-optimizing. These two features move us closer to that, but there's more technical work ahead.

We're exploring ways to incorporate external signals like weather patterns, regional events, and capacity forecasts into the imputation models. We're also working on multi-objective optimization that balances TAT performance with cost and capacity constraints simultaneously.

Logistics is still a domain where most decisions are made on gut feel or outdated data. The opportunity is in building systems that make those decisions faster and more accurately than humans can, using real-time data at scale.

At ClickPost, we process millions of shipments monthly across 500+ carriers. That data volume lets us build and validate these kinds of predictive systems. The Choke Detection System and Last Mile TAT are steps toward allocation intelligence that doesn't just respond to network conditions but anticipates them.

In logistics, the difference between reacting and predicting is measured in delivery percentages, customer satisfaction, and operational cost. We're betting on prediction.

Stop reacting to delays — start preventing them. Discover how predictive allocation identifies network bottlenecks early and automates smarter decisions. Schedule your ClickPost demo.