This order will miss its pickup window tomorrow. Today you can still fix it.
Bicycle predicts every day which orders are at risk of missing their window, gives the reason, and recommends a fix to the dispatcher.
No credit card required
An order misses its window long before the deadline: no carrier has accepted it, the pay is below what the lane needs, or nobody nearby is free. By the time it shows in on-time delivery, the customer has been let down.
At-risk orders are flagged a day ahead, each with its reason and a recommended fix.
What happens when a KPI moves.
- 01
Detect
Orders at risk of missing their window are predicted daily, and unassigned orders are flagged.
- 02
Explain
Each one carries its reason: no carrier, a gap in the lane, or tight timing.
- 03
Act
Bicycle recommends raising carrier pay or offering the order to carriers in nearby lanes, and the dispatcher decides.
- 04
Learn
The prediction is tuned on what happened to the orders it flagged.
on-time delivery, trending toward 85%
Seen at: an automotive logistics provider. Read the case study
Everyone can ask. Data & Analytics controls what gets trusted, published, and acted on.
Common questions
How do you predict which orders will be delivered late?
Does the late-order prediction improve over time?
More on delivery and turnaround
See it on your own KPI.
Bring one revenue-critical KPI. We'll show how Bicycle detects the movement, explains the cause, and recommends the next step.
