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Karnameh Forced Dispatch

Exploring why some vehicle inspection requests were less likely to be accepted.

PRODUCTKARNAMEHFOCUSPRODUCT DISCOVERYEVIDENCEReported intervention and overall outcomes
Karnameh Forced Dispatch cover
01 / PROBLEM & RESEARCH

Why did some inspections stall before assignment?

Customers book a vehicle, location and time. When the field network does not accept the request, operations must intervene manually. Dispatch data and operations interviews helped separate the symptom from its causes.

DISPATCH SIGNALS

Urgency was not the whole story.

13.54%Urgent requests forced
15.14%Non-urgent requests forced
31.8%Non-urgent with <1h remaining
01Predict dispatch risk
02Offer targeted incentive
03Assign before escalation

Vehicle type, timing, location, earning potential and capacity compounded. A targeted intervention gave operations an earlier decision point.

THE MODEL

Difficulty is contextual.

Force Dispatch appeared when several pressures stacked, not because of one request label.

01Vehicle
02Time
03Location
04Economics
05Capacity
RISK BY TIME OF DAY
10–1211.27%
14–1615.75%
16–1818.33%

The risk rose as the day progressed, peaking between 16:00 and 18:00.

01

Predict earlier

Flag hard-to-dispatch requests before assignment.

02

Improve attractiveness

Use targeted incentives where economics are weak.

03

Shape demand

Offer alternative time slots before capacity tightens.

04

Match smarter

Use vehicle, area and capacity signals together.

VALIDATED IMPACT
+12%Acceptance with targeted incentives
23%Accepted an alternative slot
71%High-risk cases identified
68%Prediction precision
THE DESIGN DECISION

Intervene before a request gets stuck.

A risk signal combined vehicle, timing, location, expected earnings and capacity. It identified 71% of high-risk cases at 68% precision, creating an earlier point for targeted incentives.

  1. Identify dispatch risk
  2. Offer a targeted incentive
  3. Monitor acceptance
  4. Escalate when needed
03 / EXPERIMENT & OUTCOME

Earlier decisions reduced manual work.

The targeted-incentive intervention improved acceptance by 12% and reduced Force Dispatch by 18%. Across the initiative, the reported results were:

−16%Force Dispatch
+9%Acceptance
−18%Assignment time
−14%Manual intervention

Intervention results and initiative-wide results describe different scopes; they are not interchangeable.

INTERACTIVE PROTOTYPEOpen prototype in Figma ↗Opens in a new tab
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© 2026 Sara JahanbakhshDesigned with clarity and curiosity ✦

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