Product Design
DESIGNING RELIABLE BUSINESS HOURS FOR DRIVERS IN ROUTE
A project about helping drivers make better decisions on the road by designing a system of states, rules and language instead of adding more UI.
Year :
2025
Company :
Mercado Libre
Products :
MeLi Logistics (MLP & Flex)
Scope :
Driver delivery experience
Problem :
Drivers relied on business-hour information to plan their routes, but inside the app this data was often incomplete, outdated or shown as broad time ranges with no confidence indicators.
The result: drivers arrived too early, too late or right at closing time, which increased failed deliveries and made routes less efficient.
What was happening in practice
Drivers couldn't confidently decide when to arrive
They searched for business hours outside the app
Stops weren't being properly prioritized
Avoidable failed deliveries kept happening
Impact: lost time, frustration, and lower delivery success rates.
Root cause
The core issue wasn't missing data. It was missing reliability signals.
Business hours were treated as static information, with no communication of certainty level, proximity risk or timing context relative to the driver's arrival.
Objectives :
Business
Scope : Metrics
Reduce failed deliveries linked to business-hour mismatch
Improve route efficiency
Increase decision confidence during delivery execution
User experience
Scope : Driver Experience
Help drivers anticipate arrival risk
Reduce uncertainty before reaching a stop
Support faster decisions without adding friction
Role & collaboration :
My role
Product Designer focused on UX writing and system logic design. I contributed to:
State definition
Messaging framework
Context rules
Interaction patterns for route view
Collaboration
This work required close collaboration with:
Product and Engineering teams
Operations and Logistics
Cross-functional stakeholders across multiple review rounds
THE CORE CHALLENGE :
The challenge wasn't the lack of data. It was its reliability and timing.
Business hours were often provided as time ranges, not exact schedules. Arriving too early or too late could mean a failed delivery, wasted time and an inefficient route.
Drivers needed to make fast decisions on the road, but the app didn't give them enough clarity to assess risk before arriving at a location.
Why this mattered
When drivers lacked clear business-hour information, the impact went beyond a single delivery. It affected route planning, increased failed deliveries and reduced trust in the app as a decision-making tool.
THE SOLUTION (HIGH-LEVEL) :
We designed a contextual business-hour visibility system integrated directly into the delivery flow.
Instead of showing fixed schedules, the system adapts messaging based on:
Expected arrival time
Distance to stop
Opening/closing proximity
Reliability level of the data
Drivers receive actionable signals — not just raw schedules.
What changed
Business hours became contextual, not static
Messaging adjusted based on time before opening or closing
Drivers could assess delivery risk without leaving their route view
Solution structure
1. Time-based logic
Business hours were interpreted differently depending on when the driver was expected to arrive: before opening, during business hours, close to closing or after.
2. Risk-informed messaging
Instead of blocking actions, the system communicated likelihood of success using clear, consistent language.
3. Flexible decision-making
Drivers retained autonomy to adjust routes while understanding the trade-offs of each decision.
IMPACT & results :
After implementing the routing and delivery information improvements, key operational metrics showed consistent gains across delivery performance and exception reduction.
Key outcomes:
Delivery Success increased to ~95–98% depending on schedule quality
First Visit Delivery Success stabilized above 92–94%
Business Closed cases reduced to ~0.7–2.4%
Unvisited Address rate remained below 0.5%
A deeper breakdown revealed a strong correlation between schedule visibility for drivers and delivery performance:
Routes with exact schedule displayed achieved:
98.3% delivery success
Lowest business closed rate
Lowest unvisited address rate
This validated the design hypothesis:
better operational information → better field decisions → higher delivery success.
key learnings
Designing for logistics at scale often means designing for uncertainty.
This project reinforced that clear communication, well-defined states and contextual messaging can be as impactful as interface changes when supporting real-time decision-making.
More Projects
Product Design
DESIGNING RELIABLE BUSINESS HOURS FOR DRIVERS IN ROUTE
A project about helping drivers make better decisions on the road by designing a system of states, rules and language instead of adding more UI.
Year :
2025
Company :
Mercado Libre
Products :
MeLi Logistics (MLP & Flex)
Scope :
Driver delivery experience
Problem :
Drivers relied on business-hour information to plan their routes, but inside the app this data was often incomplete, outdated or shown as broad time ranges with no confidence indicators.
The result: drivers arrived too early, too late or right at closing time, which increased failed deliveries and made routes less efficient.
What was happening in practice
Drivers couldn't confidently decide when to arrive
They searched for business hours outside the app
Stops weren't being properly prioritized
Avoidable failed deliveries kept happening
Impact: lost time, frustration, and lower delivery success rates.
Root cause
The core issue wasn't missing data. It was missing reliability signals.
Business hours were treated as static information, with no communication of certainty level, proximity risk or timing context relative to the driver's arrival.
Objectives :
Business
Scope : Metrics
Reduce failed deliveries linked to business-hour mismatch
Improve route efficiency
Increase decision confidence during delivery execution
User experience
Scope : Driver Experience
Help drivers anticipate arrival risk
Reduce uncertainty before reaching a stop
Support faster decisions without adding friction
Role & collaboration :
My role
Product Designer focused on UX writing and system logic design. I contributed to:
State definition
Messaging framework
Context rules
Interaction patterns for route view
Collaboration
This work required close collaboration with:
Product and Engineering teams
Operations and Logistics
Cross-functional stakeholders across multiple review rounds
THE CORE CHALLENGE :
The challenge wasn't the lack of data. It was its reliability and timing.
Business hours were often provided as time ranges, not exact schedules. Arriving too early or too late could mean a failed delivery, wasted time and an inefficient route.
Drivers needed to make fast decisions on the road, but the app didn't give them enough clarity to assess risk before arriving at a location.
Why this mattered
When drivers lacked clear business-hour information, the impact went beyond a single delivery. It affected route planning, increased failed deliveries and reduced trust in the app as a decision-making tool.
THE SOLUTION (HIGH-LEVEL) :
We designed a contextual business-hour visibility system integrated directly into the delivery flow.
Instead of showing fixed schedules, the system adapts messaging based on:
Expected arrival time
Distance to stop
Opening/closing proximity
Reliability level of the data
Drivers receive actionable signals — not just raw schedules.
What changed
Business hours became contextual, not static
Messaging adjusted based on time before opening or closing
Drivers could assess delivery risk without leaving their route view
Solution structure
1. Time-based logic
Business hours were interpreted differently depending on when the driver was expected to arrive: before opening, during business hours, close to closing or after.
2. Risk-informed messaging
Instead of blocking actions, the system communicated likelihood of success using clear, consistent language.
3. Flexible decision-making
Drivers retained autonomy to adjust routes while understanding the trade-offs of each decision.
IMPACT & results :
After implementing the routing and delivery information improvements, key operational metrics showed consistent gains across delivery performance and exception reduction.
Key outcomes:
Delivery Success increased to ~95–98% depending on schedule quality
First Visit Delivery Success stabilized above 92–94%
Business Closed cases reduced to ~0.7–2.4%
Unvisited Address rate remained below 0.5%
A deeper breakdown revealed a strong correlation between schedule visibility for drivers and delivery performance:
Routes with exact schedule displayed achieved:
98.3% delivery success
Lowest business closed rate
Lowest unvisited address rate
This validated the design hypothesis:
better operational information → better field decisions → higher delivery success.
key learnings
Designing for logistics at scale often means designing for uncertainty.
This project reinforced that clear communication, well-defined states and contextual messaging can be as impactful as interface changes when supporting real-time decision-making.
More Projects
Product Design
DESIGNING RELIABLE BUSINESS HOURS FOR DRIVERS IN ROUTE
A project about helping drivers make better decisions on the road by designing a system of states, rules and language instead of adding more UI.
Year :
2025
Company :
Mercado Libre
Products :
MeLi Logistics (MLP & Flex)
Scope :
Driver delivery experience
Problem :
Drivers relied on business-hour information to plan their routes, but inside the app this data was often incomplete, outdated or shown as broad time ranges with no confidence indicators.
The result: drivers arrived too early, too late or right at closing time, which increased failed deliveries and made routes less efficient.
What was happening in practice
Drivers couldn't confidently decide when to arrive
They searched for business hours outside the app
Stops weren't being properly prioritized
Avoidable failed deliveries kept happening
Impact: lost time, frustration, and lower delivery success rates.
Root cause
The core issue wasn't missing data. It was missing reliability signals.
Business hours were treated as static information, with no communication of certainty level, proximity risk or timing context relative to the driver's arrival.
Objectives :
Business
Scope : Metrics
Reduce failed deliveries linked to business-hour mismatch
Improve route efficiency
Increase decision confidence during delivery execution
User experience
Scope : Driver Experience
Help drivers anticipate arrival risk
Reduce uncertainty before reaching a stop
Support faster decisions without adding friction
Role & collaboration :
My role
Product Designer focused on UX writing and system logic design. I contributed to:
State definition
Messaging framework
Context rules
Interaction patterns for route view
Collaboration
This work required close collaboration with:
Product and Engineering teams
Operations and Logistics
Cross-functional stakeholders across multiple review rounds
THE CORE CHALLENGE :
The challenge wasn't the lack of data. It was its reliability and timing.
Business hours were often provided as time ranges, not exact schedules. Arriving too early or too late could mean a failed delivery, wasted time and an inefficient route.
Drivers needed to make fast decisions on the road, but the app didn't give them enough clarity to assess risk before arriving at a location.
Why this mattered
When drivers lacked clear business-hour information, the impact went beyond a single delivery. It affected route planning, increased failed deliveries and reduced trust in the app as a decision-making tool.
THE SOLUTION (HIGH-LEVEL) :
We designed a contextual business-hour visibility system integrated directly into the delivery flow.
Instead of showing fixed schedules, the system adapts messaging based on:
Expected arrival time
Distance to stop
Opening/closing proximity
Reliability level of the data
Drivers receive actionable signals — not just raw schedules.
What changed
Business hours became contextual, not static
Messaging adjusted based on time before opening or closing
Drivers could assess delivery risk without leaving their route view
Solution structure
1. Time-based logic
Business hours were interpreted differently depending on when the driver was expected to arrive: before opening, during business hours, close to closing or after.
2. Risk-informed messaging
Instead of blocking actions, the system communicated likelihood of success using clear, consistent language.
3. Flexible decision-making
Drivers retained autonomy to adjust routes while understanding the trade-offs of each decision.
IMPACT & results :
After implementing the routing and delivery information improvements, key operational metrics showed consistent gains across delivery performance and exception reduction.
Key outcomes:
Delivery Success increased to ~95–98% depending on schedule quality
First Visit Delivery Success stabilized above 92–94%
Business Closed cases reduced to ~0.7–2.4%
Unvisited Address rate remained below 0.5%
A deeper breakdown revealed a strong correlation between schedule visibility for drivers and delivery performance:
Routes with exact schedule displayed achieved:
98.3% delivery success
Lowest business closed rate
Lowest unvisited address rate
This validated the design hypothesis:
better operational information → better field decisions → higher delivery success.
key learnings
Designing for logistics at scale often means designing for uncertainty.
This project reinforced that clear communication, well-defined states and contextual messaging can be as impactful as interface changes when supporting real-time decision-making.