Verify AI Variance Reporting
Lead Product Designer | 6 Months
Capterra Visual Design Overhaul
Lead Product Designer | 6 Months
Capterra Visual Design Overhaul
Lead Product Designer | 6 Months
Please Note
NDA requirements prevent me from showing some key aspects of work involved in this project. If you'd like to know more please ask about my design process! 🙂
Please Note
NDA requirements prevent me from showing some key aspects of work involved in this project. If you'd like to know more please ask about my design process! 🙂
The Challenge
Property management executives and owners needed better visibility into portfolio performance. Existing variance reporting processes were often very manual and fragmented. Property managers often compiled explanations in spreadsheets and sent them via email, regional managers chased updates, and executives received incomplete or delayed insights. This inefficient method made it difficult to identify trends or take timely action across portfolios with 20+ properties.
The Challenge
Research employee, franchise, and customers’ needs to inform Restore’s customer experience strategy. Our deliverables include an initial website expression, a hero flow across major touch points, and a service framework.
The Solution
I led the design of a new variance reporting platform powered by generative AI that transformed the process into a more structured and collaborative workflow. Our solution streamlined how property managers documented explanations, how regional managers reviewed them, and how executives consumed portfolio-level insights.
The Solution
I led the design of a new variance reporting platform powered by generative AI that transformed the process into a more structured and collaborative workflow. Our solution streamlined how property managers documented explanations, how regional managers reviewed them, and how executives consumed portfolio-level insights.
Impact
Significant reduction in time spent on variance reporting for current customers (anecdotal)
100% completion rate for variance explanations
Actionable insights delivered to executives within 3 days vs. 2+ weeks
Successfully deployed across multiple property management companies with 20+ properties each
Impact
Significant reduction in time spent on variance reporting for current customers (anecdotal)
100% completion rate for variance explanations
Actionable insights delivered to executives within 3 days vs. 2+ weeks
Successfully deployed across multiple property management companies with 20+ properties each
Core Features:
Variance Table Interface: Familiar spreadsheet-like layout with comment fields and color coded priorities.
Approval Workflow: Review and approval stages for regional and executive stakeholders.
Executive Dashboard: Multi-tab view for AI generated portfolio summaries, trend analysis, and action tracking.
Admin Controls: Configurable thresholds, roles, and workflows to adapt to different organizational structures.
Core Features:
Variance Table Interface: Familiar spreadsheet-like layout with comment fields and color coded priorities.
Approval Workflow: Review and approval stages for regional and executive stakeholders.
Executive Dashboard: Multi-tab view for AI generated portfolio summaries, trend analysis, and action tracking.
Admin Controls: Configurable thresholds, roles, and workflows to adapt to different organizational structures.
Discovery and Research
I conducted contextual interviews with property managers, regional managers, and executives to understand pain points and goals.
Key insights:
Managers spent 4–6 hours per month on manual variance reporting.
Regional teams lacked visibility into report status.
Executives often received insights too late to act.
Both Regional teams and executives often had little time for the back and forth needed for clarifying key issues.
To validate directions quickly, our team turned to lightweight remote validation and generative research sessions with existing customers, comparing alternative workflows and consistently gathering feedback throughout the 6 month process. We needed to move quickly to gain market edge in a highly competitive prop-tech market.
Discovery and Research
I conducted contextual interviews with property managers, regional managers, and executives to understand pain points and goals.
Key insights:
Managers spent 4–6 hours per month on manual variance reporting.
Regional teams lacked visibility into report status.
Executives often received insights too late to act.
Both Regional teams and executives often had little time for the back and forth needed for clarifying key issues.
To validate directions quickly, our team turned to lightweight remote validation and generative research sessions with existing customers, comparing alternative workflows and consistently gathering feedback throughout the 6 month process. We needed to move quickly to gain market edge in a highly competitive prop-tech market.
Discovery and Research
I conducted contextual interviews with property managers, regional managers, and executives to understand pain points and goals.
Key insights:
Managers spent 4–6 hours per month on manual variance reporting.
Regional teams lacked visibility into report status.
Executives often received insights too late to act.
Both Regional teams and executives often had little time for the back and forth needed for clarifying key issues.
To validate directions quickly, our team turned to lightweight remote validation and generative research sessions with existing customers, comparing alternative workflows and consistently gathering feedback throughout the 6 month process. We needed to move quickly to gain market edge in a highly competitive prop-tech market.
Core User Flow
Through our generative feedback sessions we mapped out a core user flow.
Property Manager: Receives notification → Reviews flagged variances → Adds comments → Responds to AI questions → Submits report
Regional Manager: Reviews explanations → Asks clarifying questions → Approves or requests more information → Forwards to executive
Executive: Views portfolio-wide summaries → Identifies trends → Takes strategic actions
Core User Flow
Through our generative feedback sessions we mapped out a core user flow.
Property Manager: Receives notification → Reviews flagged variances → Adds comments → Responds to AI questions → Submits report
Regional Manager: Reviews explanations → Asks clarifying questions → Approves or requests more information → Forwards to executive
Executive: Views portfolio-wide summaries → Identifies trends → Takes strategic actions
Core User Flow
Through our generative feedback sessions we mapped out a core user flow.
Property Manager: Receives notification → Reviews flagged variances → Adds comments → Responds to AI questions → Submits report
Regional Manager: Reviews explanations → Asks clarifying questions → Approves or requests more information → Forwards to executive
Executive: Views portfolio-wide summaries → Identifies trends → Takes strategic actions
Design Process
I mapped the full information flow across user roles and created low-fidelity wireframes to align stakeholders around a simple, core experience. In Early iterations I explored more complex multi-screen flows, but validation with customers revealed users needed a more direct path.
I reduced the experience to five key steps:
Receive variance notification
Review flagged items
Add structured explanations
Submit for review
Access portfolio insights
Working closely with the product manager, we defined an MVP that prioritized core functionality while laying the foundation for future analytics and sharing features.
Design Process
I mapped the full information flow across user roles and created low-fidelity wireframes to align stakeholders around a simple, core experience. In Early iterations I explored more complex multi-screen flows, but validation with customers revealed users needed a more direct path.
I reduced the experience to five key steps:
Receive variance notification
Review flagged items
Add structured explanations
Submit for review
Access portfolio insights
Working closely with the product manager, we defined an MVP that prioritized core functionality while laying the foundation for future analytics and sharing features.
Design Process
I mapped the full information flow across user roles and created low-fidelity wireframes to align stakeholders around a simple, core experience. In Early iterations I explored more complex multi-screen flows, but validation with customers revealed users needed a more direct path.
I reduced the experience to five key steps:
Receive variance notification
Review flagged items
Add structured explanations
Submit for review
Access portfolio insights
Working closely with the product manager, we defined an MVP that prioritized core functionality while laying the foundation for future analytics and sharing features.
Current Experience
Variance Commenting: Table interface with contextual variance details, required fields, and progress indicators.
Manager & Executive Dashboards: Portfolio health summaries, key metrics, and variance trends across categories like maintenance, utilities, and income.
Admin Configuration: Drag-and-drop approval chains, customizable thresholds, and property assignments.
Current Experience
Variance Commenting: Table interface with contextual variance details, required fields, and progress indicators.
Manager & Executive Dashboards: Portfolio health summaries, key metrics, and variance trends across categories like maintenance, utilities, and income.
Admin Configuration: Drag-and-drop approval chains, customizable thresholds, and property assignments.
Current Experience
Variance Commenting: Table interface with contextual variance details, required fields, and progress indicators.
Manager & Executive Dashboards: Portfolio health summaries, key metrics, and variance trends across categories like maintenance, utilities, and income.
Admin Configuration: Drag-and-drop approval chains, customizable thresholds, and property assignments.
