Context & Problem

Pricing managers and analysts relied heavily on static dashboards. Detecting anomalies meant manual checks, often too late to prevent financial impact.

Pain points:

  • Delayed detection: Issues surfaced only after dashboards were refreshed.
  • Manual effort: Analysts had to constantly monitor and interpret data.
  • Lost opportunities: By the time problems were flagged, corrective actions lagged behind.
Actionable Insights Workspace Overview

Goals

  • Self-service: Let non-technical users create and manage alerts without engineering support.
  • Boost efficiency: Reduce reliance on analysts by streamlining anomaly detection.
  • Proactive insights: Surface issues in real time before they escalate.
  • Governance: Ensure actions and workflows remain consistent with organizational policies.

Hypothesis: By enabling self-service alerting and guided actions, users will resolve issues faster and with greater confidence, cutting the time from detection to resolution by up to 40%.

Process

1. Research

  • Conducted discovery sessions with pricing managers and business analysts.
  • Learned that users wanted proactive notifications instead of static monitoring.
  • Identified a tension: power users wanted flexibility, while non-technical users needed simplicity.
Whiteboard Logic and Detection Rules

2. Ideation & Design

  • Balanced advanced capabilities (joins, series detection) with clear no-code interfaces.
  • Designed reusable building blocks (Queries, Portlets, Dashboards) so the system could scale.
Actionable Insights User Flow Diagram

3. Testing & Iteration

  • Ran prototype tests with both technical and non-technical roles.
  • Key insight: users preferred guided flows (step-by-step setup) over large configuration panels.
  • Simplified terminology and added inline microcopy for clarity.
User Feedback and Iteration Canvas

Solution

The final design has three core elements that close the loop from insight to action:

Watchers

Define detection rules through a no-code builder.

Actions

Triggered alerts guide users toward recommended next steps.

Action Plans

Bundle multiple actions into reusable playbooks for consistency and scale.

Final Insights-to-Action Release Canvas

Outcomes & Impact

40% Reduction in Time to Resolution Users moved from month-long reconciliation cycles to real-time corrective actions.
Self-Service Alerts Non-technical users can now create and manage alerts without engineering support.
Proactive Detection Issues are surfaced in real time before they escalate into financial impact.

Reflection & Next Steps

  • What I learned: Early user testing highlighted the importance of guided flows and microcopy to reduce cognitive load.
  • Challenges: Balancing power user flexibility with non-technical user simplicity required careful iteration.
  • Next opportunity: Explore AI-driven "suggested alerts" to further accelerate setup and adoption.

My Role

As Lead Designer I owned the UX and interaction design from research to delivery. I worked with PMs, engineers, and customer success on requirements, and produced the flows, prototypes, and final UI in Figma.