Designing an AI Dashboard for Business Outcomes
Problem Statement
Customers need a single, easy-to-use dashboard to keep track of their projects, monitor key performance indicators (KPIs), and communicate with their team. Currently, they waste time switching between different tools and platforms, which leads to inefficiencies and missed updates. They need a solution that brings everything together in one place, provides real-time updates, and offers quick support through AI chatbots.
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My Role
Product Designer
Visual Designer
Information Architect
Prototyper
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Platform
Desktop Application
User Story
Meet Sarah, a project manager at a mid-sized tech company. Sarah often juggles multiple projects and needs a streamlined way to monitor service performance, track KPIs, and communicate with her team. She struggles with navigating through various platforms to get the information she needs, leading to inefficiencies and missed updates.
Research Session
With this platform being new, we pulled from past designs from similar projects, performance tools, and past personas. We collaborated with the design manager of a previous team that worked on a platform utilizing business outcomes, upcoming engagements and documentation. The Research Lead also conducted 3+ interviews with a diverse group of Consulting Engineers and Architects to understand their pain points and requirements.
Key Findings
Tracking KPIs: Customers find it challenging to track KPIs across different platforms.
Real-Time Updates: There is a need for real-time updates and alerts to stay informed about critical developments.
Customizable Dashboards: Customer have unique preferences so providing customizable dashboards would tailor to their specific needs.
AI Chatbots for Quick Insights: Understanding all data provided can be overwhelming and an Integration of AI chatbots would be beneficial for quick insights and support.
Reliable Communication: Communication can be unreliable resulting in lost documentation
Previous design iteration from different team.
This design was created 3 years ago by another team, and it didn’t focus on AI features.
Design Process
In the project, I worked with two other designers on the Customer Platform experience. I was tasked to design the Dashboard Overview and Messaging pages while the other designers worked on Activities and Documentation.
Following this I was to create information architecture for the main navigation.
Past Work
Another design team had previously worked on the design direction for this new platform. They received positive feedback from the stakeholders. We utilized those components like a design system then applied our research and insight into the designs.
Impact
Navigation
The final design features a refined navigation with a customizable dashboard covering four main categories:
Dashboard Overview: Focuses on business outcomes, expert recommendations, and upcoming engagements.
Documentation: Centralized access to all relevant documents.
Activities: Overview of ongoing and completed tasks.
Messaging: Streamlined communication among customer and client team.
New Features
AI-Driven Data Insights: Data -driven components utilize AI for deeper insights and support, allowing users to gain more information without leaving the screen.
Customizable Widgets Library: Customers can also move components and access a library of additional widgets tailored to their data needs.
Catalog
Dashboard Overview + Navigation
AI-Driven Data Insights
Messaging
Prototype: Simplified Navigation and AI Data Insights
The goal here was to showcase how a user could quickly review data highlights on the dashboard, easily access more insight with AI, and provide a simple navigation to access the most valuable information.
Lessons Learned
The dashboard has successfully solved the need for a centralized and customizable platform that monitors service performance and streamlines communication. The integration of AI chatbots would provide customers with quick insights, support, and also improve overall productivity.
Lesson 1
Research will not always be readily available, but it cannot stop you from progressing and creating new solutions. In these situations, leveraging existing data, user feedback, and iterative design processes can help bridge the gap and drive innovation. This approach ensures continuous improvement and adaptability, even in the face of limited resources.
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After