MENG LI
Cisco DNAC Assurance
AI-Powered Network Monitoring and Troubleshooting Tool
STRATEGY UX DESIGN · UI DESIGN · INTERACTION DESIGN
PROJECT OVERVIEW
Use Case Development
Design Workshop
User Testing
Data Visualizations
Design System
Visual Design
Feature Prioritization
ROLE
-
My Role: Product / UX / UI Design
-
Team: with 1 Researcher
TIME AND TOOLS
-
TIme: 5 Months
-
Tools: Sketch, inVision, Illustrator, Keynote
Prologue
WHAT IS DNAC ASSURANCE?
For many years, networks have been implemented by highly-trained and experienced network operators manually with extensive use of CLI (Command Line Interface). However, the deployment and subsequent operation of a large geographically distributed network remains a very daunting task for most organizations. What if a network manager had a tool to input machine-generated configurations and just press a button? What if this tool could analyze the network and automatically spot issues when they arise and guide network managers to root cause it? Cisco DNA Center is Cisco's solution to provide single platform that can perform intent-based networking for large enterprises. And Assurance is the unit responsible for Day N monitoring and troubleshooting of the network.
WHAT IS MY DESIGN FOCUS?
Within DNAC Assurance, I spent quite an amount of time working on understanding the user journey of troubleshooting network issues in their environment, propose simplified and elegant solutions to enhance the user experience of discovering, diagnosing, and fixing the issues.
FINAL DESIGN
Within DNAC Assurance, I spent quite an amount of time working on understanding the user journey of troubleshooting network issues in their environment, propose simplified and elegant solutions to enhance the user experience of discovering, diagnosing, and fixing the issues.
The rest of page is still under construction, feel free to contact me if you are interested to see the detailed design process.
Email: limeng233@gmail.com
Second, learning and summarizing the Best Practice as I accessed to different apps and articles.
1.
Easy to access and activate.
4.
Tolerate typos and ambiguity.
7.
Save information from one task to the next.
2.
Clearly tell people what tasks the bot can do. Make sure don't create false expectations.
5.
Allow people to interact with the bot both through free-text input and selection of links.
8.
Program flexibility into the bot: infer context and allow people to jump forward and backward.
3.
Users are not experts. Show examples of how they can ask questions.
6.
Allow sorting and filtering to let people narrow down through results.
9.
Make it personalized.
Third, besides knowing what are the good tips, also keep in mind what can go wrong.
- Nielsen Norman Group
Today’s chatbots guide users through simple linear flows, and our user research shows that they have a hard time whenever users deviate from such flows. Complexity is not well handled in the limited bot interface.
User Interviews
Before we start designing the screen or any conversations. We first need to understand who and what features we are designing for. A generative study was planned to collect such information. The goal of the user interview includes:
-
Identify key persona and corresponding use cases/pain points that have a need for conversational UI.
-
Understand the preferred use case/usage scenario in order so that we can create a priority list and phase out the development.
-
Understand what questions users want to ask, how users ask questions, and what kind of response they expect in the prioritized use case/usage scenario.
-
Understand any concerns or expectations of this type of voice system/conversational interface.
1.APPROACH
-
Moderated Remote Generative Study
-
60 Minute Sessions
-
4 Days of Fielding
-
15 Participants covering 4 personas
CUI Demo put together by Eng Team
2. METHODOLOGY
Participants performed the following activities:
-
Reviewed CUI demo and provided feedback on:
-
Expected functionality
-
Expected interaction
-
Ranked 8 categories for CUI priority for desktop (top 4) and mobile (top 3).
-
Spend 100 points on the 12 use cases from previously selected Top 4 categories in desktop to indicate value.
-
Indicated which use mobile use cases across Top 3 were most important (no point spending, simple selection).
Category Ranking and Use Case Bidding
3. KEY FINDINGS
KEY FINDINGS
USE CASE
Users Prioritize Monitoring & Troubleshooting the Network.
-
Most users ranked below use cases for their top 4 on the desktop platform.
-
Monitoring and troubleshooting for Wireless
-
Monitoring and troubleshooting for Wired
-
Monitoring and troubleshooting for Application & WAN
-
-
Users don't change their ranking that much for the mobile platform.
KEY FINDINGS
CONVERSATION
CUI Should Enable Users To Do More With Less Digging.
-
Many expect to ask and receive general status updates about their network as well as querying specific components.
-
Some expect to use keywords to see possible results.
-
Many expect to ask follow up questions after the initial query.
-
Accurate responses from the CUI to build trust and credibility with users.
-
Proactive automated troubleshooting and remediation.
KEY FINDINGS
INTERACTION
CUI Interaction Needs to Always be Available.
-
Have both voice interaction and typing options. A few participants mainly want to type to it (noisy environment and complex names).
-
Most users want a CUI popup or other format from anywhere in the network management system (or from the desktop) that can be easily accessed.
-
View the chat history, with some wanting to search back through it, reuse common queries, or export history for auditing purposes.
-
View and re-use common queries
Highlight and trace health issues that impact the network.”
If you can save me a few seconds, that’s what I care about.”
It would take a while to build up the trust. It’s the buddy cop movie analogy - they don't trust each other at first, but then they build trust over time.”
4. WORKFLOW SUMMARY
Design - Phase 1
Problem Statement:
Design a web-based intelligent assistant that use NLP to understand and support users to accomplish their monitoring and troubleshooting goals, and gradually expand to mobile and voice options.
-
Users liked having information-rich pages with graphs/tables (as opposed to more summarized info)
-
Users liked having the chat window isolated to the left side of the page (as opposed to interwoven throughout the page). This was due to the clarity it offered.
1. WORK PLANNING
Since this is the first time our team (including the PM and Eng team) exposed to CUI design and development work, I mapped out all the essential design work needs to be done, to help our stakeholders understand the scope and process needed, and align on the priority of my first batch of delivery. We decided to focus on navigation and develop some conversation first, and later tackle the visual and branding.
2. WIREFRAMING
3. CONVERSATION
Based on the top selected queries collected during the generative study, I worked with the stakeholders to brainstorm different kinds of conversations, including the questions, answers, and next-step suggestions. From there, we further composited the storyline of the POC (proof of concept). We want to demonstrate how smart assistant can help users fast discover and troubleshoot problems in their network.
4. A/B TESTING
Option A
-
Mobile-first
-
Interwoven chat
-
Rely on the conversation to navigate
-
Summarized info
Option B
-
Optimized for wide screen
-
Track dialog by thread
-
Allow manual navigation
-
Dense info
Analyzing Results
