SolarWinds IT Service Management (ITSM) is a software solution that helps organizations manage their IT services more effectively. It provides tools for logging and tracking service requests, resolving incidentsand problems, managing changes, and maintaining a knowledge base.
Organizations can streamline their IT service delivery processes, improve efficiency, and enhance customer satisfaction. Offering intuitive features for logging and tracking service requests, SolarWinds ITSM ensures a structured approach to managing incoming tickets. This helps organizations prioritize and address service requests promptly, leading to improved response times and customer satisfaction.
About Solarwinds
ITSM Product
SolarWinds ITSM is revolutionizing incident management with its GenAI summary feature, leveraging advanced AI capabilities to provide concise and insightful incident summaries.
Let's explore how this feature is transforming IT operations:
-
Smooth Handovers:
In the fast-paced world of IT, smooth handovers are essential for efficient incident resolution. With SolarWinds ITSM's GenAI summary feature, when tickets transition between teams or individuals, the next assignee receives a clear and comprehensive summary of the incident's context. This accelerates the resolution process by ensuring seamless knowledge transfer.
-
Tackling Lengthy Tickets:
Lengthy tickets or those containing extensive information can pose challenges for IT leads and managers. However, with the GenAI summary feature, key insights are distilled from ongoing conversations within the incident. This enables IT personnel to swiftly grasp the situation, even with complex or prolonged tickets, facilitating quicker resolutions.
-
Dealing with Urgent Issues:
In critical or escalated situations, time is of the essence. The GenAI summary feature provides stakeholders with quick overviews of incident statuses and highlights essential details for prioritization and decision-making. This ensures that urgent issues receive immediate attention, minimizing downtime and mitigating potential risks.
-
Easy Sharing and Data Privacy:
Handling sensitive ticket data can raise privacy concerns, especially with LLMs. It’s important to make sure account details and personal information are anonymized, securely handled within each account, and follow SolarWinds security rules to keep user trust and meet privacy laws. The GenAI summary feature makes sharing incident summaries easier while keeping data security a top priority. It runs on Amazon Bedrock, which keeps each customer's information safe and separate. Summaries are created specifically for each customer, protecting sensitive data and ensuring no information is shared across accounts.
-
Tailored Learning for Enhanced Relevance:
One of the key strengths of the GenAI summary feature is its ability to learn and adapt to each customer's unique needs. Recognizing that not every use-case is relevant to the next customer, the AI customizes its learning process. This ensures that the generated summaries remain highly relevant and insightful, contributing to improved incident management and customer satisfaction.
By harnessing the power of AI within SolarWinds ITSM, the GenAI summary feature optimizes incident management processes, enhances collaboration, and improves overall operational efficiency. With its focus on data privacy, security, and tailored learning, it sets a new standard for incident management solutions in the digital age.
About GenAI
Summary
Agents face significant challenges in managing and resolving incidents effectively, impacting overall productivity and ticket resolution times:
-
Difficulty in Understanding and Summarizing Ticket Details:
Agents spend excessive time reviewing ticket comments, titles, and descriptions to understand the full context. This manual effort to summarize information not only delays resolution but also increases the workload for agents.
-
Inefficient Handover Process
When incidents are handed over between teams or individuals, the lack of clear and consistent summaries leads to misunderstandings, missed details, and slower resolutions, further complicating the workflow.
These were the primary issues that we aimed to address with the GenAI Summary feature.
Problems
-
Admins
An admin manages system configurations to enhance agent productivity. By enabling features like GenAI summarization, they help agents quickly generate concise incident summaries, improving workflow efficiency and reducing errors.
-
Agents
An agent who manages a high volume of technical incidents on a daily basis often faces challenges in summarizing and documenting the intricate details of each ticket. Balancing the need for swift issue resolution with the requirement for detailed record-keeping and seamless handovers can be demanding. The GenAI feature addresses these challenges by automatically creating concise and clear summaries of the Incident details, which streamlines the documentation process. Additionally, it enhances the handover process between team members, ensuring that critical information is efficiently communicated and reducing the potential for errors or misunderstandings.
User Persona
I used the "How Might We" questioning method in the context of a user impersonation, this allowed me for the generation of inventive solutions while ensuring a focus on addressing the most crucial problems. By framing questions using "How Might We", it encourages creative thinking and opens up possibilities for innovative approaches to designing and improving the user impersonation feature. When applied to a user impersonation, "How Might We" questioning prompts us to consider various aspects of its functionality, user experience, and problem-solving capabilities. For example, "How might we help I and managers quickly assess long-term incidents without having to read through extensive incident histories?".
How Might We
Method
To better understand the GenAI Incident Summarisation feature and its challenges, I mapped out all competitors with AI Summary for Incidents, learning from their successes and mistakes.
Competitors
Thorough the research I collected and explored inspirations and ideas from direct competitors, the broader ecosystem, prevailing design trends, and big apps in the market, all tailored towards enhancing the GenAI Incident Summarisation feature. I meticulously mapped out all the corresponding flows and research using Figjam. Below, you can find screenshots from the research.
UI.UX Research
I used the method "User Journey Map" method to proactively address potential issues, enhance customer retention, and uncover vital information for making informed decisions. These visual diagrams depict various scenarios of the expected user experience when users interact with the GenAI incident summary feature.
-
AI Incident Summary Generation and Rating
-
AI Incident Summary Regeneration
-
Edit AI Incident Summary
-
Delete AI Incident Summary
-
GenAI Summarization Settings
User Journey Map -
Scenarios
A comprehensive flow map of the user experience when interacting with the GenAI incident summary feature, highlighting each UI screen and scenario. This serves as a crucial tool for aligning development and project management teams before proceeding with wireframes and visual designs for the GenAI incident summary feature.
-
Option 1 - AI Incident Summary Generation and Rating
-
Option 2 - AI Incident Summary Generation and Rating
-
AI Incident Summary Regeneration
-
Edit AI Incident Summary
-
Delete AI Incident Summary
-
GenAI Summarization Settings
Flow of the Screens
by Notes
We Have Chosen to Proceed with Option 1
What were the reasons for choosing the first option?
-
Easier to Find, placing the GenAI Incident Summary below the description aligns with users' mental models. Agents often expect summary-related actions to be closely linked to the incident details they just read, making it easier for them to understand and manage the summary in context.
-
Less Distractions, with the summary in the main section, agents don't have to look around the page, reducing distractions and making the process faster.
-
The step-by-step flow of reading the incident, generating the summary, and saving it all in one place feels more natural and helps agents work more efficiently.
Overall, considering the points mentioned, we found that Option 1 offers a simpler and more efficient user experience for agents.
Find below the wireframes, illustrating the AI Incident Summary feature. These wireframes provide a high-level representation of the layout and flow of the AI Incident Summary feature within the web app.
Wireframes
Handoff
In the handoff phase, I met with the development team, explained the design details thoroughly, and ensured a comprehensive understanding of the project requirements. This streamlined the transfer of responsibilities and minimized the chances of overlooking important elements during development.
Design Review
The purpose of the design review to verify that the final product aligns with the designated design specifications and to offer constructive feedback on the user interface (UI) design, if required. This process aims to guarantee that the end result faithfully represents the intended design while also allowing for necessary improvements and refinements to the UI, ensuring a user-friendly experience.
Handoff Phase and Design Review
Please find below the UI screens from our web app, illustrating the user impersonation feature.
These screens offer a visual representation and flows of the user impersonation feature in the web app.
UI Screens
In the 'AI Incident Summary Generation and Rating' flow, agent users have the capability to automatically generate incident summaries using AI and rate them based on accuracy and relevance to optimize incident management and improve response efficiency.
AI Incident Summary Generation and Rating
In the 'AI Incident Summary Regeneration' flow, agent users can regenerate AI-generated summaries to ensure greater accuracy and relevance. This capability is important for capturing updated information, improving decision-making, and optimizing incident management for better response efficiency.
AI Incident Summary Regeneration
In the 'Edit AI Incident Summary' flow, agent users have the capability to manually edit AI-generated incident summaries to ensure accuracy, add context, and tailor the content, optimizing incident management and improving response efficiency.
Edit AI Incident
Summary
In the 'Delete AI Incident Summary' flow, agent users have the capability to permanently delete AI-generated incident summaries, ensuring data accuracy by removing outdated or irrelevant summaries, which helps optimize incident management.
Delete AI Incident
Summary
In the 'GenAI Summarization Settings' flow, agent users can configure GenAI features by activating or deactivating them within the account settings. They can enable AI incident summarization through a checkbox and select the option to allow learning from ratings to improve the quality of the summaries.
GenAI Summarization
Settings
We were very happy with the success of the AI Incident Summary feature, which quickly became popular with users and exceeded our expectations. Within three months of its launch, a significant percentage of customers upgraded from the Advance Plan to Premier to access the GenAI features, showing how valuable it is.
From the data we gathered through Pendo, the feature’s adoption rate grew by 38.3% in the first 90 days, far exceeding our original goal of 20%. This shows how well it helps simplify incident management and improve agent productivity. Feature clicks also increased by 80.5%, proving strong user interest and satisfaction.
The business results have been impressive:
-
49.3% growth in unique accounts using the feature, showing it is widely adopted.
-
The feature helped grow revenue through plan upgrades, making it an important part of SolarWinds ITSM's success.
Customer feedback has been very positive.
Key benefits include:
-
Faster resolution times, as agents spend less time summarizing long tickets.
-
Better handoffs between teams, reducing misunderstandings and improving teamwork.
Although we can’t share exact numbers, usage rates were much higher than expected.
*All metrics shared are aggregated and anonymized to ensure compliance with data privacy standards. No individual or customer-specific data has been disclosed.
Outcome: Feature was
Adopted by Users
The SolarWinds Service Desk AI Incident Summary has achieved remarkable success, garnering widespread attention in the news. It has swiftly become a valuable asset among our customer base, with high demand arising from the invaluable solutions it offers. The GenAI features have had a profound impact on our business objectives, notably driving revenue growth as customers eagerly upgrade to premier plan in order to access this essential feature.
GenAI Making News Headlines
My Role and Challenges
Role - Product designer
As a Product Designer, I held full design ownership of the AI Incident Summary feature for the web app. My role covered the complete design process, from initial ideation and brainstorming to conducting user research, mapping the user experience (UX) and user journey (UJM), designing the user interface (UI), and creating prototypes. I ensured that the AI Incident Summary feature met SolarWinds’ high standards, delivering a seamless and efficient user experience that added significant value to our customers.
Challenges
-
How might we design a system that accurately summarizes complex incidents using AI while maintaining clarity and relevance for users?
-
How might we ensure users can easily edit, regenerate, or delete AI-generated summaries to maintain accuracy and context in incident management?
-
How can we visually distinguish AI-generated summaries while keeping the interface clean and user-friendly?
-
How might we provide users with control and confidence over the AI-generated summaries, allowing for real-time adjustments without confusion?
-
How might we ensure AI-generated summaries follow strict privacy rules by hiding sensitive data, limiting access, and keeping all data within the customer account?
Despite these challenges, I leveraged strong UX design principles and user research to create an intuitive and efficient AI Incident Summary feature that enhances the incident management process for our users.