How Asana uses request tracking to streamline internal support workflows

Traditional ticketing systems can create more problems than they solve: requests sit in limbo for days, teams juggle disconnected tools, and rigid workflows force workarounds that slow everything down. 

Whether it’s reporting an outage, requesting office access, or flagging a food safety issue, the underlying process should be simple—someone asks, someone responds, and the issue gets resolved. But with long triage times and clunky handoffs, that ideal rarely happens. Teams need a better way to manage inbound requests without custom integrations or patchwork fixes.

That’s why we introduced the request tracking feature: a flexible, AI-enhanced way to manage inbound requests from first submission to final resolution, entirely within Asana.

Designed for any team in any organization, the request tracking feature makes it easy to create, route, and resolve tickets at scale. And with built-in email capabilities, even teammates without an Asana license can submit and follow up on requests, keeping everyone in the loop without forcing them into a new tool.

Inside Asana, teams like enterprise tech, workplace, and culinary are already using request tracking to simplify support, reduce triage time, and improve response consistency. And because the system is built to flex, you can shape it to match the way your team works, too.

A new foundation for request tracking

At the heart of Asana’s request tracking system is the ticketing project template: a flexible, out-of-the-box setup that helps any team manage requests from submission to resolution.

When you use the template, Asana sets up a complete ticketing system for you, including:

• A built-in intake form, which captures the requester's email address, request type (pre-populated with troubleshooting, access request, security, or other), a summary and description of the request, and any optional attachments.

• A structured project view that automatically groups and sorts tickets by status (new, in progress, pending, or closed), reducing the need to create rules that manually move tasks between sections.

• Preconfigured rules that automatically manage SLA timers and task routing, including:

  • Setting a first response SLA (e.g. two hours, customizable) when a new request is submitted.

  • Setting a resolution SLA based on ticket type.

  • Starting and pausing timers depending on task status (e.g. paused when moved to “pending”).

  • Automatically grouping tickets with other tickets sharing a similar status, so everything stays organized without manual sorting.

  • Sending reminders for overdue tickets, so nothing falls through the cracks.

• Customizable project settings that allow users to further customize their ticket grouping and sorting, including the option to add project sections.

• Customizable project settings that allow you to define working hours and time zones, ensuring SLA timers pause during non-working days or hours, and remain accurate across distributed teams.

In addition to manual rules, the template comes pre-built with AI-powered rules for customers using AI Studio, including:

• Automatically name tickets based on request content, so it’s easier to scan and prioritize.

• Check for missing information, and if something’s unclear, have AI leave a comment prompting the requester to clarify.

• Draft a response, giving agents a head start on replying to incoming tickets.

The template serves as a flexible foundation that teams can adapt to their needs. At Asana, internal teams have used it to support everything from workplace access requests to technical incidents: adjusting fields, rules, and automations along the way to create workflows that work the way they do.

Here’s how two teams are putting it into practice.

How Asana’s enterprise tech team tracks, triages, and resolves incidents faster

The enterprise tech team at Asana supports a wide range of requests, from outage reports and access provisioning to system enhancements and bug fixes. They needed a ticket tracking system that could help them route, resolve, and report on requests with accuracy and accountability.

Before implementing the ticketing feature, the team lacked a standardized way to track resolution time or monitor whether they were meeting internal SLAs. According to Jorge Zuniga, head of data systems and integrations, the team was receiving feedback that tickets were taking too long to close, without a clear line of sight into where delays were happening.

“One of the main issues raised was that it sometimes took up to a year to resolve a ticket,” Jorge said. “When we looked at the ticket history, we saw there were no rules. Tickets were getting reopened, reassigned, moved between projects. It was all over the place.”

Using Asana’s request tracking feature, the team built a customized support workflow that:

• Captures and categorizes tickets based on request type and urgency.

• Assigns severity levels to incidents, with corresponding SLAs for time-to-acknowledgment and resolution.

• Standardizes status workflows using customized stages like acknowledged, awaiting SME support, and on hold.

• Pauses or starts SLA timers automatically based on task status.

• Adds unique ticket IDs for easy reference and cross-functional tracking.

• Limits visibility to only the requester and collaborators, preserving data privacy.

Here’s how it works.

Step 1: A structured form captures the right information

Each new request starts with an intake form specific to the Enterprise Tech team, tailored to accommodate three types of requests:

• Incidents (e.g., report an outage, flag an issue, or notify the team when something isn’t working as expected).

• Service requests (e.g., request tooling access, update access to an existing service, or ask for help, information, or advice).

• Enhancements (e.g., request changes to the functionality or integration of existing software).

Depending on the request type, the form dynamically prompts for different inputs:

• Incident tickets require urgency level (from low to immediate) and business impact context, like revenue risk or operational disruption.

• Service requests include fields for service request type, delivery timeline, and application involved.

• Enhancement requests ask for focus area, current vs. desired state, business impact, and a user story.

Step 2: The ticket is triaged and routed automatically

Once a form is submitted, the request is automatically populated into the team’s private Enterprise Tech project. Each task is tagged with a set of custom fields, including creation date, request status, severity, request type, urgency, and business impact, so the team can immediately understand what kind of support is needed.

The team customized their project layout to go beyond the default sections of “new,” “in progress,” “pending,” and “closed.” Every request starts in a dedicated intake section, then moves into more specific categories based on request type or topic area, such as “Enterprise Data Intelligence” or “Finance Systems.” The result is a project that functions as a centralized system of record for managing all inbound tickets, making it easy to triage requests and track progress at a glance.

From there, preconfigured rules assign the appropriate SLA timers based on request type and urgency.

• Incidents are prioritized based on severity, with corresponding timelines for acknowledgment and resolution.

• SLA timers are configured to start only after a ticket is acknowledged, and pause automatically when the status changes to “on hold” or “awaiting user info.”

• All timers align with the team’s Pacific Time work schedule, ensuring SLA accuracy across time zones and non-working hours.

This level of precision helps maintain business continuity by holding the team accountable to clear response and resolution timelines. “If an incident gets created with severity zero, the clock starts right there,” said Jorge. “We have thirty minutes to acknowledge, four hours to resolve.”

To make those timelines easier to manage, the team also introduced clearer tracking throughout the ticket lifecycle. Custom statuses help agents and requesters track exactly where a ticket stands. In addition to default labels like “open” or “closed,” the team added more descriptive statuses to reflect key stages in their workflow, such as:

• Acknowledged

• In progress

• Awaiting SME support

• Awaiting user information

• On hold

• Resolved

Step 3: AI Studio supports triage, resolution, and reporting

In addition to the baseline AI Studio rules included in the ticketing template, the Enterprise Tech team built custom AI rules tailored to their workflow. These advanced rules help the team reduce manual overhead, resolve tickets faster, and scale support more efficiently:

• Check for duplicates: AI scans new tasks against previously logged incidents, looking for recurring patterns, matching names, or severity levels. If a duplicate is found, AI flags it and surfaces past resolution details.

• Suggest resolution steps: If the issue isn’t an exact match but has a similar history, AI suggests potential troubleshooting steps based on how similar issues were resolved in the past.

• Summarize outcomes: When tickets are completed, AI generates a summary of the task, including what was done, who was involved, and how the issue was resolved.

This AI-powered support saves the team hours of manual follow-up and gives agents a clear head start on known issues.

The impact so far: less manual triage, faster resolution, and better accountability

Since transitioning to the request tracking system, the ET team has seen measurable improvements:

• Time-to-resolution is now tracked accurately, with timers tied to incident severity and task status.

• Eight hours of manual backend support per sprint have been eliminated by replacing custom scripts with built-in automations and AI Studio rules.

• Reporting is more actionable, with clear metrics around SLAs, acknowledgment time, and backlog.

By building on Asana’s ticketing foundation and extending it with AI, the enterprise tech team now runs a workflow that’s faster, more consistent, and easier to scale.

How the workplace and culinary teams simplified support with AI-powered triage

Asana’s Workplace and Culinary teams handle in-office requests including facilities support, food safety issues, and badge access requests. Before switching to Asana’s request tracking system, these teams managed intake through a complex Zendesk form that often captured more detail than necessary and required significant manual triage to act on.

Using the ticketing project template as a foundation, the teams created a system that’s easier to use and faster to manage, with clear steps from intake to resolution:

• Simplified intake forms route requests to either the workplace or culinary team, dynamically updating fields based on request type.

• All new tickets land in a “processing” section, where AI checks for missing information, tags the request, and determines whether it’s ready to be worked on.

• When ready, the task is moved to “ready to claim,” where an agent can manually claim and begin working.

• Manual rules allow agents to draft responses, assign tickets to themselves, and move tasks through statuses including “working,” “awaiting requester response,” “stakeholder approval needed,” “pending external vendor,” “on hold,” and “closed.” 

“What I love about this is how customizable it is,” said Brayth Burdios-Woemmel, IT technical program manager. “We took the Asana ticketing template that was released to general availability and added our own rules on top of that. It’s already saving time and making the process a lot more approachable for new agents.”

Here’s how it works.

Step 1: A simplified form removes friction for requesters

The team started with the intake form included in Asana’s ticketing project template, then customized it to better match the types of requests they handle. They aimed to reduce friction for employees by collecting only the most relevant information.

Now, when submitting a Workplace or Culinary support request, employees only fill out essential fields, including:

• First name

• Department the request should go to (Workplace or Culinary)

• Description of the request

Depending on the department selected, the form dynamically updates to include the right follow-up questions.

• Workplace: Submission type (question or request, general feedback, issue or concern, other) and office location.

• Culinary: Submission type (question, general feedback, food safety report, other), culinary location, and additional details.

This lighter-weight form keeps things simple for the requester, while still gathering everything the team needs to move the request forward.

Step 2: AI-powered triage routes tickets automatically

Once submitted, each request is added to a shared Workplace and Culinary project and placed in a “processing” section. From there, a set of AI Studio rules handles initial triage and tagging:

• Initial workplace triage: AI reviews the task for clarity and completeness, based on pre-defined guidance for what qualifies as “sufficient detail.”

• SLA and priority decider: AI analyzes the content and automatically applies relevant tags to help categorize the task.

When the request is complete and ready to move forward, the system updates the task status to “ready to claim,” automatically routing it to the corresponding section of the project.

Step 3: Agents claim and complete tickets with built-in rules

Once a task lands in the “ready to claim” section, agents use a manual trigger to assign it to themselves and begin working on it. From there, the ticket moves through the workflow based on updates and status changes:

• Working

• Awaiting requester response

• Stakeholder approval needed

• Pending external vendor

• On hold

• Closed

This structure gives agents clear ownership while keeping requesters informed of progress.

Step 4: AI helps write faster, clearer responses

To close the loop efficiently, agents can trigger a “Draft a response” rule powered by AI Studio. For example, if someone submits a request for gym access in the Chicago office, the agent can trigger AI to write a response confirming the next steps or resolution. The agent reviews the suggestion, makes any final tweaks, and sends it off.

This rule saves time, especially for high-volume or repetitive requests, while ensuring consistency across responses.

Step 5: Reporting provides visibility across regions and performance

The team also built a reporting dashboard to track performance and spot trends. Key metrics include:

• Total tickets created and resolved

• Average time to first response

• Average time to resolution

• Ticket volume and resolution time by office location 

Agents can filter views by location, assignment, or status, so they always know where things stand.

The impact so far: less friction for employees, more efficiency for agents

Since implementing the request tracking system, the Workplace and Culinary teams have transformed their support workflow:

• Intake is simpler and faster, thanks to pared-down forms tailored to each team’s needs.

• AI handles initial triage, reducing the time agents spend clarifying requests and tagging tasks.

• Requests move through the system with greater clarity and consistency, improving accountability and follow-through.

• Performance is easier to measure, with real-time reporting by office location, region, and status.

By starting with the ticketing template and customizing it to match their workflows, the workplace and culinary teams can now manage high-volume in-office requests with speed and structure.

What’s next: Scaling request tracking across Asana

The success of these internal workflows is just the beginning. Asana’s IT team, one of the highest-volume support teams in the company, is preparing to move their 1,500+ monthly tickets into the same request tracking system. With AI-powered triage, built-in SLAs, and a flexible project foundation, they’re aiming to reduce response times, streamline intake, and scale support without adding complexity.

Request tracking in Asana was designed to serve as a flexible starting point—one that any team can adapt to their own support needs. Available on Advanced, Enterprise, and Enterprise+ plans, it helps organizations manage inbound requests with greater clarity, accountability, and efficiency. With Asana, it’s all in one place: from the first form submission to the final resolution.