Hiring and Onboarding Remote Employees

You’re at your desk reviewing last week’s ticket metrics, coffee cooling beside your monitor, and one number looks good: 4.5 hours average time to escalation. That means your L1 team tried everything before passing tickets up, right? Then you drill into a resolved incident. Engineering fixed it in 10 minutes. API timeout error (something they’d seen three times that day already). Your L1 agent spent 4 hours troubleshooting (restarted services, checked configurations, walked the user through cache clearing). Standard fixes for connectivity problems. Engineering recognized the pattern immediately and applied a known workaround. Where did those 4 hours create value? …

You close the ServiceNow ticket at 4:17 PM, finally. Customer issue resolved after three hours of back-and-forth, all fields updated, status set to Closed. You switch tabs to check engineering’s progress on the underlying bug in Jira. The ticket is still marked “Waiting for Support.” The last comment is from yesterday: “Need more info from customer.” You closed that loop three hours ago. Your engineering team never saw the update. Now you’re typing an explanation to the customer about why the fix took two days longer than it should have. Your support team averages four-hour resolution times. Your engineering team averages a six-hour turnaround on escalations. But …

You update your ServiceNow ticket with engineering notes. Then open Jira to update the corresponding ticket with the same notes. Then Slack the engineer: “Did you see the update?” Then check both systems to confirm they match. Fifteen minutes gone. Forty escalations this week mean ten hours of duplicate work. Nobody’s tracking this (no time code for “checking if systems are in sync” exists) but you’re paying for it. In time. In delays when systems drift. In errors when updates don’t match. Management sees “tickets resolved.” Doesn’t see the invisible labor creating that output. Why escalation work stays invisible to management Your time tracking shows a ticket …

Your support AI routes a high-value customer to the basic tier queue. Not because the AI is poorly trained, but because it can’t see the CRM data showing their account status. The customer waits 20 minutes for an agent who immediately needs to escalate. You check the ticket later and see what went wrong: the AI made its routing decision using only what existed in the support platform. Everything else such as the account value, the renewal date, and the previous escalations live in systems the AI couldn’t access. ChatGPT works brilliantly because you give it complete context within the conversation. You describe the problem, provide background, and clarify details in r…

You’re staring at the escalation queue again. Same ticket, third reformat this week. Priority disappeared when it crossed from Zendesk to Jira. Custom fields such as business unit, revenue impact, compliance flags are all missing. Now you’re manually rebuilding the context your L2 team needs to route this properly, while the SLA (Service Level Agreement) clock keeps running. Your upstream team followed procedure. They documented everything in their system. But their “Critical” priority doesn’t exist in your priority schema. Their custom fields don’t map to your field structure. The ticket crossed the system boundary, and the metadata that makes escalation decisions po…

You’ve deployed AI agents to handle first-line customer inquiries, and they’re good at what they do—when they have the information they need. But you keep seeing them escalate tickets unnecessarily, give generic responses to known customers, or miss obvious context that would let them resolve issues immediately. The frustrating part? That context exists. It’s just trapped in a different system. Your billing history lives in Stripe. Account tier and contract details sit in Salesforce. Previous support interactions are in Zendesk. Project status updates are in Jira. Your AI agent only sees what’s in front of it: typically the current support ticket and whatever standard…

When teams track MTTR (mean time to resolution), they typically focus on technical response speed: how quickly engineers diagnose and deploy fixes. But look at actual incident timelines and you’ll find a different pattern. Delays happen while information travels between teams. Support has customer impact data trapped in tickets. Engineering has resolution context stuck in dev tools. Operations has monitoring insights isolated in observability platforms. The repair work waits on someone manually bridging these gaps. This isn’t about slow people or poor communication skills. It’s structural. Your systems don’t talk to each other, so humans become the connective tissue b…

Four teams. Three systems. One ticket nobody wanted to own. A customer can’t access their dashboard. Your support agent troubleshoots for twenty minutes, confirms it’s not a password issue, and escalates the ticket to engineering. Engineering sends it back: “This is a support issue.” Your agent re-escalates with more context. Engineering kicks it to DevOps. DevOps routes it to the platform team. The platform team sends it back to your queue: “Severity 3, not ours.” By the time someone actually looked at the problem, two business days had passed and your customer filed three follow-up tickets. Nobody bounced the ticket out of spite. Everyone applied their proce…

You’re three minutes into a Severity 1 incident when you realize nobody knows why the previous responder decided to restart the database cluster. The logs are scrolling, alerts are firing, and the executive team has joined the war room. Someone asks, “Did we check replication lag before the restart?” Nobody knows. The person who made that call is already troubleshooting the next failure mode, unreachable in another Slack thread. You’re holding a lit fuse with no idea how long it’s been burning. This happens because blameless culture meets its infrastructure problem during handoffs. You’ve done the postmortem training. You’ve removed “human error” from your vocabul…

Data makes for better decisions, more effective projects, and stronger alignment across your organization. With Smartsheet as the powerhouse for that data, you get visibility on valuable work, seamless collaboration, and deep reporting. But the data you need isn’t always in Smartsheet. That’s when you need a software integration. Smartsheet offers its own integrations through Smartsheet Bridge, allowing you to bridge the gap between this essential tool and other platforms. Unito’s Smartsheet integration, meanwhile, creates a two-way flow between Smartsheet and other tools, powering smoother collaboration across tools. Here’s your guide to picking the right option …

Your service desk metrics look great. Average handle time is down. First response time is under ten minutes. Ticket volume is steady. Then the VP of Sales corners you after standup: “Why does it take three days to reset someone’s laptop permissions? My team is still waiting on that CRM integration issue from last week.” You pull up the tickets. Both were closed by your service desk within the Service Level Agreement (SLA). Both were handed off to specialist teams (security, integration support), and that’s where they vanished into the void. Your service desk did its job perfectly. The work still didn’t get done. This is the coordination problem that most IT direct…

You’ve documented your ticket escalation process. Level One handles password resets and basic requests. Level Two takes infrastructure issues and account access problems. Level Three owns complex technical problems and vendor coordination. The workflow diagram looks clean. The support tiers are clearly defined. Then a ticket escalates, and everything breaks down. Level Two gets a ticket with “Network connectivity issue, escalating” in the notes and nothing else. They can’t see the troubleshooting steps Level One already tried. They don’t know which user reported the problem or when it started. They spend twenty minutes reconstructing context from Slack messages and em…

Your workflow documentation describes the happy path: a ticket arrives, gets categorized, routes to the right team, and gets resolved. Real workflows fail at the transitions. A P1 incident escalates from the service desk. Your engineering team sees it for the first time days after the customer reported it. The ticket shows three status changes, two reassignments, and zero context about what’s been tried. The customer’s last update reads: “Still broken. This is unacceptable.” You’re about to spend your evening reconstructing days of troubleshooting from Slack messages and email threads because someone, somewhere, marked the ticket as “in progress” without documenting w…

The ticket was simple. A user can’t access their financial reporting system. Priority: High. That part was clear. What wasn’t clear? Three teams touched the same ticket. Security had already verified credentials. Network ops had confirmed connectivity. But when the ticket landed with your application support team, none of that history came with it. Just a ticket number, a frustrated user, and a request to “please resolve ASAP.” You spent the next forty minutes reconstructing work that had already been done. The user spent that time wondering why IT couldn’t get its act together. And somewhere, buried in two other ticketing systems, was all the context you needed. …

Not every ticket gets resolved on the first try. Difficult issues, technical questions, and situations out of your control can all lead to a ticket needing to be escalated to a leader or a completely different team. That’s why having a robust, documented ticket escalation workflow is so important. Without this workflow, every ticket has the potential to balloon into a massive, costly issue. So how do you get this workflow under control? How do you measure its effectiveness? Here’s Unito’s guide to this essential workflow. What is ticket escalation? Ticket escalation is a process through which tickets that need additional expertise or authority are routed to…

So you’ve got a sales team in Salesforce with creatives or marketers managing projects in Asana. How do they collaborate and manage the pre-sales and sales cycles? Or alternatively, what if your support team handles case intake from Salesforce but then needs to assign work based on those cases through Asana? Maybe there’s a project manager jumping between both tools, maybe you’ve got automation figured out with a couple of triggers and actions to share work 1-way, or everyone is just sharing context in Slack and updating their own tasks accordingly. None of these options are ideal, especially not for a growing organization with hundreds or thousands of tasks to keep track…

This guide will show you how to quickly create a 2-way sync between Azure DevOps and Jira that turns work items into issues. When this guide is complete, you’ll know how to easily set up a no-code integration that keeps your software development work up-to-date in real-time. Whether you’re a Jira developer wanting visibility into Azure DevOps or a lead software developer streamlining cross-team work, Unito has you covered! Here’s an example of our demo integration between Jira and Azure DevOps New to Unito? Here’s more information about this Jira Azure DevOps integration. By the end of this guide you’ll have an Azure DevOps Jira integration that can: …

You meet all your Service Level Agreement metrics, but customer satisfaction scores are low and falling fast. You’re in monthly meetings explaining how both can be true while executives read comments about tickets “disappearing for days” despite being resolved “on time.” You suspect handoff delays are happening somewhere in the gaps between teams as tickets move between them. But your SLA tracking shows clean handoffs; the timer pauses, ownership transfers, and the clock restarts. Everything looks fine in your dashboard. The problem? Your metrics don’t actually measure your customers’ experience. They track ownership as though moving a ticket between systems is insta…

Your network operations team escalates a P1 ticket to infrastructure. The infrastructure team lead opens it twenty minutes later and sees a ticket created that morning with three comments, none of which explain why it’s now urgent or what the network team already tried. She pings the original engineer on Slack: “What’s the actual issue here?” He’s confused; he added a detailed handoff comment before escalating the ticket. The problem? It’s in the old system. She’s looking at the new one. This happens constantly during and after tool migrations. Escalation paths exist in your documentation and your org chart, but the actual context for individual tickets disappears in…

How do you manage work between Jira and Smartsheet? At Unito, we often see examples of one department using one tool, while the team they work with prefers another, while neither is interested in doubling their work in multiple tools. This disrupts software development projects with lost information, siloed data, miscommunication, and sluggish collaboration. So if you’ve come here seeking help with enhanced project or task management, this Smartsheet Jira connector is your go-to solution. By the end of this article, you’ll learn how easily anyone can set up real-time task and issue syncing to boost your team’s efficiency. We’ll navigate through each Unito connector’s …

You’re staring at an incident that looks familiar. The symptoms match something you saw three months ago: authentication failures cascading through the mobile app, then the web portal, then the partner integrations. You remember the pain of that incident clearly. What you can’t remember is whether you actually fixed the underlying problem or just patched the symptoms. You pull up the previous incident ticket. It shows the resolution: “Updated connection pool settings in the auth service.” But you’re looking at a Jira ticket, and the actual authentication service lives in a different team’s Azure DevOps backlog. The monitoring alerts came through PagerDuty. The custome…

This guide will show you how to integrate Salesforce objects and ServiceNow records. With a no-code setup and fully customizable two-way flow, Unito automatically syncs work items between Salesforce and ServiceNow so you can bridge the gap between sales teams, project managers, support teams, and more. Setting up an integration only takes minutes, and each Unito flow supports real-time updates, deep field mappings, and customizable rules. All you need is an account in Salesforce and ServiceNow with permission to create and edit records and objects. Unito’s two-way integration supports all ServiceNow records and Salesforce objects, but this walkthrough will focus on an…

Your newest hire just sent their third Slack message in an hour. First, they couldn’t find the email template for password resets. Then they needed the escalation criteria for database issues. Now they’re asking which Jira project handles network tickets versus hardware requests. You answer each question in under a minute, but you’re also watching your own queue grow while they wait. This is day three. They completed the standard onboarding materials. They know the tools exist. They just can’t find anything when they need it. Closing a single ticket requires knowledge from systems that don’t talk to each other, and you’ve accidentally built an operation where experien…

Microsoft Azure DevOps is a key tool for software development teams managing code changes, testing and deploying processes, reporting, and managing projects. ServiceNow is a premiere IT management platform with a wide range of use cases, but in the context of an integration with ADO, we’re going to focus exclusively on ITSM in this article. So, imagine a scenario where a customer or internal user encounters a problem with your company’s app or service. This incident is reported to the IT service desk, who creates an incident in ServiceNow. All the details are in that incident, but the dev team works in Azure DevOps to actually make changes to the app, product, or ser…

Your engineer just shipped a Slack app that surfaces ServiceNow tickets in relevant channels. It took three days to build. Six months later, ServiceNow changed their API versioning structure, your Slack workspace reorganized, and the engineer who built it is on a different team. The integration still works, mostly, but no one’s entirely sure how the error handling works, and there’s a growing list of edge cases in a Notion doc somewhere. This is the moment you start looking at integration platforms. Not because you can’t build integrations, but because you’re already supporting too many of them. The conversation that follows usually splits along predictable lines.…