Reducing IT firefighting: Fewer failed updates, less manual cleanup

Why IT teams get stuck firefighting Mac deployments (and how to stop)

MacOS devices get deployed to end-users. Some devices apply baseline settings. Some don’t – interrupting business operations and frustrating users.

Before the issue can be resolved, IT’s in triage mode, gathering and analyzing logs to identify what’s preventing devices from meeting compliance.

If this scenario sounds too familiar, chances are this isn’t an occasional glitch, but the perpetual rhythm that defines IT’s mode of operation: reactive. Where once deployments are “pushed out,” clean-up is triggered and here’s where the heavy lifting begins.

For mid-market IT teams, this usually isn’t a skills problem or lack of planning, but a model problem. And understanding this distinction is the first step toward breaking the remediation cycle and shifting to a proactive mode.

The remediation cycle

While responding to issues has always been “part of the job,” the fact that it’s common doesn’t mean mid-market IT teams should simply stop questioning why issues that lead to additional, manual tasks continue to happen.

Let’s walk through a common deployment example:

1. A critical update fails

Though complete on 85% of the fleet, the remaining 15% cannot be verified.

2. Determining root cause

IT gathers reports and analyzes data to identify which devices failed and why.

3. Rerun the deployment

After removing hurdles, updates still cannot be verified, requiring manual intervention.

4. Manual response(s)

Endpoints remain potentially open to risk until the update is confirmed or installed manually.

When multiplied across the number of deployments occurring throughout a device’s lifecycle, it’s easy to see how reactive work crowds out everything else, leaving little room for other IT tasks.

Hidden costs add up

Time spent on cleanup is the most visible cost, but it’s not the only one.

Time: The only resource you spend but can’t get back

Depending on the size of your IT team, post-deployment remediations can trigger delays to other admin-related tasks, until prioritized issues are remediated.

Time spent firefighting is a reactive response that contrasts with proactive modes. In reactive mode, teams focus on tackling hurdles. In a proactive mode, IT is free to focus their skills on strategic initiatives. An example of this paradigm shift is automation, where the focus is on “removing hurdles from common tasks so IT can scale efficiently without needing more hands.”

Risk: Exposures are like windows that remain open

Each device that is stuck in a failed or partially completed state, or has a status that IT cannot verify, should be treated as a non-compliant endpoint.

Exposure goes hand-in-glove with time. The longer a known vulnerability remains unmitigated, the wider the window (exposure) grows and the greater the opportunity (time) that threat actors have to exploit those vulnerabilities. This is highlighted clearly in the disconnect between the time command-based management models push commands and when devices respond with their statuses.

Morale: costs that don’t show up in reports

This impact is nearly impossible to quantify but surely felt by IT team members. The effects on morale, by way of firefighting, commonly leave team members feeling mental and physical tolls. Common symptoms include:

• Overwhelm: Reacting to every action.
• Frustration: Feeling like there’s no progress.
• Exhaustion: Running from one issue to the next.
• Boredom: Repeating the same tasks over again.
• Apathy: Lack drive to complete tasks successfully.

If this occurs long enough, the temporary state of “catch-up” creates a culture that spends most IT’s time reacting to failures instead of using the skills they’ve acquired to build toward something better.

The implications on talent retention are equally real, but the good news is this type of impact can be both transient and largely preventable.

Does a command-based model create the conditions for failure?

No, but perhaps the question IT should be asking instead is: Do traditional MDM workflows meet the needs of modern environments?

To answer that question, let’s first examine the command-based, or push model used in traditional MDM operations.

1. The management server pushes a command to devices.
2. Devices receive it at a scheduled or predetermined check-in.
3. Once received, devices begin processing data payload(s).
4. Endpoints report statuses back to MDM only after the command is processed.
5. Device records stored on the server with timestamped status updates.

Because MDM processes occur over IP as best-effort, actions like the following can and do occur, contributing to deployment failures:

• Device offline during check-in: commands are missed.
• Limited network connectivity: commands eventually timing out.
• Users dismiss the update prompt: workflows stop running.
• Resource contention: queued commands cause bottlenecks.

These everyday occurrences highlight modern scenarios that legacy MDM was not designed to account for.

How a state-based management model reduces failures

Declarative Device Management’s (DDM) state-based management approach is designed with the needs of modern deployments in mind. First, all the components that make up what a compliant device looks like are included by IT. Next, that definition, or blueprint is shared directly with each managed device. Last, the devices themselves process the task(s) necessary to achieve compliance based on organizational needs.

How does DDM compare to legacy MDM?

• Automatic retry: devices retry automatically regardless of:
  • Devices being offline.
  • Limited network connectivity.
  • User-cancelled update prompts.
• Proactive status reporting: no waiting for the next check-in to validate compliance.
• On-device enforcement: consistent management is ensured at the device level.

What IT teams get back

For mid-market organizations, the benefits include a deployment management program that is efficient, thereby reducing firefighting because common deployment problems are proactively resolved before they occur.

Fewer failures = less post-deployment cleanup. And less cleanup (reactive) means significantly more time for IT to prioritize strategic endeavors (proactive).