Asset management automation uses technology to streamline IT processes in order to improve efficiency and reduce human error.
Yet, despite how much IT teams try to automate onboarding, offboarding, and other cross-functional tasks, most attempts fail outright or need constant manual fixing. That’s because of the Trust Gap–the distance between the asset state your automation assumed exists and the state that actually exists.
When you run IT asset automation using fragmented, untrustworthy data, you will only get results that scale errors, not outcomes. Rather than add more tools to the mix, you need to address the data problem and establish a foundation of continuously reconciled, lifecycle-aware asset data that powers every workflow.
Keep reading to learn:
- Why asset management automation tends to fail
- Where automations most commonly break
- How to fix your data for automated asset management
Three Reasons Why Asset Management Automation Fails
While many organizations assume they lack the tools to properly automate IT processes, most asset management automations fail because teams build them using bad data.
Three core issues break IT asset automations.
1. The Input Problem
All the systems and tools that feed automation workflows–MDMs, CMDBs, HR, security, compliance, and procurement platforms–house different versions of asset lifecycle reality. Plus, most tools only cover active, deployed devices, leaving several lifecycle stages unaccounted for.
Since automation tools aren’t designed to resolve contradictory data, workflows pull incorrect or incomplete asset information from these inputs. When, not if, they produce poor results, IT leaders are stuck constantly intervening to resolve issues.
2. The Silo Problem
On top of holding conflicting asset data, the various tools you use to manage IT and cross-functional operations also keep data siloed from each other across the asset lifecycle.
Discovery tools say a device is active and assigned. Your CMDB says it’s decommissioned. Procurement has it under contract. And none of the tools share information with each other.
Your automations pick incorrect data from one platform, not knowing that another platform holds the truth, creating false positives and negatives built on fragmented and outdated asset lifecycle information.
3. The Manual Problem
When your team needs to export, compare, and clean data before running each automation, you’ve automated the step after manual work, not the process itself.
Every hour you spend prepping data to feed automation initiatives is an hour of efficiency that the automation was supposed to solve.
Not only do all your manual efforts entirely defeat the purpose of automation in the first place, but it makes it impossible to demonstrate automation ROI, making it harder for your CIO to build a viable business case for IT asset management investment.
If you can’t trust your data to run your automations unsupervised, you’ll never see the benefits you were hoping to gain–especially in certain lifecycle stages.
Where Do IT Asset Management Automations Break?
You can’t automate what you can’t verify. As the Trust Gap widens and you automate asset workflows on top of fragmented, outdated data, several core operations feel the immediate impact.
If any of these scenarios seem all too familiar to you, it’s time to fix the data you use to automate IT asset lifecycle management.
Onboarding
Asset data isn’t synced across systems. The information is outdated. The automation fires, but the device it assigns already belongs to someone else. Correct automation, wrong result.
Why It Matters:
- IT and HR have to scramble to reverse the automated assignment and correctly assign a new device.
- The employee waits longer for their device and loses productivity time.
License Reclamation
A software license renewal is quickly approaching. Your software asset management and discovery tools disagree on ownership and usage details. Without the correct data, the automation misses that license, and it renews unnecessarily.
Why It Matters:
- Without correct data, Finance can’t properly budget or forecast for software renewal planning. There’s no chance of significant savings.
- IT needs to manually track and reconcile license usage, entitlement, and identity data to ensure IT asset automations can run correctly.
Compliance Reporting
A compliance tool runs automations based on asset data that only covers on-the-wire assets. Some compliant assets are flagged as noncompliant. The workflow misses real policy deviation stemming from shadow IT.
Why It Matters:
- Security teams need to triage alerts that result from automations built on lagging data.
- False results based on data decay create regulatory and compliance exposure.
- Audits become fire drills as teams need to manually check that automations pulled the right results.
Offboarding
An employee leaves the company. Their laptop’s ownership records were never updated in your CMDB. To your automation, there is nothing to collect. The laptop, and everything on it, gets shoved into the person’s closet.
Why It Matters:
- Procurement ends up buying additional hardware because stock diminishes with every lost return.
- Finance cannot follow planned depreciation schedules for hardware, and budgets are overrun due to non-reclaimed assets.
- Security risks increase as former users retain access to software licenses and sensitive data.
Every asset management automation failure traces back to the same thing: bad asset data.
It’s obvious, then, that the only way to ensure your automations run as intended and produce the results you need is to fix the data your workflows run on.
How to Fix IT Asset Management Automation
Automating IT asset lifecycle management requires continuously reconciled, lifecycle-aware asset data as a foundation.
Establishing that foundation means looking for systems that offer specific criteria.
1. Continuously Reconcile Asset Data
Asset data needs to be updated and synced across systems with every lifecycle change.
Point-in-time asset reconciliation can’t keep up with how fast modern IT asset landscapes change. Even daily reconciliation can allow for stale data when changes aren’t accounted for within that 24-hour period.
By having continuous, bi-directional data synchronization across MDM, CMDB, HRIS, ITSM, procurement, and cloud systems, you can execute automations based on a single, accurate asset record.
2. Include the Full Lifecycle
The Trust Gap grows when you only have limited, static visibility into an asset’s lifecycle.
Automations need full context:
- Who owns an asset
- Where it is
- Where it’s been
- How it’s used
- Its current compliance and security state
All of that information–and having a clear chain-of-custody of it–makes asset management automation more reliable, traceable, and defensible.
3. Detect Drift Early
Instead of waiting to discover data drift when your workflows produce the wrong outcomes, monitor for drift and resolve issues before they become problems that break automation initiatives.
As data drift persists:
- Incident management misroutes tickets
- Licenses renew when they shouldn’t
- Security slips when tracking uses old data
By catching drift as it happens, you can keep upstream data clean, close blind spots, and ensure automated remediation workflows operate using trustworthy information.
Ready to close the Trust Gap and actually start benefiting from IT asset automation?
Oomnitza offers each of these capabilities for a foundation that makes every workflow automation you already have actually deliver desired results.
Oomnitza Powers Asset Management Automation with Trustworthy Data
Establishing a strong data foundation is what makes automation reliable enough to run without a safety net.
Oomnitza enables this by continuously reconciling asset data across systems to keep data accurate over time and embedding governance directly into lifecycle workflows.
With Oomnitza, you can rely on one system to support automated asset lifecycle management by:
- Eliminating Conflicting Asset Records Across Every Connected System: Use 1,500+ turnkey connectors to reconcile data across your endpoint, CMDB, HR, ITSM, and procurement tools.
- Giving Every Workflow a Single, Verified Source of Truth: Resolve duplicate, conflicting, or incomplete asset records to address issues before automation ever acts on them.
- Keeping Every Asset Record Accurate at the Moment Automation Fires: Push reconciled, accurate asset data back to connected systems using bi-directional sync for real-time, 98%+ accuracy across all tools.
- Catching Data Drift Before It Breaks Your Next Workflow: Monitor for discrepancies between assumed and actual asset data and immediately trigger remediation.
- Running Workflows Without a Manual Verification Step: Leverage low-code workflows and prebuilt templates to make policy-driven automation accessible to your entire team.
- Giving Every Team the Visibility They Want: Share reports on automation health, asset lifecycle status, ownership, cost, and compliance to prove things are running as intended.
Frequently Asked Questions
1. Why does asset management automation keep failing even after we invest in new tools?
Because no number of tools makes up for bad data. Until you start building asset management automations on accurate, up-to-date, complete IT asset data that doesn’t require manual upkeep or intervention, every initiative is doomed to fail.
2. How do I know if my asset data is good enough to support automation?
If your asset management automations can run and produce correct, intended outcomes, without your team needing to step in and verify data before the workflow runs, you have good enough data. Anything less and your data is not ready.
3. Can I fix the Trust Gap without replacing our existing tools?
Yes. Rather than ripping out existing tools, closing the Trust Gap requires adding in a federated reconciliation layer that establishes a foundation of normalized, reconciled data. The right solution integrates with your existing systems, so you don't have to rip apart your tech stack.
4. Does more governance mean slower automation?
No. Increased governance over your IT asset management processes actually speeds automation. That's because, instead of taking more time to fix the mistakes that ungoverned, bad data always results in, you can trust that your automations are running on correct information and scale those efforts for faster results.
From “Automate and Hope” to “Automate with Confidence”
When your foundation is right, automated asset management runs correctly, without the need for triaging or manual intervention.
By leveraging Oomnitza’s IT asset management platform to maintain clean asset data, you can close the Trust Gap, feed workflows the data they need to run successfully, and realize the efficiency and ROI that comes from reliable IT asset automations.
