Common pitfalls in Collibra Workflows implementation

Approvals, escalations, certifications – there’s a Collibra workflow for that. But (not to sound too harsh) just because you can build a workflow doesn’t mean you’re doing it right. In fact, many organizations dive in headfirst and end up with clunky, confusing, or completely ignored workflows. And Collibra Workflows only deliver value when they’re implemented with the right mix of strategy, simplicity, and collaboration, and with business processes in mind. 

So in this article, we’re breaking down the most common mistakes teams make when rolling out workflows, and more importantly, how to avoid them.

What is a Collibra Workflow?

Before we dive into the pitfalls, let’s quickly go over the Collibra Workflow definition.

A Collibra Workflow is an automated process designed using BPMN (Business Process Model and Notation) that helps manage data governance tasks in a structured, repeatable way that’s clear for everyone involved. Workflows can be used to coordinate interactions between users, automate approvals, escalate issues, and make sure compliance processes are easy to follow consistently.

Workflows run within the Collibra Data Intelligence Platform and can be triggered by user actions, metadata changes, or system events. Each workflow defines a series of tasks, decisions, and interactions, guiding users through governance processes such as requesting access to a dataset, certifying a data source, or escalating a data quality issue.

You can watch this Collibra Workflow Designer tutorial for a quick overview of Collibra workflows and what they look like.

Example: Data access approval workflow

Imagine a user needs access to a sensitive customer data set stored in a data lake. Rather than manually emailing the data owner and waiting for approvals, the organization uses a Collibra Workflow to automate the process:

1. User submits a data access request in Collibra.
2. Workflow routes the request to the data steward responsible for that domain.
3. The steward reviews the request and either approves or rejects it.
4. If approved, the request is automatically sent to the data owner for final approval.
5. Once approved, the workflow triggers a system integration that grants the necessary access, and the user is notified.

An automated workflow like this eliminates bottlenecks, provides an auditable trail of approvals, and helps make sure that only authorized team members can gain access to sensitive data. And, with the release of Collibra Workflow Designer (2025.06), creating, testing, and deploying custom workflows has become even more intuitive.

As usual, there’s a “but”. A powerful tool like this doesn’t guarantee success on its own. Real-world challenges, like workflows grinding to a halt under performance pressure, being dismissed by users due to poor relevance, or failing quietly because nobody monitors them, are more common than you might think.

Let’s take a look at a few examples.

Misaligned business objectives

Pitfall: Workflows designed without clear alignment to business needs, leading to low adoption or irrelevant outputs

One of the most frequent (and costly) missteps is designing custom workflows in a vacuum, focusing only on technical implementation and neglecting the “why.” If the workflow doesn’t solve a real business problem or align with strategic goals, it risks being ignored or underused.

For example, automating a data access approval process might seem like a win, but if the business actually needs a data certification workflow to ensure compliance with data privacy regulations, you’ve built the wrong solution entirely.

How to avoid it:

• Start with clear business objectives. Before designing a single step, document the underlying goals – for example, regulatory compliance, improving data quality, accelerating data product delivery, or increasing transparency.
• Involve business stakeholders from the start. Workflows are designed for business users. Engage data owners, stewards, compliance leads, and business analysts in workshops or planning sessions. Their insights will help define relevant use cases and prioritize what to automate.
• Map workflows to business value. Each workflow should trace back to a measurable outcome, like fewer access delays, faster issue resolution, improved data trust, etc.

Let Murdio take care of the development and technical implementation. We always start with the business needs first. 

“At Murdio, we start with solution design. This means that we start with a visual mockup before we even get to the code. We need to establish what the workflow is for, what it’s intended to do, and who participates in it. Only when we pinpoint every detail and create comprehensive documentation can we start the development of the workflow.”

Łukasz Banaszewski, Murdio Co-Founder

Poorly designed workflow logic

Pitfall: Overly complex or inefficient workflows causing performance bottlenecks

A common technical pitfall is designing workflows that are too complicated or monolithic – or designing too many of them. Developers who don’t have previous Collibra experience often want to handle everything with workflows. Which often results in too many workflows, with nobody really knowing what they actually do. And on top of that, running 150+ multi-day workflows simultaneously, all maintaining large in-memory states, can cripple performance. 

How to avoid it:

• Modularize using the Workflow Designer (2025.06). The latest Workflow Designer makes it easier to create modular, reusable workflow fragments. Use subprocesses and templates to keep logic clean and maintainable.
• Simplify long chains of tasks. Break down multi-step approval processes into parallel flows where possible. For example, instead of a sequential 5-person approval, route tasks concurrently to reduce time and system load.
• Test performance at scale. What works in a sandbox with 10 users might fail in production with 10,000. Simulate load and measure latency across the process chain.

“The key is to always start with the process and understand it first. Then – simplify it as much as possible. And only then design the actual workflows for an already optimized and pruned process.”

Łukasz Banaszewski, Murdio Co-Founder

Inadequate resource planning

Pitfall: Missing technical requirements or unavailable personnel delaying implementation

Sometimes, organizations dive into workflow implementation assuming everything will “just work.” But trust us, nothing ever “just works” on its own. 

Collibra Workflows often require specific backend resources, from network configurations and Edge provisioning to access tokens, security roles, and system integrations. And, maybe most of all, they require Collibra experience – at least the ones that are seamless and optimized.

Missing any of these can delay implementation for weeks. For instance, workflows that rely on pushing data to external systems via APIs need outbound access permissions, which aren’t always available in highly regulated environments.

How to avoid it:

• Identify all dependencies upfront. Before implementation, audit what the workflow will need: Edge node setup, system integrations, authentication protocols, API keys, etc.
• Engage the IT and security teams early. Include them in the planning phase to avoid last-minute blockers.
• Set realistic timelines. Allocate time for provisioning, testing, and issue resolution. Underestimating technical setup is one of the fastest ways to derail a workflow project.
• Document environment-specific configurations. Many problems arise from inconsistent setups across dev, test, and prod environments. Keep your documentation updated and include deployment checklists.

Neglecting user adoption and training

Pitfall: Workflows fail because end-users don’t understand their roles

No matter how perfectly a workflow is designed, it won’t succeed unless users, especially data stewards, domain owners, and business users, know how to use it. We’ve seen cases where workflows were technically sound but got stuck in limbo because a user didn’t know they had to approve a request or escalate an issue.

This is why at Murdio we always do user acceptance testing first, getting validation from real business users and refining the process before it’s deployed. Even small changes to the user interface can significantly affect adoption.

How to avoid it:

• Invest in user training. Use resources like Collibra University to train your key users. Demo your workflows and focus not just on “how” but also “why” – explain the purpose and value of each workflow.
• Pilot before scaling. Run the workflow with a small team first. Gather feedback on usability, clarity, and functionality, then adjust before an enterprise-wide rollout.
• Build intuitive interfaces. Use clear task descriptions, deadlines, and status indicators in the user-facing screens. Confusion leads to delays, or worse, people abandoning the process.
• Encourage feedback loops. Make it easy for users to report issues or suggest improvements. You’ll improve adoption and the overall quality of your workflows.

Lack of monitoring and iteration

Pitfall: Assuming workflows are “set and forget,” leading to outdated or ineffective processes

At Murdio, we don’t treat workflow implementation as a one-time project. As a matter of fact, it’s the fine-tuning phase that we’re really into – because that’s where we can really make a difference and improve things based on client feedback.

Because like any business process, workflows require ongoing care. Business priorities usually evolve (they better be), regulations change, everyday users provide feedback – and workflows need to be updated to remain effective.

And this might be pretty ironic, because workflows are supposed to make things easier, but without monitoring, they often become bottlenecks, complicating things, or at best, being completely useless.

How to avoid it:

• Monitor key metrics. Use Collibra usage analytics dashboards to track approval times, time to resolution, task completion rates, and error frequencies. KPIs help detect slowdowns and usage issues early.

Also, read this article on Collibra data quality metrics.

• Set up alerts. Automate alerts for stuck tasks, overdue approvals, or unexpected errors. This allows proactive troubleshooting.
• Regularly review and iterate. Schedule regular workflow reviews, quarterly or biannually, to assess performance, collect user feedback, and implement necessary changes.
• Use app revisions and version control. Collibra Workflow Designer now supports workflow revisions. Create updated versions without disrupting current usage, test changes safely, and roll them out with confidence.

Final thoughts

Collibra Workflows can dramatically improve data governance outcomes, but only when implemented with intention and discipline. They’re not just strings of code, but a living part of your data governance strategy. One that evolves with your organization, adapts to change, and ultimately drives trust in your data ecosystem.

If you need support with implementing Collibra workflows for your organization’s use cases, we’d love to connect and talk about your needs and challenges that workflows can solve. 

Frequently asked questions

What are Collibra Workflows used for?

Collibra Workflows help automate data governance processes like:

• access requests
• asset retention
• data helpdesk and issue escalation
• data certifications
• monitoring quality drops
• custom report generation
• stewardship assignments
• and much more.

They streamline collaboration, reduce manual tasks, and ensure compliance by enforcing consistent processes across your organization.

Do I need coding skills to build Collibra Workflows?

Not necessarily – it really depends. While Collibra Workflows are based on BPMN (Business Process Model and Notation), you don’t have to be a developer to build them, especially with the updated Workflow Designer (as of the 2025.06 release). That said, complex logic, integrations, or custom UI elements may require technical support or scripting knowledge.

How do I test a Collibra Workflow before rolling it out?

The best approach is to pilot the workflow with a small team or within a test environment. Use Collibra’s Workflow Designer to simulate logic and interactions, and gather feedback from real users before scaling it across the organization. Don’t skip this step – it can reveal usability issues and performance risks early on.

Why is my Collibra Workflow slow or stuck?

Performance issues are often caused by:

• Overly complex workflow logic
• Too many concurrent, long-running workflows
• Large in-memory states
• Missing external resources or integration failures

To fix it, try breaking large workflows into smaller steps, offloading states to an external database, or simplifying approval chains. Monitoring and logging will also help pinpoint bottlenecks.

How do I monitor workflow performance in Collibra?

Use Collibra dashboards and reports to track key metrics such as approval times, task durations, and error rates. You can also set up alerts for stuck or overdue tasks. Regular monitoring helps you catch issues early and continuously improve your workflows.

What’s the difference between a good workflow and a bad one?

A good workflow is:

• Aligned with business goals
• Simple and easy to follow
• Efficient and scalable
• Actively monitored and improved over time

A bad one? It’s usually complex, slow, disconnected from user needs, and forgotten after deployment. 

At Murdio, we only build good ones, but help fix the bad ones, too.