Modernizing a complex OpenText environment - without stopping the business

The objective was to remove obstacles to cloud readiness, enable modern business capabilities, and make future changes easier and more sustainable. But where do you begin when everything is connected - and the business needs to keep moving?

Modernization is not a one-to-one replacement

Replacing legacy components with newer technology does not necessarily resolve the decisions and dependencies that created the complexity.

We first needed to understand what should be retained, simplified, redesigned, or decommissioned. The goal was not to recreate the existing environment with new tools, but to normalize data and permissions, reduce complexity, and establish reusable standards for future extensions and integrations.

At the beginning of the project, we had no access to the live system or legacy source code. Documentation was aging, while business-user descriptions varied significantly in detail. Through a series of workshops with business and technical stakeholders, we reconstructed the environment and developed a structured view of the existing landscape.

Turn uncertainty into a delivery plan

You do not need to know everything before planning a modernization program. You need to know enough to make informed decisions. We began with a focused 20-day assessment to map the functional and technical landscape, identify dependencies, define the target data model, and design the migration and coexistence approach.

Rather than examining every internal project in the same depth, we asked the customer to group projects according to their similarities. We then selected representative projects for deeper analysis and used the findings to categorize them by estimated size and effort - small, medium, or large.

This allowed us to extrapolate the likely effort across the wider portfolio and give decision-makers a clearer view of the scope, sequence, costs, and resources involved. A complex program filled with unknowns became a journey the organization could understand, evaluate, and fund.

Modernize in manageable chunks

Years of customization had created connections between data, workflows, applications, and integrations. Before modernizing individual projects, we needed to identify these knots and determine how to untangle them with the fewest possible downstream impacts.

By analyzing shared data structures, functionality, and dependencies, we defined clusters that could be addressed progressively. This turned one large transformation into a sequence of manageable releases. Legacy and modernized projects could coexist in the same live environment, with each release moving the boundary toward the target model.

Migration could also follow business demand. Specific sets of data could be migrated when users needed them, while less urgent information continued to be transformed progressively in the background.

No big bang: modernize in chunks, transform data in parallel, and keep the business running.

Don’t just move legacy data - move it forward

Moving historical information unchanged would have transferred the same complexity into the new environment. We therefore redesigned the data model before migration, introducing clearer hierarchies and taxonomies, decoupling objects, removing duplications, and identifying workflows to redesign or decommission.

The sequence was deliberate: Redesign the data model → Modernize → Migrate.

We applied the same principle to integrations. Instead of replacing legacy connectors one by one, we established a repeatable model that preserved necessary external contracts while removing duplicated data, database jobs, triggers, and low-level logic.

Build for what comes next

We involved the customer’s internal IT team throughout the program, combining external expertise with internal knowledge and capacity. Knowledge transfer and reusable practices were built into the delivery model from the beginning. This helped balance internal and external costs, make future efforts more predictable, and prepare the team to take increasing ownership of the environment.

The result was more than a modernized platform. It was a sustainable foundation for new business use cases, integrations, AI proofs of concept, and future upgrades. That is our approach: understand the landscape, reduce dependencies, and move forward in manageable chunks.

Because successful modernization should make the next change cheaper, faster, and easier than the previous one.

Facing a complex modernization program and unsure where to begin? We can help you turn accumulated complexity into a realistic and sustainable path forward.‍

Let's discuss your modernization journey.