Lessons Learned from Major Corporate Software Migrations

October 07, 2024

Table of Contents

Migrating enterprise software isn’t a simple task. With growing companies comes the scaling and upgrade of their software systems to accommodate business demands. Major corporate software migrations present their own unique challenges and risks. In light of past experiences, several key lessons companies can learn to avoid seeing major migration projects come in over budget and over time, and miss the mark on their business outcomes.

Carefully Evaluate Migration Readiness

Before committing to a major Visual FoxPro migration, companies need to assess their readiness across three key areas honestly:

Legacy Software Environment

What is the legacy environment like today? Is it too complex or brittle? In other words, are there too many highly customized older applications that won’t be easy to modernize or replace? Migration will require just how much work is based on existing technical debt and capabilities.

Data Environment

What shape is your data in? Evaluating data quality, consistency, accessibility, and portability is crucial. Data migrations often prove more difficult than expected. Garbage in will mean garbage out after a migration if data issues are not addressed upfront.

Organizational Readiness

Do you have the skills, resources, bandwidth, and executive buy-in to make the migration a success? These big projects are straining IT teams and business units alike. Early identification of organizational change management and training needs is important.

However, if companies are not ready across these areas, migration success is in jeopardy, and schedule delays, cost overruns and legacy system snags are possible. It’s about being honest about readiness gaps and budgeting the time and resources to pre-emptively address them.

Validate a Strong Business Case

Major software migrations require massive investments. The business case needs to be compelling enough to secure steady executive sponsorship and stakeholder alignment. Clearly define and validate the primary business drivers and expected outcomes before kicking off a migration journey that could span years.

Key business case validations include:

Cost/benefit analysis – Will savings or revenue gains exceed project costs enough to justify the investment?
Risk evaluation – What risks does the legacy environment pose if left in place without a migration?
Current state analysis – Are legacy systems truly incapable of meeting current and projected business demands? Why?
Future state visioning – Will desired capabilities be unlocked after migration, and is leadership aligned on what that looks like?

Without a solid business case, migrations can lose steam or get prioritized differently as leadership changes occur over long project timelines. Continually revalidating the business drivers and expected outcomes is essential governance throughout a migration initiative.

Architect the Future State with Care

Importance of Thoughtful Architecture

Architecting the future state technology environment is crucial for migration success, yet many companies fail to do this effectively. All too often, teams simply try to replicate legacy system capabilities within new solutions. This reactive approach usually leads to suboptimal results and missed opportunities.

Envisioning the Future State

Instead, you need to thoughtfully envision and architect your future state with the business capabilities required for the future firmly in mind. Conduct productive working sessions with both business and technology stakeholders across the organization.

Define what capabilities will actually differentiate you in the market and empower employees moving forward. Which solutions will unlock our growth flywheel? Get alignment on the must-have functionality while standardizing other non-differentiating systems.

Aligning Business Goals and Technology Principles

Your business goals and strategy should be the future state architecture. However, there are some fundamental modern technology principles that we should embed, such as cloud scalability, API-centered connectivity between systems, modular components, centralized data access, and built-in security.

Nobody can predict the future, but cloud solutions are incredibly flexible and provide unmatched scale to start small and scale up or scale down as the needs change. The move from a rigid legacy architecture to APIs and microservices brings much-welcomed agility. It lets you swap out components as needed, like building blocks.

Evolving Beyond Legacy Limitations

You only want to migrate legacy technical debt and limitations forward if you have to. This migration is the perfect opportunity to evolve. Architecting the future state is tough work that requires a shared vision across the business and IT.

The Long-Term Impact of Today’s Decisions

But done right, you can recast aging technology environments into key enablers of strategic goals rather than a constraint or afterthought. The solutions you architect today will determine what your organization can and can’t accomplish for years to come.

Plan Meticulously and Adjust Accordingly

Major software migrations can easily take 1-3+ years from planning through execution. Trying to plan out every project detail upfront meticulously is a fool’s errand. At best, companies can define a high-level roadmap with the flexibility to adjust as inevitable surprises occur.

Critical elements of a pragmatic migration roadmap include:

Phased deployment – Break projects into manageable phases focused on specific business capabilities or functions. Avoid big-bang cutovers.
Pilots and testing – Test migration processes, data conversions, integrations, etc., with pilot groups first before wide-scale rollouts.
Business involvement – Keep business representatives involved throughout to monitor results and catch issues early.
Contingency planning – Identify risk scenarios and have contingency plans in place for potential pivots or delays.
Post-implementation reviews – Conduct lessons learned and satisfaction assessments after each major milestone to identify ongoing improvements needed.

Adequate testing and piloting will reveal flaws and knowledge gaps in even the most meticulous plans. Building structured feedback loops and contingencies into the roadmap will enable course corrections. Remain nimble to adjust project scope and timelines based on learnings without losing executive buy-in.

Invest in Migration Testing

Testing is the most underappreciated aspect of major software migrations. IT teams often underestimate the testing efforts required, both from a timeframe and resource perspective. This is problematic since testing directly reveals how well solution designs and data migration assumptions actually align with business requirements.

Testing phases that require heavy focus for enterprise migrations include:

User acceptance testing (UAT) – Validate new solutions perform as expected for key user workflows. Identify usability and functionality gaps early.

Integration testing – Rigorously test all critical application and data integrations. Verify reliable interoperability and data synchronization.

Performance testing – Validate that new solutions can handle peak production workloads and expected growth. Identify infrastructure gaps.

End-to-end process testing – Test major business processes from end-to-end. Catch workflow gaps across systems.

Regression testing – Re-test previously working functions to catch any new defects after solution changes.

Data validation – Scrutinize production data conversions. Data errors post-migration severely impact business operations.

Getting testing right is crucial. Assign adequate resources to validation well in advance of production cutovers. Phase testing in conjunction with piloting and work to resolve defects systematically.

Invest in People and Skills Development

Ultimately, people determine the success or failure of technology migrations. Unfortunately, companies often underinvest in change management and skills development required to adopt new solutions. This slows user adoption and the ability to unlock full business value from new technologies.

Major training initiatives that require investment include:

Technical training – Hands-on training to reskill IT teams on new solutions being adopted.
Process training – Training for business users on updated processes and workflows enabled by new systems.
Leadership alignment – Sessions to align leaders on desired outcomes and get their vocal advocacy to drive adoption.
End-user training – Easy-to-consume training for all end users on new solutions and digital capabilities available to them.
Power-user networks – Develop networks of power users across business units who become local experts and coaches.
Measurement and reinforcement – Regularly measure solution adoption and continue to reinforce usage through training refreshers as needed.

Well-executed change management ensures organizations have the skills and alignments required to migrate successfully to new ways of working. This upfront investment pays long-term dividends.

Maintain Laser Focus on Data Quality

“Garbage in, garbage out” remains one of the most famous adages in technology for a reason. Data underpins business operations and decision-making today. Just a few critical data errors post-migration can wreak havoc on downstream systems and processes.

That is why maintaining an intense focus on data quality, conversion, and validation takes outsized importance on enterprise migrations. Some leading practices include:

Data profiling: Thoroughly profile legacy datasets to understand what is clean and what is dirty. Identify data domains requiring fixes beforehand.
Data cleansing: Provide resources to fix identified dirty data in legacy systems prior to conversion. This avoids baking in problems.
Validation rules: Define business rules and validations to test against converted datasets. Automate where possible.
Reconciliation: Compare production data volumes, metrics, and KPIs pre- and post-conversion to identify inconsistencies.
Anomaly detection: Use statistical analysis and even AI-based anomaly detection to uncover odd data values that skew results or break downstream processes.
Incident response: Have skilled data resources ready to investigate and resolve data issues discovered post-migration with minimal business disruption.

While often considered boring or secondary work, getting data right is what keeps companies running. Data experts working closely with business teams need to take the lead on data quality initiatives underlying migrations.

Conclusion: Remain Flexible and Expect Surprises

Major enterprise software migrations are multi-year transformational journeys full of expected and unexpected twists. I remain attuned to the fact that surprises and challenges will continue to arise no matter how meticulous the upfront planning is. Build contingency plans along with structured feedback loops to correct course smoothly when roadblocks occur.

If organizations follow leading practices around the critical elements above – validating readiness, centering architecture on differentiating business capabilities, phasing rollouts, testing rigorously, investing in people, ensuring data quality, and working closely with partners – they put themselves in the best position to migrate successfully and unlock their desired business outcomes over time.

With the rapid pace of technology innovation and evolution, companies must become adept at migrating between solutions to remain competitive. Using lessons from past migration journeys helps pave the way for future initiatives to reach their end destinations right on time.