Transform Legacy Systems into a Clean IFS Cloud Go-Live with Forseti.
If you’re gearing up to move your business on to the cloud with IFS Cloud, you’re probably well aware that it’s about far more than installing new software. At the center of any successful transition lies one critical element: data migration. Whether you’re in manufacturing, distribution, oil & gas, retail, or construction, the journey from your legacy systems to a fresh IFS Cloud go-live represents an opportunity and a risk.
This is where Forseti Solutions steps in. With deep expertise in building IFS ERP systems across key industries, we understand the complexities of moving from legacy to high-performing platforms. In today’s post, we share three key strategy areas to guide your data migration and help you go-live with confidence.
When it comes to data migration for IFS Cloud, one of the first decisions you must make is “how” you’re going to move the data, and that choice sets the tone for the rest of your project.
Why this matters
According to a recent article by Help Desk Migration, businesses that invest in a strategic migration approach enjoy a 29% ROI and a 14% improvement in process resolution.
On the flip side, migration projects are notoriously challenging: A study by Tredence found that over 70 % of data-migration initiatives turn out to be more complex than expected, with many exceeding budget or schedule.
Big Bang Approach: Migrating all systems, modules, and users to the new platform at once enables a streamlined deployment but heightens risk if problems occur. It’s best for smaller organizations or those adopting only a few functional areas.
Pros: Tech Target states that the main advantage of the Big Bang approach is speed and simplicity; everything is implemented in one phase, so employees can start using all the new system features immediately. This allows for a faster transition and quicker access to improved functionality across the organization.
Cons: Panorama Consulting Group discusses the key drawback of the Big Bang approach as the lack of time to identify and fix bugs and compatibility issues before going live, which can lead to major problems once the system is active.
Phased or Incremental Approach: Data is migrated in stages (by module, business unit, geography, or timeframe). Each migration chunk is validated before moving to the next. This reduces risk, gives more flexibility, and allows adjustments along the way. The challenge is managing the “two systems” scenario and ensuring proper data synchronization.
Pros: Tech Target states that a phased ERP implementation rolls out the system in stages, allowing employees to access new features gradually and provide feedback that informs future phases. This approach keeps each phase’s scope smaller, making it easier to manage budgets, resources, and unforeseen issues. It also shortens the time key team members are needed, reducing the risk of losing critical personnel mid-project.
Cons: Panorama Consulting Group says that a phased ERP implementation can be more expensive since both legacy and new systems run simultaneously, increasing operational costs. However, this approach often leads to higher user adoption because employees have more time to adjust and learn. By rolling out modules gradually, teams can receive focused training on specific functions, improving confidence and long-term success.
Once you’ve chosen your strategic approach, the next phase is deeply tactical: ensuring your data is in the right shape, in the right place, and validated for go-live.
Why data quality, mapping, and validation matter:
Even the best migration strategy won’t deliver if the source data is messy or the mappings are wrong. Oracle states that up to 80 % of migration projects fail due to misconceptions, challenges, and the complexities of these projects.
Qlik defines Data Migration as: “moving data between storage systems, applications, or formats,” and that this typically includes “prepping, extracting, transforming, and loading the data.”
Key tasks
Data audit and cleansing: Identify duplicates, inconsistencies, obsolete records, and legacy junk. For example, in a manufacturing context, you may have product master records that haven’t been used for years but still exist.
Data mapping and transformation: Define what data from your legacy systems maps into the IFS Cloud data model: field-to-field, business rules, dependencies. For example, you might need to transform legacy work order statuses into the IFS Cloud status taxonomy.
Validation & reconciliation: After migrating a chunk, validate that everything made it over properly, the volumes match, key business reports reconcile, and the business users accept the data.
Governance and ownership: Assign data owners, define the “single source of truth”, and establish rules for ongoing maintenance once the system is live.
Did You Know?
According to research by Celonis, in system migrations, two-thirds of projects produce a negative ROI because the business case was not clearly aligned up front.
Another stat from Celonis, more than half of system migrations fail outright.
The process of data migration requires strategic planning, effective communication, and time management.
Having strategy and data hygiene in place, the final major phase is execution, migrating the data into IFS Cloud and managing the transition so your go-live is clean (i.e., minimal disruption, accurate data, rapid user adoption).
Step-by-step advice
1. Dry runs/pilot migrations: Before the final migration, run pilot migrations with subsets of data and business users. Validate performance, check business reporting, and get feedback.
2. Final cut-over planning: For your go-live, establish a clear cut-over window, downtime planning, roles and responsibilities, and contingency options. If you’re following a phased model, make sure the final transactional data migration is orchestrated to avoid business interruptions.
3. User acceptance and change management: Even though this blog focuses on technical data migration, remember that the human side matters. Train users, update reference documentation, communicate the data changes, and explain what they mean for everyday workflows.
4. Post-go-live validation and monitoring: After you go live, monitor key reports and data flows. Make sure there are no data gaps and that business processes are running end-to-end in IFS Cloud. Establish ongoing support for data issues.
5. Decommission legacy systems: Once you’re confident the data is live and stable in IFS Cloud, retire your legacy systems (or archive them) to eliminate confusion and reduce maintenance overhead.
Tip from Forseti’s ERP Experts
When moving to IFS Cloud, treat this not as “system cut-over” but as “business transformation”. Data migration is the hinge between the past and the future: use it to rationalize and clean your legacy footprint, don’t simply duplicate old issues into the new system.
Migrating from legacy systems to IFS Cloud is more than a technical upgrade; it’s an opportunity to clean up data, streamline operations, and set a strong foundation for future growth. With the right strategy and execution, your business can achieve a seamless, clean go-live.
Forseti Solutions specializes in guiding companies through every step of this process to ensure successful data migration.