In SAP SuccessFactors projects, teams are often focused on transformation outcomes: improved experience, efficiency, better process alignment, accurate, actionable analytics. Yet the accuracy and integrity of data is what underpins every transformation outcome – and it’s often forgotten until it’s too late.

Let’s take a typical scenario. A sponsor greenlights the project and assigns a program lead. Data is considered a tactical stream – so it’s assigned to internal HR and IT teams. The system integrator provides templates for data input, but internal teams are buried in BAU and design workshops. Mock 1 approaches, and the load fails. Fields are missing, structures are misaligned, and the system integrator escalates the issue. Suddenly, a six-week catch-up effort begins, derailing confidence and stretching already overloaded resources. What’s worse, without a repeatable process and clear project resources accountable for the data stream, Mock 2 approaches rapidly and compounds the risk. Now it’s a red item on the project risk register, with leadership asking why this wasn’t flagged earlier.

This is avoidable. But only when sponsors understand that data migration is not just a backend activity – it’s a foundational part of ensuring the platform delivers as intended.

Sponsors don’t need to be data architects. But they do need to be informed, engaged, and ready to act early – because decisions made in the very early weeks can make or break the implementation.

The Hidden Workstream that can Make or Break Your SAP SuccessFactorsProject. here

We’ve seen well-intentioned sponsors fall into these common traps:

• “We’ve been given all the load templates – it’s just a case of populating them.”
  This is one of the most common misconceptions. Populating load templates isn’t a simple task. It involves interpreting the requirements, extracting from multiple legacy sources, cleaning and cleansing inconsistent or outdated data, transforming it into the new data structures, reconciling totals across systems, resolving gaps, and iterating through multiple rounds of validation and reconciliation. It requires time, process discipline, and support – not assumptions.
• “The system integrator will manage it.”
  Unless explicitly included in contract negotiations, SI partners typically only provide load templates and technical execution. It is your responsibility to source the data and provide it to the project, load ready. They don’t cleanse, structure, or validate your legacy data.
• “Our HR or IT team can own it.”
  HR and IT are critical stakeholders – but they often lack the capacity, methodology, and tools to lead a complex data stream. HR teams are closest to the business rules and operational detail, but they’re already spread thin across design workshops, communications, and managing business-as-usual. IT teams can assist with system access, data extracts, and infrastructure, but they often lack context around the HR data, field definitions, and global policy nuances. Without a dedicated data lead, structured framework, and accountability, the data stream drifts. The result is reactive firefighting during mock cycles and escalating tension between delivery partners. Sponsors must resist the temptation to ‘assign data to HR and IT’ and instead ensure it is treated as a distinct and resourced stream of work.
• “We’ll deal with data after design.”
  Unfortunately, data issues often emerge during design and testing. Waiting until build puts you behind before you’ve started.

You don’t need to write data rules or clean spreadsheets. But your leadership is critical in the following ways:

Ensure there is a data migration strategy

Sponsors should expect the data team to work from a clear and structured migration strategy that defines how data will be extracted, cleansed, transformed, validated, and loaded across each mock cycle. If your internal team doesn’t have one, ask your implementation partner if they can provide a baseline template. A documented approach helps avoid missed steps, enables progress tracking, and creates consistency across cycles. Without it, you’re relying on ad hoc decisions – which inevitably lead to rework and delays.

This should be the first action a sponsor takes when engaging with the data stream. Before assigning roles or setting timelines, ensure the team knows how they intend to approach the migration – not just technically, but operationally. A strategy brings clarity, structure, and repeatability to a stream that otherwise risks becoming reactive.

Approve dedicated resourcing

Many projects underestimate how much time is required for data readiness. SMEs must extract, map, cleanse, and validate data while participating in design and maintaining BAU. Sponsors who proactively assign and protect these resources help prevent backlogs that otherwise surface late in testing.

Support timeline realism

Compressed data timelines are one of the most common failure points. Sponsors can challenge unrealistic assumptions and support a timeline that allows for at least two mock loads, including early simulations. This also creates space to uncover structural issues that often get missed in design.

Clarify accountability

Data sign-off isn’t always straightforward – especially in global programs. Sponsors help by defining who owns what (e.g., local vs. global, HR vs. payroll), how decisions will be made, and what success criteria apply. This avoids late-stage conflicts and streamlines go/no-go decisions.

Here’s when sponsors are most needed during the migration stream:

Treating data migration as a technical task misses its true nature: it’s a business-critical, cross-functional, and time-bound initiative that directly affects user trust and go-live integrity.

Data needs its own:

• Leadership (a data migration lead or external readiness partner)
• Methodology (profiling, mapping, rule transformation, reconciliation)
• Governance (decision rights, sign-off roles, change control)
• Schedule (mock cycles, dry runs, cutover planning)
• Controls (security, privacy, access management)

Programs that assign this as a part-time task to already-busy SMEs often find themselves slipping behind without a clear way to recover. Sponsors should expect – and demand – that data migration is treated with the same seriousness as testing, change, and integration.

We often hear: “Our HR SMEs can prepare the data.”
This is often a red flag. Here’s why:

1. HR SMEs are already stretched
   In one program, HR leads were managing change, communications, and policy reviews. Data work fell through the cracks until Mock 1 exposed major gaps – forcing a three-week delay.
2. They don’t know the SuccessFactors data model
   SSF introduces new structures – like job classification or dynamic security groups. Without upfront guidance, HR teams can’t reliably map legacy fields into SSF’s requirements.
3. SIs expect finished data, not guidance
   One sponsor assumed the SI would “help clean the data.” In reality, the SI rejected loads that didn’t match template specs, causing friction and emergency meetings to realign expectations.
4. Data migration is a specialised discipline
   It requires profiling tools, structured cleansing cycles, transformation rules, and repeatable cutover rehearsal. Sponsors should treat it like testing or change – not an ad hoc admin task.
5. IT support does not equal data leadership
   IT teams often help with extracts and environments but lack context on HR processes. We’ve seen migrations stall because IT couldn’t interpret legacy job codes or contract rules.
6. Mock 1 often exposes unpreparedness
   In almost every project, Mock 1 is the wake-up call. The sponsor’s job is to ensure the team is already simulating loads and reconciling outputs before formal cycles begin.
7. Security and privacy are real concerns
   In one public sector project, access to HR and payroll data was loosely managed in early stages. Once auditors became involved, retroactive controls had to be imposed – costing time and credibility.

1. Do we know who owns each domain of HR data?
2. Have we profiled our legacy data for quality, completeness, and alignment?
3. Who is managing the data stream, and what framework are they using?
4. Have we planned for secure handling of sensitive HR/payroll data?
5. What happens if our data isn’t ready for Mock 1 or cut-over?
6. Do we have a clear migration strategy?
7. Have we established a repeatable method to extract, cleanse, and transform the data to support each mock load?
8. Can we track and audit the data migration process to monitor progress and identify risks early?

These questions often surface too late. Being able to answer them with confidence ahead of time is what separates well-governed projects from high-stress recoveries.

Data migration success doesn’t come from technical wizardry – it comes from leadership foresight. When sponsors recognize that data underpins every other success factor in an SAP SuccessFactors project, they create the conditions for progress, not panic. From ensuring early strategy to assigning accountable roles and protecting timelines, your engagement sets the tone.

Data doesn’t clean or load itself. Nor will it conform to best practices without structure, resources, and governance. As a sponsor, you don’t need to know every field in a load template. But you do need to ensure that the team is treating data migration as a first-class workstream – one that has a plan, a leader, and the time to execute.

Do this, and you’ll not only reduce risk – you’ll drive confidence, clarity, and the outcomes your transformation set out to achieve.

• Read Our Blog Post Who Owns the Data in SAP SuccessFactors Projects – And Why It Matters
• Review related services and case studies SAP SuccessFactors Data Migration Services
• Test Your Posture SAP SuccessFactors Data Data Readiness Self-Assessment – tailored insights, instant report
• Book a Strategy Alignment Review – Check your data strategy before you start!
• Check out our other services Cloud ERP Solutions for Mid-Market Businesses