SAP Migration · 5 min read · April 2026
What belongs in an SAP migration risk register
By Thinklytics Partners, SAP S/4HANA Practice
An SAP migration risk register should weight the data and reporting risks most heavily, because they cause most failures. Score each, assign an owner, and re-score.
An SAP migration risk register should weight the data and reporting risks most heavily, because they cause most failures. Score each risk on likelihood and impact, assign an owner, and re-score as readiness work drives the data risks down.
What separates a working register from a filed one
Scoring is the easy part. These are the habits that make the register change a decision.
- Weight data and reporting highest. They are the most common cause of stalls and overruns, so they earn the most attention and budget.
- Score likelihood and impact into one combined number. Sort by that score and the top rows almost always include several data and reporting risks.
- Put a named person against every risk. Not the program in general. A risk with no accountable owner does not get mitigated.
- Re-score at each program stage. Readiness work should visibly pull the data risks from red into manageable.
- Setting the go-live date before the data is measured. Committing a date and budget before measuring the data is the highest-scoring risk on most registers.
- Writing it once and filing it. A register nobody updates is theater. It changes nothing about how the program runs.
Source: Thinklytics SAP migration risk model, 2026.
Why most registers are wrong
Most registers over-weight platform and integration risks and under-weight data and reporting, which is backwards. Data is the most common cause of stalls and overruns, so it deserves the most attention and budget.
The four quiet killers of an S/4HANA migration
None of these show up in a sandbox demo. They surface at conversion, reconciliation, or the first close.
- Duplicate master data. Breaks reconciliation and migrates as separate records unless stopped.
- Dark data. Unused historical records that inflate volume, cost, and conversion time for no value.
- Custom code that breaks. ABAP written against the old tables fails on the simplified data model.
- Reporting that goes dark. BW models and downstream dashboards snap when the data structure changes.
Source: Thinklytics SAP data readiness practice, 2026.
What to capture
For each risk: a category, a description, a likelihood score, an impact score, a combined score, an owner, and a mitigation. Sort by combined score. The top risks almost always include several from the data and reporting categories.
What a weighted SAP migration risk register looks like
Score likelihood and impact, sort by combined score, assign an owner. The top rows are almost always data and reporting.
| Risk | Category | Weight | Owner |
|---|---|---|---|
| Date and budget set before data measured | Data | Highest | Program sponsor |
| Duplicate master data breaks reconciliation | Data | High | Data lead |
| Reporting goes dark at cutover | Reporting | High | Analytics lead |
| Custom code fails on the new model | Custom code | Medium | ABAP lead |
| Integration interface defects | Platform | Medium | Integration lead |
Source: Thinklytics SAP migration risk model, 2026.
Make it live
Re-score at each program stage. A good readiness program should visibly pull the data risks from red into manageable before a go-live date is ever set. A register you update is a tool. One you write once and file is theater. The Analytics Truth Audit gives you the scored, owned register to start from.
Frequently asked questions
What belongs in an SAP migration risk register?
Each risk with a category, description, likelihood and impact scores, a combined score, an owner, and a mitigation. The data and reporting risks should carry the most weight.
Why weight data risks most heavily?
Because data is the most common cause of stalls and overruns. Registers that over-weight platform and integration risk miss where migrations actually fail.
How do we score risks?
On likelihood and impact, multiplied into a combined score. Sort by combined score and the top items almost always include several data and reporting risks.
How often should we update the register?
At each program stage. A good readiness program visibly pulls the data risks from red into manageable before a go-live date is set.
What is the most common high-scoring risk?
Committing a date and budget before measuring the data, plus duplicate master data and reporting that breaks at cutover.
Who owns each risk?
A named person, not the program generally. A risk without an accountable owner does not get mitigated.
Topics covered
- Risk Register
- Migration Risk
- S/4HANA
- Program Management
Frequently asked questions
What belongs in an SAP migration risk register?
Each risk with a category, description, likelihood and impact scores, a combined score, an owner, and a mitigation. The data and reporting risks should carry the most weight.
Why weight data risks most heavily?
Because data is the most common cause of stalls and overruns. Registers that over-weight platform and integration risk miss where migrations actually fail.
How do we score risks?
On likelihood and impact, multiplied into a combined score. Sort by combined score and the top items almost always include several data and reporting risks.
How often should we update the register?
At each program stage. A good readiness program visibly pulls the data risks from red into manageable before a go-live date is set.
What is the most common high-scoring risk?
Committing a date and budget before measuring the data, plus duplicate master data and reporting that breaks at cutover.
Who owns each risk?
A named person, not the program generally. A risk without an accountable owner does not get mitigated.