Bad data doesn't get better when you move it to SAP.

Data cleansing is identifying and correcting inaccurate, incomplete, or duplicate records before they are loaded into the new system. Poor quality data in a new SAP environment undermines user confidence, reporting accuracy, and process automation from day one — and the problems compound over time. Functional teams typically own this responsibility in their domain.

Not all data needs to move. A data migration strategy should categorise data by quality, relevance, and business need. Historical data that will not be used operationally in the new system can be archived rather than migrated — significantly reducing migration complexity and risk. The decisions require business owners, not just the technical team.

There is no standard timeline — data migration duration depends on the volume and complexity of data objects in scope, the quality of source data, the number of migration iterations required, and the migration approach chosen. What is consistent is that it takes longer than most organisations plan for, and that starting the data workstream late is the single most common cause of go-live delays.

As a general rule, data migration activity should begin in the Discover phase — well before system build starts. Cleansing alone can take months depending on data quality. Migration iterations typically run three to five times before a clean cutover load is achieved. Organisations that treat data migration as a final-phase activity consistently encounter delays and quality issues that could have been identified and resolved much earlier. Limelight's data readiness assessment establishes a realistic migration timeline at the outset — so the programme plans around the actual data challenge, not an optimistic assumption.

Master data governance is the set of policies, ownership structures, and processes that ensure your core data — materials, vendors, customers, organisational structures — remains accurate, consistent, and trusted after go-live. Without it, data quality degrades quickly as teams make changes without standards or accountability, and the reporting and automation your SAP investment was supposed to deliver becomes unreliable.

Most organisations focus governance effort on getting data right for go-live. The harder discipline is keeping it right afterwards. Limelight establishes master data governance as a formal workstream — with defined data owners, clear standards, and the processes to maintain quality as the business evolves.

Limelight's data practice sits on the client side — independent of the delivery partern. Where the partners data team is responsible for the technical migration process, Limelight owns the client-side obligations: data strategy, governance, cleansing, ownership, and readiness assessment. The two teams work in parallel, not in competition.

In practice, strong client-side data leadership makes the SI's data delivery faster and more straightforward — because requirements are clearly defined, cleansing is completed on time, and data ownership decisions are made by the right people before the partner needs them. Limelight provides the independent data governance that ensures your interests are protected throughout.

The first step is a structured consultation with Graham Stewart, Limelight's Data Practice Lead — typically sixty minutes in which we understand your current data landscape, your programme timeline, and where the greatest data risks lie. There is no commitment required. If it's useful, we will also recommend completing the Data Readiness Scorecard beforehand so the conversation starts with a clear picture of where you stand.

Most data conversations start too late — after the delivery partner is engaged and the programme clock is already running. The earlier Limelight is involved, the more value the data workstream adds. Whether your programme is at Launchpad stage or already in delivery, start with a conversation and we will tell you honestly what we think.