Transforming data from a liability to an asset
Decades of tactical workarounds, deferred housekeeping, poor data definition, and limited documentation have left most large organisations sitting on data that is incomplete, obsolete, inconsistent, and ungoverned. That data will not power an AI strategy. It will sabotage it, and destroy trust in the process.
The good news is that any significant transformation creates a prime opportunity to fix this: an S/4HANA migration, a platform consolidation, even a standalone governance review. Improving data quality, relevance, and governability is no-regrets work. It pays for itself regardless of what comes next.
This is what Kiros does. We conduct deep analysis of legacy systems, SAP and beyond, across three dimensions.
Actual data quality: we identify what is broken and fix it through targeted remediation and enrichment.
Relevance: obsolete and redundant data does not just add noise; it confuses AI outputs and jeopardises reconciliation if you migrate to S/4HANA. We help you remove it.
Governance: not a textbook governance model, but one that works within the reality of your organisation's culture, structures, and ways of working.
From that analysis, we build something practical: clear ownership, proactive stewardship, data standards, and measurable outcomes that make data quality stick over time. If you then need us to execute the migration itself, we do that too.
The ultimate no-regrets investment to enable AI Success
One pattern determines SAP migration success above all else: early, deliberate work in three areas.
Upfront analysis. Deep assessment of legacy SAP and non-SAP data: master data, where it's mastered, what's relevant, what isn't.
Targeted cleansing. A realistic plan to prepare relevant data for migration, accelerated by purpose-built tooling.
Practical governance. A model designed for adoption, not resistance: built around how each organisation actually manages data.
This upfront investment pays for itself. Repeatedly.
It surfaces hidden commercial value. The analysis gives functional teams visibility they've never had. One client used it to reduce payment terms from 130+ days to ~30: an eight-figure working capital improvement.
It cuts infrastructure and AI costs. Relevant data means a smaller S/4HANA footprint and sharper AI performance. At one client, 78% of materials, BOMs, recipes, and associated transactions had been untouched for five years. Validated, archived, excluded, delivering material infrastructure savings.
It de-risks the migration. Clean, governed data simplifies execution, strengthens source-to-target reconciliation, and reduces post-cutover operational risk. We have seen it save considerable cost, and prevent the data quality failures that derail go-lives.