But like gold, it has to be refined to realise its true value. Through Golden Record, I help large enterprises turn fragmented data into a single, trustworthy source — the foundation for AI you can actually deploy.
Most enterprises treat data management as a hurdle to clear during system upgrades — a checkbox before go-live. I treat it as the operating system itself.
I design and deliver the data architectures that turn fragmented operations into unified, AI-ready enterprises. Across S/4HANA migrations, governance programmes, and finance-controlled rollouts, I've governed 80+ data objects, corrected hundreds of thousands of errors, and led delivery teams of 60+. Not in theory. In production.
Most AI initiatives fail not for lack of GPUs or talent, but because the underlying data is fragmented, inconsistently governed, and of uncertain quality. No LLM is trained on your customer hierarchies, pricing logic, or operational vocabulary — and generative AI amplifies the garbage in, garbage out principle at scale.
I do the unglamorous work that comes before AI works. Audit, govern, harmonise. Without it, your AI strategy is expensive theatre. With it, the next-generation capabilities your board has signed off on actually deliver.
Most enterprise AI programmes fail because the first three steps are skipped. Here's what I run, in order.
Find the silos. Identify governance gaps and quality risk.
RCM-aligned controls. Named data owners with real authority.
Cleanse. Standardise. Consolidate. Audit-ready.
RAG architecture. Prove ROI before scale.
On foundations that won't break.
Steps 4 and 5 only work if the first three are done. Most consultants skip to 4. I won't.
Interim Director of MDM. Partnered with the D&A / IT&D Board to design the enterprise-wide digital strategy and global operating model. Defined and validated the SAP software Bill of Materials (MDG, Datasphere, Syniti) as the digital core for an AI-ready enterprise.
Director of Master Data Management on the IT Leadership Team, reporting to the Group CIO. Steering committee member alongside Executive Leadership and country MDs. 80+ data objects governed across 150 business units and 44 disparate ERP estates. £2m in cost reductions through a Data Centre of Excellence in Vilnius.
Most senior Reckitt role. Authored supplier governance policies aligned to Reckitt's Risk & Controls Matrix, embedded across 60+ markets. Concurrently led an 8-developer Agile squad on Microsoft Cloud (Power BI, Power Platform, Azure) — digitising control workflows and automating manual operations. Earlier: master-data lead on the EU REACH programme — 9 months, 64 tollgates, 43 factories, 500K+ errors corrected.
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