FILE 0001 SECTION / HOME CLEARANCE / OPEN

Data is
the new gold.

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.

CLIENTS  DANONE · BMI · RECKITT 13+ YRS  ENTERPRISE FMCG £250M+  PROGRAMMES SHAPED GLOBAL  UNITS GOVERNED OXFORD AI  2026
FILE 0002  /  WHERE I COME IN

Beyond the necessary evil.

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.

Beyond transformation
FILE 0003  /  THE THESIS

AI without the hallucination.

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.

"AI is only as good as the data that underpins it. If you cannot clean, harmonise and standardise your siloed data, your AI models will hallucinate and fail to deliver accurate insights."

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.

Initialise engagement
FILE 0004  /  THE SEQUENCE

The order that works.

Most enterprise AI programmes fail because the first three steps are skipped. Here's what I run, in order.

01 / AUDIT

Map the estate.

Find the silos. Identify governance gaps and quality risk.

02 / GOVERN

Establish ownership.

RCM-aligned controls. Named data owners with real authority.

03 / HARMONISE

Single source of truth.

Cleanse. Standardise. Consolidate. Audit-ready.

04 / VALIDATE

Pilot AI on clean data.

RAG architecture. Prove ROI before scale.

05 / SCALE

Across the enterprise.

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.

FILE 0005 / RECENT ENGAGEMENTS
003 ENTRIES  /  £250M+ SHAPED

Refined for the boardroom.

ENG-001 / DANONE

MDM transformation.

2024 — 2025

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.

ENG-002 / BMI GROUP

£250m S/4HANA global template.

2022 — 2023

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.

ENG-003 / RECKITT

Global Data Owner — Supplier.

2018 — 2022 / Corporate Finance

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.

FILE 0006 / CONTACT

Turn your data into a strategic asset.

Inform intelligent insights. Propel your business towards a thriving future.

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