Digital Transformation Advisory
Every digital transformation we've seen fail in the last five years has failed for the same reason: the AI tool was bought before the data was clean, or the automation was built before the process was understood. We start somewhere different.
What we hear from operators
The problems we solve
The roadmap exists. Nothing is getting built.
Most organisations have a digital transformation strategy document — produced by a big four firm, blessed by the board, filed somewhere on SharePoint. It identifies the right priorities. It doesn't explain how to sequence them, what the first 90-day deliverable is, or who owns what. Two years later, the strategy is still the strategy. A few pilots have happened. The transformation hasn't.
AI was deployed before the data was ready
Generative AI tools, predictive models, and automated decision systems all share the same dependency: clean, connected, current data. When organisations deploy AI on top of fragmented, unreliable data, they get AI that produces confidently wrong outputs. The failure of the AI gets attributed to the technology. It's a data problem. The AI just made it visible.
Technology is being selected before the problem is defined
Vendor demos create technology pull. A Databricks demo impresses the CDO. A Salesforce pitch impresses the CCO. Technology decisions get made based on capability demonstrations, not on a clear definition of the problem being solved, the alternative options evaluated, or the total cost of ownership over three years. The result is a technology portfolio that doesn't fit together and doesn't match the organisation's maturity.
By market
Digital Transformation — market-specific pages
Each page below covers what digital transformation advisory looks like specifically in that market — the local ERP landscape, compliance context, and the operational patterns we actually see there.
Singapore & Malaysia
United Kingdom
North America
By industry
Digital Transformation — industry-specific pages
How digital transformation advisory applies to the specific systems, metrics, and operational challenges of each vertical.
Manufacturing
Most manufacturing plants we walk into have four or five systems that don't talk to each other: SAP or Oracle for production orders, a separate MES for floor execution, a quality system that's often standalone, and spreadsheets filling every gap in between.
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EPC (Engineering, Procurement & Construction)
EPC data environments are uniquely complex: long project timelines, multi-currency and multi-jurisdiction reporting, complex contractual structures (lump sum, reimbursable, target cost), and a fundamental tension between the project management system (Primavera, MS Project) and the cost management system (Oracle, SAP PS).
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Technology stack
Start with a conversation, not a proposal
First call is 45 minutes. No deck. We ask about your systems, your team, and your most pressing operational problem. You get a clear view of where the gap is and what closing it looks like.