Turn data from a recurring argument into an asset the business trusts. We set data strategy against the decisions you need to make, put proportionate governance and ownership in place, and fix the master data that every system and AI model depends on.
Book a confidential conversationERP, CRM, billing and AI programmes all stall on the same thing: data nobody owns, definitions that differ between teams and quality problems discovered only during migration. Strategy documents describe a data driven future while the monthly report is still reconciled by hand.
Good data strategy is short, tied to decisions and owned by the business. Good governance is light enough that people follow it.
A clear view of the decisions, products and regulatory needs your data must support, the gaps today and a costed roadmap to close them.
Owners and stewards for critical data domains, agreed definitions, quality measures and a governance forum with the authority to decide.
Customer, product, supplier and asset master data cleansed, structured and kept clean, ahead of ERP, CRM or AI programmes.
We begin with a short diagnostic of the data behind your most important decisions and systems, then agree a plan that fixes the highest value problems first and builds governance around them.
Scope and price are agreed up front, on a fixed price or a day rate.
Talk to us about dataAI models and copilots are only as good as the data behind them, and regulators expect you to know what data your AI uses and where it came from. We align data governance with AI governance so you can adopt AI with confidence. Our data governance framework guide sets out the structure we use as a starting point.
Data strategy sets out what your data must do for the business and how you will get there. Data governance is the ownership, standards and processes that keep data fit for purpose day to day.
At least for the data you are migrating. Naming owners and agreeing definitions before migration is far cheaper than discovering the problems in testing.
The processes and tools that keep core records such as customers, products, suppliers and assets accurate and consistent across systems.
Only once the process and ownership are clear, and we will tell you if a spreadsheet and a clear owner will do for now.
A fixed price for the diagnostic and an agreed price or day rate for what follows.
A data strategy sets out how an organisation will collect, manage, govern and use its data to meet its goals: what data matters, who owns it, the standards it must meet, the platforms it lives on and how it turns into decisions. A data and analytics strategy extends that to the reporting, analytics and AI the business will build on top.
Because systems, reporting and AI all depend on data that is owned, trusted and consistent. Without a data strategy, each programme fixes its own data problems and the same issues come back on the next one.
Tell us which decision or programme is being held back by data, and we will tell you where we would start.
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