A data strategy that names owners, not just ambitions

Agilus provides data strategy consulting to enterprises in South Africa and beyond: we define your data target state, design the operating model that will run it, and sequence the roadmap so the investment survives contact with a CFO. The work is anchored to the Data Governance and Data Architecture knowledge areas of DAMA-DMBOK2.

Why do most data strategies fail?

Because they are documents, not decisions. The typical data strategy names technologies and ambitions — “become data-driven”, “single view of customer”, “AI-enabled” — but not the three things that determine whether anything changes:

A strategy that skips these is shelf-ware within a quarter.

What our data strategy engagement delivers

one

Current-state baseline

Where your data management actually stands — scored across seven pillars against DAMA-DMBOK2 and DCAM using DM360. Not a workshop opinion; a measured position.

two

Target state and architecture

The data architecture, platforms and capability model your business strategy actually requires — including cloud transition where it earns its place, not because it is fashionable.

three

Operating model and stewardship

Data ownership by domain, steward roles people can do alongside their day jobs, a governance forum with teeth, and decision rights that end the arguments.

four

Sequenced roadmap and business case

What to do first, what it costs, what it unlocks — sized in rand terms a CFO can interrogate.

Who is this for?

Common questions

What is a data strategy?

A data strategy defines how an organisation will manage and use its data as an asset: the target architecture, the ownership and governance model, the priority initiatives and the investment case. A good data strategy is measured against a standard — Agilus uses DAMA-DMBOK2 and DCAM — so progress can be tracked objectively.

A typical Agilus data strategy engagement runs six to ten weeks: two to three weeks of baseline assessment, two to three weeks of target-state and operating-model design, and two weeks to sequence the roadmap and business case with your executives.

A data operating model defines who does what in managing an organisation’s data: domain ownership, steward roles, the governance forum, decision rights and escalation paths. It is the difference between a data strategy that changes an organisation and one that stays a document.

Start with a measured baseline

Take the free 6-minute AI Readiness Scorecard

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