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Rubix-developed

Feasibility × Impact Matrix.

Use-case prioritization on four dimensions.

Category
Rubix-developed
When we recommend it

Every Phase 01 engagement. The matrix is also useful in Phase 00 as a quick screen on whether a client has plausible Phase 02 candidates at all.

What it is

The framework, what it covers, and the problem it addresses.

A four-dimensional scoring rubric for AI use cases: technical feasibility (can the model do this), data readiness (does the data exist in the right form), organizational readiness (will the operating model absorb it), and impact magnitude (does it move the P&L if it works). Each dimension scored 1-5 with anchor descriptions. The matrix surfaces the use cases that score well across all four, usually 5-8 from a long list of 20-40.

Why it matters

The reason this framework exists in the Rubix toolkit, and why omitting it is the wrong shortcut.

The most common Phase 02 failure pattern is building the wrong use case. Not technically wrong; strategically wrong. The team picks something exciting (high impact) without checking whether the data exists (low data readiness) or whether the operating model can absorb the change (low organizational readiness). Pilots succeed and never scale. The matrix is what prevents that.

In the Kingdom and the GCC

Regional context. PDPL, SDAIA, Vision 2030, Saudization, and the operating realities that shape how this framework lands here.

In Saudi enterprises, the data-readiness and organizational-readiness scores often diverge sharply from technical feasibility. Many organizations have strong infrastructure (high feasibility) but fragmented data ownership (low data readiness) and limited internal change capacity (low organizational readiness). The matrix is what produces a roadmap the organization can actually execute, rather than a roadmap that looks good on paper.

How Rubix applies it

The phases of the Rubix Way where this framework is operationalized, and what we do with it there.

Phase 01

Strategize. We score 20-40 candidate use cases on the matrix during Phase 01. The 5-8 candidates that score well across all four dimensions become the Phase 02/03 portfolio. The rest are documented as deferred or declined, with the reason explicit.

Common pitfalls

The failure modes we have seen up close, written so the next engagement avoids them.

  • 01

    Scoring impact magnitude in isolation. A use case that scores 5 on impact and 2 on data readiness is a 3-year initiative, not a Phase 02 candidate.

  • 02

    Letting executive enthusiasm override the matrix. The matrix exists precisely because executives have favorite use cases that fail at the readiness layer.

  • 03

    Not refreshing the matrix as Phase 02 progresses. Use cases that were 3/5 on data readiness become 4/5 once the platform is built. The portfolio updates accordingly.