Problems Solved. Value Delivered.

• Adopting A Product First Approach To Data & AI
• Connecting Strategy With Execution
• Developing Value-Centric Product & Infrastructure Roadmaps

Continuous transformation must reach down into strategy implementation and execution. Without that connection, strategy is aspirational. The maturity models support implementing continuous transformation and technical strategy across 4 key pillars.

This is the most challenging connection to make because it spans across products, business units, customer segments, and technology waves. The big picture of continuous transformation is massive, and the maturity models create alignment with a lightweight framework set.

The business’s data and AI capabilities continuously transform to deliver higher-value products. The capabilities maturity model keeps that development aligned with products and initiatives. This framework supports value vs. technology-focused decisions about capabilities development.

Products continuously transform to seize opportunities with each technology wave. The data product maturity model explains how digital products evolve into data, analytics, and advanced model-supported products. This framework supports decision-making about initiative planning. Products can be built today with space for the inevitable transformations coming next and monetized at each phase. Incremental delivery creates incremental returns so transformation is sustainable, and costs are minimized.

Data gathering capabilities transform to seize opportunities as product lines grow into platforms. The data maturity model supports moving the business from opaque to transparent. It connects data engineering and monetization.

The way people work with technology, especially data and advanced models, must be taken into account. Breaking initiatives down to support internal users’ and customers’ reliability needs is supported by the human-machine maturity model.

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