As organizations accelerate AI adoption and expand analytics capabilities, many still struggle to execute their data strategies due to unclear operating models, siloed decision-making, and ...

How organizations can do more with their data to realize business goals and achieve a sustainable competitive advantage. In partnership withWNS Triange In 2006, British mathematician Clive Humby said, ...

Only 4% of organizations have fully aligned operating models to support their strategic goals. AI is now the strongest driver of operating model redesign, cited by nearly 70% of executives.

In 2026, data governance has stopped tiptoeing around the edges of organizational strategy and stepped directly into the ...

Buy-side firms are consistently faced with burgeoning volumes of data, necessitating adept management of expansive data extractions, a task fraught with intricacies and considerable costs. Arthur Orts ...

Why advanced technology accelerates dysfunction when decision rights, workflows, and culture aren’t built to execute.

It’s been said that AI is only as good as the data fueling it. And that’s true—to an extent. Having good data is important, but it is also useless if it’s inaccessible. This explains why building the ...

For decades, banks have wrestled with fragmented regulatory data by investing billions in lakes, warehouses and point solutions that promised control but delivered more silos. What financial ...

In the dynamic realm of software development, the effective implementation of a product operating model is crucial for companies striving to innovate and consistently deliver value to their customers.

Management and technology consultancy BearingPoint has released a new research study, “Future-ready by design: Reinventing operating models for the AI era.” Based on a survey of nearly 400 C-level ...