Oliver Wyman

On connaît souvent un métier avant de connaître ceux qui le font. Pour nos vidéos de recrutement, on a décidé de faire l'inverse. Quelques-uns de nos collègues racontent leur quotidien chez Oliver Wyman et ce qui, selon eux, fait la différence : les personnes, l'entraide, l'exigence, mais aussi la convivialité. Une immersion pour découvrir Oliver Wyman de l'intérieur, à travers celles et ceux qui le font vivre au quotidien. Envie de nous rejoindre ? Découvrez nos opportunités de carrière.

On connaît souvent un métier avant de connaître ceux qui le font. Pour nos vidéos de recrutement, on a décidé de faire l'inverse. Quelques-uns de nos collègues racontent leur quotidien chez Oliver Wyman et ce qui, selon eux, fait la différence : les personnes, l'entraide, l'exigence, mais aussi la convivialité. Une immersion pour découvrir Oliver Wyman de l'intérieur, à travers celles et ceux qui le font vivre au quotidien. Envie de nous rejoindre ? Découvrez nos opportunités de carrière : https://owy.mn/3N0LOFh #OliverWymanCareers

Having proprietary data is one thing. Turning it into a competitive advantage is another. In an AI-driven market, the companies best positioned to win will be those that put their data to work, improving products, decisions, and customer outcomes in ways competitors cant easily replicate. Steven Eisenberg, Marc Stanke and I explore what it takes to build a truly defensible data moat in our latest article. Read more: https://lnkd.in/dFyBTUKR;

"Proprietary data” is one of the most common answers companies give when asked what protects them from AI disruption. But having proprietary data isn’t the same as having a moat. The real questions are: Is the data valuable? Is the advantage defensible as AI improves? And can the company actually put the data to work? In our latest piece, George Tan, Marc Stanke, and I look at where data moats hold up, where they break down, and what investors and operators should pressure-test. Read more: https://lnkd.in/gC7vVzNx

Proprietary data has long been considered a powerful competitive moat. But AI is challenging that assumption. As AI makes once-scarce information easier to replicate or replace, even companies with extensive proprietary datasets may find their market position under threat. For investors, the question is no longer just what data a company owns, but whether it can turn that data into lasting value. In our latest article, Oliver Wyman experts examine what separates truly defensible data moats from those vulnerable to AI disruption, and share three critical tests investors can use to pressure-test their investment theses. Read more: https://owy.mn/4rZCftu

The strongest data moats don’t just get bigger. They get stronger with use. More customers, interactions, and workflow ownership can create an advantage that becomes harder to replicate — but only if the data actually improves products, decisions, or outcomes. In our latest article, Steven Eisenberg, George Tan, and I explore what makes a data moat durable in an AI-driven market. Read more: https://lnkd.in/gkeJFWfw