When a software project stumbles—or ultimately fails—it can have a range of negative consequences, from lost and unrecoverable resources to a blow to team morale. It can be tempting to blame a failed ...

Several years ago, I was hired as IT manager at the convention center of a well-known Gulf Coast metropolis. There was plenty of action, with one big show after another. For the first few weeks, my ...

Learn how NVT Phybridge helps schools modernize safely and affordably, avoiding rip-and-replace to deploy IP devices faster, ...

The world of enterprise technology is painted with promises of transformation, but behind the glossy presentations and pilot ...

The Project Management Institute and The Agile Alliance spent over 20 years competing for project funding, certifications, training dollars and credibility. Their agreement to form The PMI Agile ...

Even as we emerge from generative AI’s tire-kicking phase, it’s still true that many (most?) enterprise artificial intelligence and machine learning projects will derail before delivering real value.

Enterprise applications are the lifeblood of modern business, driving operational efficiency, enabling smarter business decisions and reducing technical debt. Yet, many strategies continue to fall ...

The vast majority of enterprise AI projects fail due to data fragmentation, unclear business goals, piecemeal tools, and ...