Digital Strategy, Operating Models & Technology Implementation Insight

Expert guidance in business technology strategy, leadership, and implementation in response to digitally-driven disruption of traditional business models. From emerging new operating models to strategies that put data at the heart of your business; overcoming cultural hurdles to what makes a digital leader; achieving enterprise agility to creating a culture that supports continuous experimentation — you’ll be on the cutting edge of the factors that are critical to successful digital transformation.

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We have control over whether AI will be a trusted aide to humanity or a threat. But we need a number of convergent approaches to be able to choose the right path. Ultimately, this amounts to AI governance.
Organizations need to address several issues across four critical steps to make AI work to their best advantage: (1) assess business needs, (2) seek skilled AI people and train staff, (3) identify AI machine learning input data, and (4) choose AI and ML tools. This Executive Update addresses each of the four steps and offers recommendations.

Note from the author: While I often write about organizations and technologies, this Advisor is a bit of a (related and important) tangent, as it focuses on career advancement. Invariably, in working with executives and rising leaders, particularly technology professionals and consultants, conversations turn to career challenges. I have long wanted to author a piece that captures an effective approach that, over many years, has resonated well with business professionals aiming for a promotion and meaningful career advancement.

Discover how fintech can support businesses to not only reopen post-pandemic, but also to develop a robust digital infrastructure that will support growth into the future.
Essential team conditions need to be set up well and are tenaciously difficult to fix later. Having the right talent is one such essential condition, but not all organizations are strategically ready for the problems of finding and selecting top talent, accurately understanding what roles that talent will fill, or building up their own leadership competencies internally.
Technology projects continue to fail at an astounding rate, and the number and cost of these failures are stunning. The contrib­utors to this issue of CBTJ refuse to give up and refuse to accept the notion that failure is a feature.
Cutter Consortium Fellow Robert Charette starts off the issue by looking at failure through an incredibly intriguing lens: what if failure is "the desired outcome of an IT project development and that success is inadvertent"? He then proceeds to set the “conditions” necessary for the pursuit of failure. He then goes on to test — and largely confirm — his “cynical theory.”
Ralph Menzano takes us directly into the C-suite through a series of discussions he had with CIOs and other executives about why so many damn technology projects fail. His article probes some of the causes of failure often ignored by the research community.