Strategic advice to leverage new technologies

Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.

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Why do technology projects continue to fail at such an astounding rate? Why has the technical debt metaphor outgrown its original intent and evolved as a company-wide concern? Find out in this latest edition of The Cutter Edge!
The goal of the customer experience equation is to develop a connection. Connection is achieved through two factors. The first is content and represents the product or service that you sell. The second factor is context, which represents everything surrounding both your content and your cus­tomer.
This issue of CBTJ addresses the tactical, operational, strategic, and human reasons that allow technology projects to fail and offers guidance and solutions to mitigate the possibility of failure.
Research establishing a link between analytics and business performance remains in a nascent stage, but the popular press is rife with examples of firms predict­ing the viewing and shopping habits of individuals, providing personalized healthcare-related services, and harnessing real-time agricultural data to increase productivity and efficiency. Nevertheless, when defined as the use of advanced mathematics to identify, explain, or predict patterns in data to improve confidence in business decision making to create value, the majority of analytics projects fail to deliver or have low success rates. This Advisor explores some of the reasons for that failure.
The biggest challenge organizations face while starting an Agile transformation is not the learning, but the unlearning. This Advisor focuses on Agile anti-patterns around roles, events, artifacts, and overall cultural mindset.
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.
Agility initiates and accepts changes to business processes, and artificial intelligence (AI) further enables agility by providing timely updates on the status of a business to facilitate decision making. This Advisor explores Agile principles and their corresponding impact on technology-driven change management.
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.”