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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Take a minute and write an answer to the question, “What is technical debt?” Then read this Advisor and reread your answer — and see if it still makes sense.
When contemplating transformation, you should test your assumptions in a pilot project before betting the farm on them. Such a project should be chosen to have minimal impact on the company in case of failure, should be realistic to build with a small team, and should have high potential for growth.
A common denominator behind failed ML projects is the anthropomorphism of technology. This Advisor explores how, through our tendency toward anthropomorphism, we fail to make a critical distinction in the way humans and machines interpret the world.
Today’s decision support tools are useful but limited — and running algorithms can be computationally expensive. We need statistical shortcuts that simplify incredibly complex equations so that they can run on today’s hardware. This Executive Update highlights the “quantum leap” and how it will end estimating and solve equations in their full complexity. Instead of waiting 24 hours, the solution might only take a second. Within the next 10-20 years, the quantum computing era can lead us to a fully intelligent enterprise.
Myles Suer and John Wills address how to ready data for analysis and competitive advantage. They compare and contrast how legacy companies differ from startup enterprises in terms of data history, governance processes, and management experience. They explore in great depth the importance of properly cataloging data for eventual strategic use. An important lasting lesson of their article is the importance of people in maximizing the business results from any data strategy and technology investment.
Understanding what the transition to sustainability means for the organization is as important in the overall transition as developing the list of what to do. In this Advisor, we explore how leveraging an architectural approach for the initiative begins with understanding the business motivation and translating the motivation into new business and operating models, strategies, objectives, and tactics. The next step is to understand how the newly articulated models, goals, tactics, and so on, fit in the overall enterprise. This is one place that an architect’s big-picture view is invaluable.
Cutter Consortium Fellow Steve Andriole opens the issue with a fundamental question of the times, "What's different about pre- versus post-pandemic technology adoption?" He addresses the timeless imperative for technology leaders to be effective both strategically and operationally.
This Advisor considers a few qualities that an enterprise architect must have. The goal is to provide a starting point for using the framework of architecture quality attributes to understand desirable traits in an architect.