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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No human could possibly read everything, but a machine can. The best you can do with old-fashioned methods is to hire experts to sample a subset of the relevant data and produce written market insight reports. While these studies can be extremely useful, the resulting analysis is constrained by the amount of data sampled. Many companies already use forms of automation to sort through the data with machines, but, in the end, humans still have to read the data and decide what it means.
As has been our tradition for the last several years, we’ve compiled the five most intriguing articles published by the Business Agility & Software Engineering Excellence practice for today’s Advisor. How did we come up with this list? We chose the articles that garnered the most feedback from Cutter Members. Your questions and comments not only make it possible to create lists like this, they help focus Cutter’s Senior Consultants’ research on the areas that are most important to organizations like yours. So please keep your feedback coming.
As has been our tradition for the last several years, we’ve compiled the five most intriguing articles published by the Business & Enterprise Architecture practice for today’s Advisor. How did we come up with this list? We chose the articles that garnered the most feedback from Cutter Members. Your questions and comments not only make it possible to create lists like this, they help focus Cutter’s Senior Consultants’ research on the areas that are most important to organizations like yours. So please keep your feedback coming.
As has been our tradition for the last several years, we’ve compiled the five most intriguing articles published by the Data Analytics & Digital Technologies practice this year for today’s Advisor. How did we come up with this list? We chose the articles that garnered the most feedback from Cutter Members and clients and those that created controversy among Cutter Senior Consultants and Fellows.
The definition of “Agile architecture” is neither clear nor concrete. Instigated by hype, EA managers may rush to implement fashionable Agile approaches to the detriment of their organizations. Instead, they should strike a balance between up-front planning and agility — because no firms can plan their future in every detail, and not one single company can avoid planning altogether to stay perfectly Agile. As we explore in this Executive Update, EA managers should determine the “golden mean” between total planning and full agility that best meets the specific needs of their organizations.
The authors share part of a research project that seeks to “demystify digital transformation” through findings from interviews with senior leaders at seven firms undergoing digital transformation in a variety of industries. One of their major initial findings is the degree to which senior leaders’ digital mindsets determine the success or failure of these initiatives. The authors highlight the importance of an enterprise-wide view, explaining why a project-by-project approach rarely produces true or lasting digital transformation.
Timothy Chiu discusses how data and digital architectures require improved application security and how the new security framework from the US National Institute of Standards and Technology (NIST) endorses this view. As more and more organizations move rapidly to the cloud, he argues, applications and their associated data are increasingly at risk. With supporting data from multiple sources, Chiu frames the risks through examples of data breaches across multiple industries and geographies. Fortunately, he says, NIST is on the case.
Thomas Gossler writes about how a digital ecosystem platform demands a solid architecture for data and infrastructure on top of which a network of stakeholders can engage in valuable interactions with each other. The journey from a pipeline business model to an ecosystem platform is no small feat, and the author shares the approach he and his colleagues at Siemens Healthineers took and the lessons learned in their seven-year digital transformation