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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Building AI systems is a huge undertaking. Therefore, most companies should focus on helping employees adjust to the new world of AI, curating the right data and leaving the mechanics of building AI systems to vendors.
This Executive Update discusses the thinking behind employing artificial intelligence (AI) in an organization through “augmentation.” It presents a case study on how a superregional bank implemented a cognitive contact center by using an AI framework called HALO — Human Augmented Learning Organization — and showcases the meaning of “AI as a practice” within an organization.
Advisor
Disruptors and IT: Shaping EA
What are disruptors doing that we can learn from and shape the EA toward?
Whether AI eventually lives up to all the hype obviously remains to be seen; however, I expect that we are going to witness some innovative and disrupting applications in the not-too-distant future.
Gill Kent and Robin Harwood provide a case study about linking Business Process Model and Notation (BPMN) workflows and user stories. They focus on the importance of initial modeling during what they call the Discovery phase of a digital transformation project. In their example, they followed a pragmatic, Agile approach to modeling the business and their host systems to gain important insight into the enterprise transformation scope and a vision of the required system change for their endeavor. This enabled them to establish a business/stakeholder vision that captured a clear scope for the following phases. With an initial technical strategy/architecture identified, the team was able to name a backlog of architecturally relevant stories, mitigating the risk of late identification of system integration requirements and the potential for significant rework. In short, a pragmatic investment in initial modeling and planning paid off in huge dividends for their Agile team.
Designing cognitive computing systems (CCSs) requires a strong case for the investment into those systems. Organizations must not only be able to justify the initial investment into developing a CCS, but also think through the investments that will be needed to ensure it can be refined and enhanced over time.
This Executive Update presents a framework in the form of processes, techniques, measurement metrics, and best practices to guide you toward successful API monetization.
Establishing business architecture within an organization takes passion, persistence, and patience. Inspired by over a decade and a half of helping organizations to mature their practices — combined with personal mountaineering experiences — this Advisor shares a few lessons for conquering the “business architecture summit” using mountains as metaphor.