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.
Recently Published
In our studies of medical decision making under stressful conditions, we found that individual differences between users, such as experience level or familiarity with the technology, must be recognized as part of the context (i.e., individual user characteristics). In addition, local conditions such as time pressure or uncertainty provide another construct for context (i.e., environmental characteristics). We share a model for technology embeddedness in this Advisor.
Following the popularization of Agile in tech, educators in a small New York City startup who got word about it began experimenting with creating “agile classrooms” in an effort to increase student engagement and collaboration in otherwise conventional environments.
There is a wealth of evolving business and IT strategies, disciplines, and technologies, but many of these concepts are technology-driven and lack a unifying vision. The cognitive enterprise, on the other hand, offers a business-driven vision for organizations where technology is merely a means to an end. This Executive Update outlines the purpose of the cognitive enterprise, its two fundamental underlying concepts, common scenarios that manifest within a cognitive enterprise, and how to position organizations to achieve this vision.
The advent of big data technologies with an emphasis on the ease and speed of ingestion of large amounts of data into a data lake — as opposed to the often-complex traditional ETL processes for loading into a data warehouse — has meant far less focus on defining schemas or structures. The focus now shifts toward how to achieve an adequate level of governance of such data lakes. This is where the data catalog provides a central canonical reference point of business meaning to underpin any data governance activities of the data lake.
In this issue of The Cutter Edge we explore the idea of allowing and encouraging dissent in organizations, four best practices that can help address innovation challenges, and innovation models across industries.
New commercial applications are now available that utilize artificial intelligence, machine vision, Internet of Things connectivity, and camera-based security technologies to detect and interdict active shooter incidences before they become deadly.
In Part VI of this Executive Update series on statistical project management, we look at the “nature” of the project and its role as the firm’s “working memory.”
In the digitized world of financial data, there are truly enormous volumes of heterogeneous structured and unstructured data across siloed data stores. Managing such complexity is beyond human cognitive abilities or comprehension; hence, AI-based smart machines are required to assist human cognition and decision making. We believe that if AI is to achieve its promise, financial institutions are going to have to address a range of challenges.