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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Unfortunately, most digital transformation initiatives fail not because they lack capabilities or intelligent, talented people but because they lack precise objectives, digital leadership, and an innovative mindset. Goals — such as what the target business outcomes are — must be clearly defined because a digital transformation journey on its own is already a very complicated endeavor. Digital architecture is what simplifies the journey and makes sense of it. It is vital to begin with a clear objective in order to create the right architecture.
With the dawn of the 21st century, we have begun to observe a more inclusive digital shift in value creation, with the transformation of business as well as societal systems due to an emerging phenomenon: a new computing paradigm that has introduced myriad Web and mobile-based applications aiming to fulfill society’s primary and secondary human needs. Nonetheless, many attempts to develop social computing applications to facilitate value creation have failed. We have created a human needs fulfillment (HNF) model that enables an optimum fulfillment of human needs, resulting in value creation.
Most of us will have some intuitive criteria for judging what data is valuable. These intuitive criteria may be good enough for simple and familiar operations, but when we start to address more complex and dynamic ones, we need a more systematic method for assigning value to data. In this Executive Update, we look at some of the challenges of putting a monetary or nonmonetary value on your data assets.
Rapid and unprecedented changes to the unemployment laws have created both a tidal wave of transactions that need to be processed, and significant changes to the programmed business processes that execute those transactions. Those business processes are entombed in old COBOL code on old mainframe systems. People are starting to panic about needing COBOL programmers. Yes, but.…
Artificial intelligence (AI), machine learning (ML), and big data are expected to have a huge impact on how we live and what we choose to do. Most categories involving these technologies focus on specific lifestyle items like shopping, dining, movies, and so forth. But such customer-centric categories lack specificity from the investor’s eye. In this Advisor, we redrew the categories on which AI/ML and big data startups should focus.
Executive Update
Autonomous Machines Move to the Fast Lane
In a broad Arthur D. Little (ADL) study, we interviewed 30+ industry and technology experts along the automotive value chain (i.e., OEMs, suppliers, distributors, and end customers) in Europe, North America, and Asia. This Executive Update highlights the biggest challenges, barriers, and implications for vehicle design and the industry’s business models.
In Part X of this Executive Update series on customer experience (CX) management in the enterprise, we examine survey findings pertaining to how organizations view their CX efforts to date.
in this edition of The Cutter Edge, we explore decision making lessons in wartime medicine, the impact of COVID-19 on the business technology sector, managing risk with AI and machine learning, and more!