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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Joel Nichols discusses the barriers and challenges facing regulated industries as they attempt to implement Industry 4.0 technologies and change their culture. The article examines the questions that regulated industries must address as they embrace digital transformation and the advances that specific Industry 4.0 technologies can yield. The author argues that although digital transformation may require more time in regulated than in nonregulated industries, “the impact of regulated industry transformation on producers and consumers alike ultimately will be greater than that of the nonregulated sector.”
This Advisor shares five practical tips on rolling out “industrial,” scalable robotic process automation solutions based on my experience at a multinational organization.
In this week's edition of The Cutter Edge, we'll explore how to leverage visuals to make your BA initiatives more effective, and examine the five technologies that could help automate your software development efforts.
For most organizations implementing customer experience (CX) management practices, it is still too soon to tell if their practices are living up to expectations.
Our company’s Agile journey across a 2,000+-person product development unit in 10 locations in Sweden, Poland, and China, resulted in a quadrupling of value throughput; a doubling of speed; a tenfold increase in quality; and happier, more engaged people who are, ultimately, more innovative. The company made major shifts in a few areas. In this Advisor, we explore its shift from resource efficiency to flow efficiency.
People’s increased mobility, facilitated by air travel, has resulted in the increased spread of contagion across geopolitical boundaries. A growing awareness that bioterrorism agents could spread in the same way has raised the level of concern even more. Many practitioners and researchers agree that contact tracing, which is the identification and locating of people who may have been in contact with an infected person, represents an important factor in mitigating the spread of a pandemic.
Encouraging and developing data-based decision support is an organization-wide effort and requires many resources, including people, money, and technologies. Building an effective decision support capability can help improve decision making, but meeting that goal is a challenging task. So how can senior managers increase the chances of the successful implementation of an enterprise-wide data-based decision support, analytics, or BI project? The answers to the five pivotal questions explored in this Advisor provide some insight.
Financial institutions have digitally transformed their business processes and products, creating vast sources of structured and unstructured data. AI offers the means to complete this transformation in radical ways — across the front, middle, and back offices, while also addressing the big data problem. In addition, AI is also shaping the fintech and regulation (“regtech”) landscapes, particularly in addressing what has become known as “Big Regulation.” However, AI’s promise must be balanced with current limitations to the application of enabling technologies like machine learning (ML) and natural language processing (NLP). This Advisor looks at the promise, potential, and limitations of AI in the financial industry.