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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I've been playing around with an idea for several months in conjunction with a new book I am working on. In effect, I thought about extending the popular "patterns" approach to provide a way to help business managers think about the kinds of changes they could make in their organizations. A lot of companies are thinking about transitioning to e-business models.
In Business Week this week, I read of a gentleman who traded stock with E*Trade. On the side, he sold an older computer via Yahoo! Classifieds. The sale went quickly and he got a bank- certified check for his computer. Unfortunately, the check was a phony, written by a cybercrook that the FBI was after. The gentleman didn't know any of this and deposited the certified check into his E*Trade account.
When I talk about component systems, I tend to emphasize that they are flexible. A single component can have interfaces that will support other components based on different component models. By using CORBA, a company can link COM, C++, and Enterprise JavaBeans components located on different servers in widely different geographical locations.
The Japanese government recently announced a five-year plan to make itself into an Internet powerhouse. I read the announcement with interest. When I was heavily involved in expert systems and AI in the mid-1980s, Japan was engaged in its Fifth Generation project, an effort to propel Japan into a leadership position in AI.
Over the years, I have developed a checklist for selecting automated tools to perform macro software project estimates. Mine is similar, though not identical, to Robert Park's Checklists and Criteria for Evaluating the Cost and Schedule Estimating Capabilities of Software Organizations (SEI-95-SR-005, January 1995).
In previous issues of ITMS, I tackled the subject of managing Internet-speed deadlines (see ITMS, May and June 2000). Specifically, what do you do when IT projects are given a deadline first, before you know the full scope of the requirements? Also, how do IT applications development and maintenance projects fundamentally behave -- what are the "laws of nature"? How can that knowledge help us estimate projects better?
A good measurement program is one of the cornerstones of any successful process-improvement program. In fact, measurement is essential if you want to be able to quantitatively identify improvements. But knowing this doesn't help when you find yourself responsible for the implementation of a measurement program in your organization. There are just a few questions you want answered. Where do you start? What are the right things to measure? Why me?