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The MSIM curriculum part four: Managing the edge

Information managers work in a dynamic environment. They must know how to deploy the latest technologies to maximize the competitive edge for their firms, but they must also watch the horizon for the next game changer. KnowIT’s tour of the Master of Science in Information Management (MSIM) continues this month with a look at two courses that prepare students to be managers who leverage change.

2012-09-04

Information managers work in a dynamic environment. They must know how to deploy the latest technologies to maximize the competitive edge for their firms, but they must also watch the horizon for the next game changer. KnowIT’s tour of the Master of Science in Information Management (MSIM) continues this month with a look at two courses that prepare students to be managers who leverage change. “Emerging Technologies,” taught by Professors Ajay Vinze and Bin Gu, teaches students how to track and evaluate advances in technology. “Knowledge Management and Text Analysis,” taught by Faculty Associate Theresa Edgington, leads students into a new paradigm where they learn a new way of thinking about the nature of knowledge, and how new knowledge can be generated using human input. Emerging technologies The problem with preparing a course on emerging technologies, Vinze says, is that by the time you teach it the technologies may have already emerged. Vinze and Gu — one of the department’s new professors — are collaborating to create the class. By the time students reach this class, they will have had courses that exposed them to the kinds of technology now in use. But, Vinze said, “managers today must live with one eye on the present and one eye on the future — this is the one eye on the future part.” Fully appreciating the rapid pace of technological change, Vinze and Gu chose not to focus on a specific product or service. Instead they have structured the curriculum around the major classes of emerging technologies. Within each class they will look at a representative example. The five classes include:

• Smart mobility — how social and communication skills interface with technology and enable work mobility
• Big data — how to leverage increasingly broad and complex data, such as voice, audio, video and other non-traditional data, which presents new issues of size, scope and complexity
• Digital distribution — how this will change the nature of commerce
• Nextware — the “internet of things,” an internet much larger than the human internet, comprised of the communications between things, whether the parts of your car or your refrigerator telling the grocery store that you are out of milk
• Smart technology — agile and nano technologies — a major source of next generation developments.

Each of these classes has produced technologies that are already in use, and they are spawning a new vocabulary that managers need to recognize. “We want students to understand that there will be multiple generations of innovation that will come out of each class,” Gu said. “At the same time we show them how to look into the future— how to look at the life cycle of an emerging technology — and that will differentiate them from engineers.” Vinze added that students will learn to look not only at the benefits of a new technology, but also the risk and down side — of adopting or not adopting. “Another thing we will discuss with students is the effect on current technologies,” Gu said. “In some cases emerging technologies will be totally disruptive, in some cases they may not have a huge impact and may go away in a few years, but in many cases the impact won’t be obvious up front.” The class will also consider the question of standards, and the decisions their companies will have to make in that regard. By the end, students will have developed an analytical framework and obtained some hands-on experience they can use to evaluate the opportunities in what is sure to be a continuously changing environment. Knowledge management and text analysis Clinical Associate Professor Theresa Edgington says that IT professionals often think that "everything can be optimized," but, she says, they over reach if they think this applies to knowledge. Optimization is a mathematical process leading to a finite state, she explains, but knowledge includes a human factor. Edgington, who completed her Ph.D. in information management at W. P. Carey in 2000 and has recently joined the faculty at Arizona State University, is teaching "Knowledge Management and Text Analysis" in the MSIM — both the online and in person programs — this fall and spring. The class will lead students through a paradigm shift away from a view of information technology as traditional processing. This includes most of the well-known technologies, which capture, store, sort, etc. explicit information. "We can be very good at that," she added, and any of that information can be optimized. But knowledge is something more: It is all of that data, put in context by the human mind. Managers need to understand the difference between information and knowledge, she said, because knowledge is the source of competitive advantage. Technology can be used to encourage people to be more aware of what they know — to identify their knowledge — and to create more. "Some people remain fearful that technology will turn us into machines," she said, but that isn't true. "We can use technology to become more of what we should be." The creation of knowledge is not a process that can be optimized, she said, but technology can help us continuously to get better at it. The first order of business will be to help students understand what knowledge is. Then, Edgington will move them into an exploration of social media, and how it can be used to bring people together to create knowledge. The adage "The smartest person in the room is … the room" can be true, she said; using social media, a group of intelligent people can accomplish more than one brilliant person. But managers need to know how to these tools. Otherwise, the social aspect can dominate and "you've got a party," she laughs. Text analysis marries information management and knowledge creation by allowing managers to detect patterns in otherwise unstructured data. Then humans can bring context to the patterns they discover, yielding potentially game changing knowledge. Edgington adds one more point that should be of great interest to graduate students. Anything that can be optimized, she said, can be outsourced — but not knowledge creation. Learn more about the MSIM: Part One: The Line-of-Business Ladder Part Two: Data and Project Management Part Three: Business Intelligence and Security

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