Unit VII Annotated Bibliography

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Course Learning Outcomes for Unit VII Upon completion of this unit, students should be able to:

4. Summarize the challenges faced by information technology (IT) departments when managing security and service delivery for organizations. 4.1 Analyze peer-reviewed sources relating to the role of internal and external management on the

demand for technology.

5. Evaluate the importance of developing competent, professional, and ethical information technology (IT) leadership. 5.1 Explain the challenges of preparing leadership to manage emerging technologies.

Course/Unit Learning Outcomes

Learning Activity

4.1 Unit VII Annotated Bibliography

5.1

Unit Lesson Chapter 17 Chapter 18 Chapter 19 Unit VII Annotated Bibliography

Reading Assignment Chapter 17: Managing Emerging Technologies Chapter 18: Enhancing Development Productivity Chapter 19: Transforming to DevOps

Unit Lesson Dilemmas in Emerging Technologies The technologies in use today were once emerging technologies. The difficulty with understanding how to manage technologies that are emerging today is that their future promise is by no means certain. Studying the emerging technologies of the past illustrates how hindsight is 20/20. It is easier to make judgments regarding yesterday’s technologies than it is to consider what management steps to take today. A classic example of the difficulties involved with making decisions about emerging technology is observed in the history of Kodak. Few today can understand why Kodak is a peripheral player in the world of photography. At one time, Kodak dominated the photography market and was a wellspring of innovation in the field. The company headquarters area in Rochester, NY, was said to be the Silicon Valley of 100 years ago (Balachander, 2017). Why, then, did Kodak miss out on the emergence of digital photography? Imagine that you were the chief executive officer (CEO) of Kodak in the 1980s and 1990s. Digital photography was an emerging technology during this time. It could not compare to film photography in performance. It was comparatively expensive—particularly in terms of research and development (R&D) investment. Further, its future was uncertain. Though possibilities for this technology could be envisioned, this is a vision that Kodak would not necessarily welcome, given its dominance in film. Because of this, though many could not clearly see the future promise of this technology, Kodak tended to see it less clearly than others did. What, then,

UNIT VII STUDY GUIDE

The Impact of New Technologies and Methodologies on IT Management

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would you—playing the role of the CEO of Kodak—do in this environment? Is it possible that the board of directors and shareholders would welcome a push from the CEO to record lower profits (due to increased R&D spending) and to invest in a technology that is a threat to existing Kodak products and market share? Would you (in the role of the CEO) have enough passion and confidence in the future of this particular technology to the extent that you would bet the company and your career on it? The answer is probably no, and by giving this answer, it becomes increasingly clear why Kodak did not manage to navigate its way into the technology of the future. Managers who deal with emerging technologies encounter the Kodak dilemma every day. The past is clear, but the future is not. To consider a current example, consider the dilemmas faced by technology CEOs today in companies, such as Apple, Microsoft, and Tesla. For Apple, what is the next big thing now that the smartphone, PC, and tablet markets are maturing? Is it self-driving cars? Is it new 5G wireless services? If you were the CEO at Microsoft today, where should the company go beyond the Windows product line? Is it the cloud? Would you, for example, invest further in surface laptops or possibly reenter into the smartphone market? Finally, is Tesla’s electric vehicle the technology of the future? When it comes to electricity, one can never be too sure which path the market will choose, even when the leadership behind the company is a household name. Recall that over 100 years ago, Thomas Edison’s direct current power systems were promoted everywhere, but Westinghouse—with the aid of Nikola Tesla—pushed Edison out of the market with the more efficient alternating current technology that we still use today (King, 2011). It is interesting to observe that the company called Tesla today took the name of an entrepreneur from earlier generations whose technology became highly successful but, unfortunately, mostly after his lifetime. System Development and Productivity It is observed that emerging technology is expensive to develop. This is especially true within the realm of information technology (IT) due to the complex mix of systems, software, and intangibles. There may be a nearly infinite array of moving parts, each of which is, in the case of software, invisible. Every stage of system development is difficult. It is challenging to understand requirements for clients and the general marketplace when looking ahead 3 to 5 years. Technologies and standards tend to change often, and not all standards that are proposed are adopted by the market. It is highly likely that even if requirements are well understood, they may change after the development effort has begun and significant work has been completed. In addition, the technical capability required to develop systems—especially those involving emerging technologies—can be very demanding. No individual has all of the skills required to get the job done, so this requires a high degree of multidisciplinary teamwork to produce advanced systems. Systems development, therefore, occurs at the intersection of standards, requirements, technologies, people, and processes. For these reasons, systems development is often daunting and very low in productivity. Processes have evolved over time to improve how systems are developed. In the early history of IT, organizations typically approached systems development in a rather ad hoc manner. Often, the difference between success and failure depended upon one or more mad geniuses who would rise to the occasion in a heroic fashion and somehow pull all of the pieces together at the last minute. The unpredictability and spotty success rates of the ad hoc approach led to the development of structured processes to guide the hand of development teams from start to finish. One such process is the systems development lifecycle (SDLC). The SDLC is often referred to as the waterfall method since system development under this methodology occurs in phases. As one phase is completed, the output of one phase is fed to the next in sequence. Review the graphic below, which shows the flow of SDLC.

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The structured approach improved success rates and kept systems development moving in an orderly fashion, but it was not without shortcomings. The SDLC is known for requiring significant process structure and documentation. It has been observed by those who use the SDLC that the process can create what is perceived to be a burdensome process overhead. Another critique of the SDLC is that since one phase leads to another, projects often terminate in a final “big bang” integration milestone as subsystems that are developed are linked together for the first time. This type of final integration leads to a high degree of uncertainty since it is common for the system to fail to work properly when all subsystems come together for the first time. SDLC projects are known for falling into an abyss of software bugs as the team struggles to finalize the system and get it delivered and operational. The Agile system development methodology evolved as a response to the shortcomings of the SDLC. The term agile has the connotation of flexibility and perhaps being able to move quickly. This is what the Agile system is intended to accomplish with its featured low process overhead and its emphasis on constant communications between team members and project sponsors. The Agile approach, unlike the SDLC, does not view systems to be monolithic. Rather, Agile focuses on executing a little bit at a time using deliverables referred to as sprints. Instead of taking on everything at once, Agile does some analysis, some design, and some development, and it then produces pieces of functionality that can be evaluated on an ongoing basis by clients. Since Agile approaches system development using one element of functionality at a time, there is a greater ability to take into account changing requirements. Unlike the SDLC, there is no final big bang integration. Instead, there are a series of smaller scale integration milestones that mature the overall system along the way, one step at a time. DevOps: Another Approach to Productivity DevOps, like Agile, is another way to think about systems development. Whereas Agile emphasizes daily standup meetings and frequent communication among the team, DevOps extends this idea to the stakeholders who will use the system. In other words, the development team and the individuals within operations who employ the developed systems and applications interact frequently with the development team to try out deliverables as they are made available and then provide feedback results in a rapid, virtuous cycle. This sequence of activities is similar to the Agile approach with much more emphasis on proving out the system as it evolves, much like sequential prototyping.

SDLC waterfall (Bourgeois, 2014)

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Does It Get Any Easier? It is observed that novel development methodologies have been proposed and implemented to improve productivity and to organize and streamline highly complex development activities. Do they achieve this goal? New process methodologies do appear to support managers’ goals for lowering costs, improving the rate of output, and, finally, improving the quality of deliverables. Unfortunately, the effort is a moving target. At its heart, the development of complex systems and technologies is inherently difficult. Although it is true that processes improve over time, it is also observed that systems being developed are growing to be increasingly complex. While it is desirable for technology managers to get ahead of the curve, which is the ideal goal, simply keeping up with complexity and difficulty presented by systems development may be good enough.

References Balachander, S. (2017). Historians weigh forces that shaped Silicon Valley. Retrieved from

https://west.stanford.edu/news/historians-weigh-forces-shaped-silicon-valley Bourgeois, D. T. (2014). Information systems for business and beyond. Retrieved from

https://bus206.pressbooks.com/ King, G. (2011). Edison vs. Westinghouse: A shocking rivalry. Retrieved from

https://www.smithsonianmag.com/history/edison-vs-westinghouse-a-shocking-rivalry-102146036/