Unit VI Research Paper

DBA 8671, Technology and Innovation Management 1

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

3. Evaluate the role of portfolio management in governing the innovation management process. 3.1 Describe governance in regard to portfolio management.

6. Synthesize communication methods, leadership skills, and business acumen in the development of a

new technology strategy. 6.1 Assess the role of internal collaboration between technology and business functions.

Course/Unit Learning Outcomes

Learning Activity

3.1

Chapter 14 Chapter 15 Chapter 16 Unit VI Research Paper

6.1 Unit Lesson Unit VI Research Paper

Reading Assignment Chapter 14: Improving the Customer Experience: An IT Perspective Chapter 15: Moving Towards an API Economy Chapter 16: Preparing for Artificial Intelligence

Unit Lesson Customers, Services, and Experiences The Information Age in which we live is powered primarily by a service economy. We buy services, content, and other intangible technological products, including intellectual property. We also tend to work for companies that operate business models, which, to a substantial degree, are grounded in services. This suggests that consumers today do not purchase things any longer but, rather, experiences. Even the purchase of a product as tangible as an automobile could be viewed as a bundle of experiences. The information and support provided by sales and marketing is a service that is experienced. Consider, for example, the build and price configurators now available on most automobile manufacturer websites. The services aid in combining the most desirable mix of features, and then the customer is directed to a local dealer upon request. Financing the automobile is a service. The growing number of available financial packages attests to the importance of automobile finance. In fact, prior to the failure and bailout of General Motors (GM) in the financial collapse of 2007, GM Acceptance Corporation (GMAC), the financial service arm of GM, was valued higher than the actual automobile manufacturing (Celeritas Investments, 2018). It almost seemed that GM was manufacturing automobiles simply to provide a mechanism for offering financial services. Once inside a purchased vehicle, the customer encounters a range of services—many of which are supported or designed in conjunction with information technology (IT). Such services include navigation, satellite radio, and 4G LTE and WiFi connectivity. Many automobiles today connect with home WiFi and 4G wireless to download software and system updates and report vehicle problems. If the car is involved in an

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Customers, Services, and Experiences

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accident, chances are that the vehicle will automatically contact a service, such as OnStar, report the accident, and connect the customer with assistance. Stan Shih, the founder of Acer Computers, recognized the importance of customers and experiences in his introduction of the concept of the smiling curve, which is shown in the graphic below (Baldwin & Evenett, 2015).

Stan Shih used the smiling curve to illustrate the fact that global competition has greatly reduced the profitability of manufacturing products (Baldwin & Evenett, 2015). The sales of products are said to produce the least value in terms of return on investment. In other words, product sales do not provide an efficient means to tap into the value associated with the know-how of the organization. To survive within the Information Age in which companies compete, product sales must be complemented by sales of components, technologies, and services. Some companies, upon recognition of this framework, have focused exclusively on sales of components, technologies, and services. Qualcomm is an example of a company that has taken this approach. Qualcomm may not be instantly recognizable by the average smartphone user, but Qualcomm technology is found in nearly every phone sold in the world. Furthermore, Qualcomm’s design services likely aided manufacturers in their respective product development effort. IBM is another company that shifted its emphasis because of the smiling curve. IBM, once known as a manufacturer of mainframe computer systems, is now known for its consulting services and intellectual property. What does this mean for technology managers? The global service economy is booming because of the value that consumers place on experiences and services. In fact, the expectation of services bundled with products or even offered on a standalone basis has risen to the point where it is becoming viewed as a norm rather than as something extra that is being offered as an afterthought to the products. The What and Why of the Application Programming Interface Much of software development over the last 20 plus years is object-oriented in its design and construction. Object-oriented software design provides the means to reuse that which is already developed. It has the potential of simplifying the overall software development effort. This is because the object-oriented approach bundles together data and operations into self-contained bundles. Objects interact with other objects by sending messages back and forth while, at the same time, hiding the underlying complexity of the internal code and algorithms. A common analogy used to explain object orientation is provided using the wristwatch. The owner of the wristwatch is able to query the watch by viewing its user interface (i.e., the face of the

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watch). The owner of the watch may do this at any time without knowing anything about the underlying complexity of the watch. The springs and gears inside the watch are hidden, and they are not accessible. Furthermore, access to the underlying watch technology is generally not necessary. What, then, does object- oriented development have to do with the application programming interface (API)? The API for a given system or application specifies how other applications, systems, or software may interact with the application. Object-orientation provides useful background for what the API does and how it works. This is because APIs do not require that those accessing the application using the API understand the underlying technologies of the application. Instead, the API facilitates interaction and the sending and retrieval of data to and from the application. Continuing with the API for a wristwatch, the basic interface is to look at it, with a possible API extension of winding it occasionally. Why are APIs important in the Information Age? Making APIs available for most systems and applications allows applications to work together seamlessly while hiding its underlying complexity. In addition, when this is done, business opportunities are created. For example, a service that provides data, such as time, location, and weather, may have an API, and public websites may access this API to provide an ongoing source of weather information that is linked to the time of day and the location. Consumers who visit the site to access weather information may also see advertisement messages and click on them. APIs also have the potential to remove humans completely from transactions. Systems using APIs may query and monitor other systems, which, in turn, collect data from things, such as packages and machine performance data. Machine to machine interaction using the Internet is known as the Internet of Things (IoT). McKeen and Smith (2019) refer to the API economy when discussing the importance of the API. What does the API economy infer? What does it mean for the technology manager? The API economy asks managers to envision all technologies, applications, systems, and networks as potential business opportunities and, further, as potential means for transformation, innovation, and disruption. This requires adopting a holistic outlook where managers think in terms of possibilities that did not previously exist. For example, an information source and associated service in one part of the company that formerly operated in isolation could potentially interface with other similar sources and services in ways that were not formerly considered. Why Artificial Intelligence? Technology managers will be familiar with the data, information, knowledge, and wisdom (DIKW) model. The intent of this model is to illustrate the progression of data at its most raw and unrefined state and show how it becomes something more. Each stage requires work or an expenditure of energy. When data is collected, it only becomes useful when work is performed on the data to make it relevant and place it in a form that is consumable. Data that is relevant is information, and the data that information contains has undergone a transformation to arrive at this state. Information that is incorporated into life and practice becomes knowledge. Knowledge that is applied over an extended period of time and is incorporated at a higher level becomes wisdom. How does the DIKW model relate to artificial intelligence (AI)? The problem with making data useful is the effort and the intensive thought processes involved. Humans have limited capabilities and limited attention spans, making it quite difficult to make sense of the sea of data generated by systems, by systems talking to other systems using APIs, by IoT devices, and, finally, by the simple fact that much of the work we do in our daily lives leaves behind a trail of data. AI has the means to offload the mental burden of making sense of things by building up a macro-view of the world, beginning from data at its most granular state. AI is able to do this without being overwhelmed. AI can effectively sort through millions of water molecules and detect the surface level of water as well as the waves. To further extend the analogy, AI can sift through millions of blades of grass and determine the presence of a lawn. IT managers are likely to be familiar with business intelligence (BI) through the use of systems, such as IBM’s Cognos. Although BI offers an extremely powerful toolset, what if BI could learn over time? What if it could evolve and become more sophisticated based upon feeding experiences from the past into the present? Perhaps this is where managers will obtain the first glimpse of AI in the future. For better or worse, navigating and making sense of the enormous volumes of data that our systems produce today and will produce in the future will require raw intelligence to make sense of it. Such intelligence may well come from machines rather than humans.

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References Baldwin, R. E., & Evenett, S. J. (2015). Value creation and trade in 21st century manufacturing. Journal of

Regional Science, 55(1), 31–50. Retrieved from https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direc t=true&db=a9h&AN=100373310&site=ehost-live&scope=site

Celeritas Investments. (2017, June 16). Old GM vs. today's GM. Retrieved from

https://seekingalpha.com/article/4081961-old-gm-vs-todays-gm McKeen, J. D., & Smith, H. A. (2019). IT strategy & innovation (4th ed.). Burlington, VT. Prospect Press.