Every once in a while, it is a good idea to take a high level overview of where information technology (IT) has come from and where IT is going. That helps us put our efforts into context and lets us know where we should be devoting our efforts.
Information technology is now in its third transformation. The first transformation was the digitization of business. The second is the continuing digitization of human experience. The third stage is the digitization of machines. Each transformation is ongoing, builds upon the others, and may overlap. Thus, some technologies that formed a foundation earlier are still active. For example, the mainframe is still alive and well even in the time of mobile computing. We have to understand that while they act simultaneously in some sense, we also have to understand how they fit together.
Even though specific technologies provide a frame of reference, these transformations are from a broad perspective and not dependent upon any one technology. Please also note that there is not a smooth transition to each transformation, but that elements of a later transformation may be present while the key transformation of an earlier era is still more prominent.
The Three Digital Transformations
Let’s take a closer look at all three from a digital perspective:
- Transformation I: Business Workflow and business automation — the beneficiary of this transformation is the business itself; it represents the digitization of traditional business processes most familiarly associated with online transactions processing systems (OLTP); from a software perspective, including operating systems, application-driven software intelligence using third-generation and object-oriented programming languages, database management systems; and from a hardware perspective, mainframes, minicomputers, and servers along with hard disks and magnetic tape; and from a network perspective, leased lines.
- Transformation II: Human Experience– this has consisted of two stages.
(i) Interpersonal communication and productivity — the beneficiaries of this first stage has been employees broadly and directly at all levels; it represents digitization meant to enhance worker productivity and includes office applications, such as e-mail, word processing, presentations and spreadsheets; the key software was office productivity tools; the key computing hardware was the personal computer; and the key networking component was the extension of the local-area network (LAN) within a company’s local environment and the extension of the wide-area network (WAN) to the Internet so that employees of one company could communicate with other people (including customers and business partners).
(ii) Virtual digital world (cyberspace) — the chief beneficiary of this stage is the individual (consumer); yes, business has benefited tremendously, but the overall result has been the immersion of the individual into the digital world (notably cyberspace); the Internet is key to this transformation, as is the move to mobile devices that have added tablets and smartphones to the mix ,along with traditional laptops and their derivatives.
- Transformation III: Machines — the chief target of this transformation is things (mostly machines); this transformation represents the Internet of things which contain digital intelligence (embedded processors and storage); some call this the “industrial Internet” but that is limiting, because not only machine-machine interactions can take place, but also machine-biological interactions (such as body sensors); this represents heavy use of data-driven software intelligence, which encompasses sensors and other instrumentation, machine learning, robotics, and content creation (such as online learning).
Why is this taxonomy useful? Let’s look at it from a big data growth perspective as shown in the following slide. We can see how all three transformations play a role in big data and how our lives are getting more complicated as a result.
Figure 1: Sources of Big Data Growth
Source: The Storage Networking Industry Association Data Protection and Capacity Optimization Group 2013
What about the trends we consider so important?
We will not ignore major trends as they affect our everyday life. Take big data. Big data is a code word for solutions that seek to make sense of and derive insights from the explosion of data. It consists of both what is happening in Transformation 3, such as the Internet of things, as well as taking advantage of Internet-created data from Facebook, Google searches, etc.,. Still, there is more that has to be done to have “things” use this data effectively.
In the Internet of things, most data is generally created by machines autonomously rather than by people individually. Data can come from artifacts, the non-biological natural world, or the biological natural world.
- Artifacts — the technological creation of the human mind, from everyday items, such as washing machines and refrigerators, to sophisticated high technology, such as smartphones or tablet computers. Your washing machine or refrigerator can communicate problems over the Internet. Your position over time can be collected using GPS on your smartphone and used for a number of purposes (such as helping you locate the nearest Italian restaurant).
- The non-biological natural world — this includes the weather, astronomical observations, and mineral deposits as well as most of the areas where the hard sciences, such as physics and chemistry, play a big role. Weather data, searching for mineral deposits and the work of CERN all generate big data.
- The biological natural world — this consists of the spectrum of living (or near living) things), such as plants and animals – and encompassing humans. For example, genomic research is a major contributor.
Sensors of one type or another are responsible for capturing information, ranging from those which measure component wear and predict failure on a train locomotive or car (artifact), to data that collects data on hurricanes (non-biological natural world), and to medical sensors on a person to monitor heart rate, temperature, etc. (biological natural world).
The Internet of things has a big impact on IT organizations and what they need to do with emerging technologies and platforms like cloud computing. When we think of a compute cloud (say, for simplicity’s sake, a private cloud) we tend to think of a transformation of a traditional data center. However, the traditional data center was designed for transformation 1 (such as OLTP systems). The data center was adapted to serve Transformation 2 (as businesses found accommodation with PCs). In addition, IT organizations may have been able to force-fit their own Web services into traditional data center environments. This is not perfect, but most of the data is still under the control of IT theoretically.
That is changing. In dealing with BYOD where business and personal data commingle, IT finds that there is data “in the wild” that is outside the control of IT. One source of the “data in the wild” problem are business units that opt for shadow IT outside the confines of official IT, such as SaaS applications, without considering the consequences. These problems have been harder for IT to tackle.
Add in the geographically dispersed and distributed collection of data that the Internet of things requires. In this case, the cloud has to be not merely a physical single data center but a world-wide virtual data center that encompasses everything, with the necessary scale and elasticity, including the ability to deliver IT as a service. Quite a challenge.
The concept of IT causes a problem when we try to think about what is happening today with information, because we naturally think in terms of specific technology products and what is happening before our eyes rather than from a broader perspective. Other terms, such as “infosphere” (not the IBM product) have been coined to describe this complex situation, but they are not commonly recognized nor accepted.
IT has been very adaptable to change over the years, and will continue to do so. Hopefully, having the Three Transformations of IT laid out will provide a context and reference point from which IT can put its thinking cap on and plan for the big picture rather than donning blinders and focusing only on one immediate problem at a time.