Since the period of Industrial Revolution and development of the production systems, critics, economists and philosopher try to answer a question about future of work and increased productivity. In the past, systems have been used by organizations to “automate the back room.” Dramatic improvements have been made in the areas of inventory and receivables management and centralized data capture from far-flung stores. For the most part, these changes have enabled organizations to do the same job faster or at less cost. In the future, certainly more automation of current, back room activities will take place. However, there will be a greater use of systems to initiate new procedures and enable organizations to pursue business strategically. In spite of greet changes in technology, production systems and motivation, most all of the predictions about the future of work are either naively utopian or dystopian.
Applied to HRM the term utopian means ideal state. “Connected with the literary fable of a utopia has been the belief in an actual ideal state in some remote and undiscovered corner of the world” (Prychitko 1991, p. 34). On the contrary, dystopia means a vision of future as miserable and oppressive (Prychitko, 1991). The key of dystopian ideas about future of work is increased impact of technology on HRM. The key will be to apply technology in order to gain a sustainable competitive advantage. Only by applying technology in this manner can exceptional profit performance be achieved. Michael Porter, professor at the Harvard Business School, has identified the competitive pressures that come to play in any industry. Critics remind us that we face competition not only from the obvious direct competitors in the industry, but from suppliers, from possible new entrants, and from substitutes for our services.
Marxism and Marx’s idea are often considered a utopia. “The idea of workers managing their own workplaces–cooperation and self-management–has captured the minds of many people” (Prychitko 1991, p. 1). Marxism itself contributed to this growing sense that the Victorian ideal of progress implied not that things get better, but simply that things change, and very possibly for the worse. Hegelian history was in many ways the paradigm of nineteenth-century notions of progress. In Hegel the inexorable dialectical march of history was guided by the teleology provided by the guiding spirit of God’s plan–things always eventually change for the better and toward the fulfillment of this plan. But, despite the utopian element in his own thought, Marx’s demystification of Hegel removed the assurance provided by this teleology and made it possible to envision a dialectical history that leads not to utopia, but to disaster (Senge, 2000)
A number of developments in nineteenth-century thought might be adduced to explain the gradual turn to dystopianism during the course of the century. For example, the Marxist vision of a coming workers’ paradise is one of the central instances of nineteenth-century utopian thought, while at the same time the Marxist critique of capitalism. Such analyses also indicate that this sense of mastery already contained the seeds of its own destruction. Indeed, by the time Newtonian science reached its zenith in the nineteenth century (along with the imperialism and capitalism that it had helped to produce), scientific discoveries were already beginning to undermine the unlimited faith in the power of science that had been growing during the two previous centuries (Bach, 2005).
Even a brief litany of scientific discoveries in the nineteenth century shows that science was beginning to point toward limitations on the ability of humanity to dominate its environment. For example, in 1850 the German physicist Rudolf Julius Emanuel Clausius announced the second law of thermodynamics, which stated that the entropy of a closed system will always increase with time, regardless of circumstances. Entropy is a general measure of randomness in a system and has to do with the unavailability of energy in the system, so that this continual increase in entropy leads to a gradual decrease in available energy. What is significant in the second law of thermodynamics is the utter irreversibility of this process of entropic decay. “Marx nevertheless maintained that cooperative production would not, in itself, “convert social production into one large and harmonious system of free and co-operative labour” (Prychitko1991, p. 7). Thus, contrary to the paradigm of continuing and limitless progress, this law presented humankind with the horrifying vision of a universe gradually decaying toward a condition of total randomness, total unavailability of energy–the so-called heat death of the universe. If, as eighteenth-century science had suggested, the universe ran like a giant clock, the second law of thermodynamics suggested that the clock was running down and that it could not be rewound (Campbell and Crag, 2005).
Following Skill, the cheap labor pool that organizations enjoyed will decrease. Fewer, and less educated, candidates will fill out job applications. The cost of labor will jump dramatically and training and support needs for the typical clerk will increase. Young sales people will be in great demand whereas older, semi retired individuals will be seeking part-time work (Doyle and Stern, 2006). Organizations will have to learn to manage a vastly more diverse work force. For example, the number of white males will drop from the current 45 percent to 30 percent of the labor force by the year 2000. People from a variety of ethnic backgrounds win be entering the labor pool in increasing numbers, particularly Spanish-speaking individuals. The labor pool shifts come at the same time that serving the customer is of growing importance. organizations will have to provide more service but with less labor input (Kay, 2003).
The utopia ideas about future of work are based on suppositions that robots, computers and technology will replace work and people will control these technical devices spending time for their own needs. Researchers and critics believe that communications technologies are improving almost as fast as are computer hardware and software technologies. The move to fiber optics over the next decade win provide a quantum leap in what can be done with communications. We will be moving from a copper wire technology that can carry twenty-four voice conversations simultaneously (on what are currently advanced lines) in an analog mode to fiber optic lines that can carry sixteen thousand conversations simultaneously in a digital mode. It is all too easy to underestimate the vast changes that will take place because of improved communications (Lynch,1997). For example, fiber optics win allow movies to be “downloaded” over telephone lines to individual homes in minutes, shoppers will be able to “turn through the pages” of full motion hypermedia catalogs on their high-definition televisions, and picture telephones will finally become a reality. Other technologies include digital cellular radio, which will expand the capacity of the radio frequency channels to allow portable telephone communication anywhere (Armstrong, 2001).
These ideas are utopian because humans will never be replaced by computers to make the broad-based decisions, to supply the high-level understanding, to create ever better systems, to inject innovation, to provide creativity, and to execute the crucial personal side of business. But, humans will be freed to deal with these central matters by the automation of low-level decisions. By the mid-1990s vast amounts of inventory and logistics decision making will have been automated by the use of models housed in computer programs. This trend will spread and penetrate many other areas of the organization. This is really an extrapolation of trends that trace their roots back to the development of operations research during World War II (Lawton and Rose, 1994).
The dystopian ideas about future of work deal with a threat coming from innovative technologies and dominance of computer intelligence over humans. At present, organizations think in terms of centralized or decentralized operations and decision making. In the future, information will be centralized and the decisions will be decentralized. Centralized data are best for storage and maintenance. Decentralized decisions are best for marketing, accountability, and motivational reasons. The new generation of systems and networks will allow both goals to be achieved. In the past there has been much debate among organizations as to how best to handle the issue of centralization. Should most key decisions be made at corporate headquarters, or should they be made at a regional or store level? In the future, information technology is going to require the centralization of data as part of the movement to systems integration and the use of corporate data dictionaries in conjunction with relational databases (Reed, 2001). There are strong advantages in centralizing information management because data can be stored with fewer redundancies and with better data integrity if they are put into a single relational structure. Also, data can be safeguarded and backed up on a more systematic basis if centralized. However, the centralization of data does not dictate the centralization of decision making (Prychitko, 1991).
Technology should never be allowed to get in the way of important human factors. Rather, information technology should be used to improve the human factors of the business by automating routine, low-level decisions and achieve a form of job enrichment because it allows employees more time and better support for those functions that only humans can do–functions such as assessing changes in the environment of the firm, providing motivation, instilling creativity into the organization, and treating others in a personal and humane way (Robertson et al, 2002). It is clear that organizations face substantial opportunities and challenges resulting from the dramatic technological advances that are taking place in the information systems area. As this paper has stressed, there are strong consumer, competitive, and resource trends that can best be capitalized on by the use of this new, emerging information technology (Kay, 2003).
Computers and communications set the stage for the implementation of business “smarts”. However, these smarts go beyond what computers can do; computers are just workhorses that can get the job of decision making implemented. Behind the scenes are the technologies of neural networks and econometrics used to (1) analyze data and develop causal relationships, (2) develop mathematical programs to allocate resources most efficiently, and (3) allow mathematical modeling, mathematical programming, optimal control, and simulation to tackle difficult and/or highly repetitive decisions. Technology will not be embraced for its own sake, but rather to support key applications. Organizations can organize their thinking about the use of technology by keying in on three interfaces: the organizations -customer interface, the within-firm departmental interfaces. The use of advanced networks within the firm will allow it to develop seamless information systems, even out to vendors and customers (Robbins, 2004). This will make possible less middle-management and generally more efficient operations that are at the same time more effective than today. In particular, to prosper in the next decade, the firm must quickly move to full relational database management. Relational database systems will be needed to manage the business but also will come into play in tracking customer behavior data at the transaction level (Rosow and Casner-Lotto, 1998). Organizations, on the other hand, will be able to match response to products offered and marketing strategies to smaller and more targeted segments. Even the largest firms will adopt localized marketing programs, giving them tremendous use of scale and long-run competitive advantages over smaller firms in the marketplace (Becker, 2003). They will cover virtually all of the transactions and will provide one of the key enabling factors for seamless systems integration between the firm and its suppliers. Massive data storage capacity coupled with data compression techniques and advanced data servers will support real-time access to huge databases. Expert systems and statistical systems (including neural networks) will be used to segment databases, to predict response to marketing efforts, and to send this information upstream to suppliers (Fill, 2005).
. Applying these technologies will require a number of organizational changes. Firms will need more computer-literate support staff in their buying offices and stores to develop decision-support systems and causal models. Decision makers will need to be freed of the more mundane decision problems by the automation of much of what they deal with today. More sophisticated decision makers who have advanced business training will be needed (e.g., MBAs who have an understanding of both systems and models, supported by econometricians and artificial intelligence specialists who can tune, debug, and consult on the use of statistical analysis and pattern recognition approaches to causal modeling).
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