Work in Complex Sociotechnical Systems

Work environments are social systems which exhibit varying degrees of complexity. When an organization brings technology into the work environment, workers enact that technology and social relations simultaneously, creating non-random, yet not entirely predictable, outcomes (Orlikowski 2000). Within such a system people and technology combine to create products or services jointly. To understand the outcomes that result when a new or emerging technology is introduced, one must consider both the human element and the technical elements jointly, considering the requirements of both for engaging in goal-

directed work and understanding how these two elements interact (Fox 1995). One must also understand the wider historical and environmental structures that shape human action durin the performance of work (Orlikowski and Robey 1991). In fact, one can consider a

computerized work environment to be a “sociotechnical system,” if one uses that term in a broad sense to indicate that human action, work context, and technology interact together to influence outcomes (Dillon 2000).

Sociotechnical systems tend to be complex. Vicente (1999, 13-16) highlights the characteristics of a complex sociotechnical system.8 All complex sociotechnical systems will exhibit some or all of these elements. However, the degree to which any given feature is exhibited will vary across types of systems. As he points out, the characteristics defining a nuclear power plant are significantly different from those defining a small office

environment.

A complex system, according to Vicente, tends to reflect a large problem space in which numerous elements interact so that it is difficult (or even impossible) for people within the system or external to the system to enumerate all the key variables that influence the operation and the outcomes of behavior within the system. Likewise, such systems are social in nature, requiring significant human-to-human and human-to-technology interaction. Because of the social nature of these systems, they are characterized by heterogeneous perspectives, whereby the people within the system are strongly motivated by different value

8 _{Since every worker relies upon both discursive and tacit knowledge, the distinction between a sociotechnical} system and a non-social system is an analytical distinction rather than an ontological distinction. Even the lone writer uses the language and tacit skills learned while growing up in a social system. Similarly, virtually any enabling artifact could be considered a technology, as far as it requires technê. One can understand Vicente’s cognitive engineering view, however, as one of degree rather than one of kind.

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systems. In spite of the difference of values, some degree of coherence occurs through cooperation and competition, governed by tacit and explicit authority mechanisms.

The various elements of complex systems also tend to be distributed, both

geographically and functionally. This can make it difficult to monitor and control the system as a whole without specific mechanisms designed to do so. In addition, the goal-relevant properties of the system tend to be dynamic and often the overall system takes considerable time to reflect change in response to changes in these properties. The whole system will evolve as its properties evolve, but often with a lag in response time.

Complex systems can often be hazardous as well, in that the outcomes of operational errors in the elements of the system or its inability to adjust to changing internal and external factors can lead to harmful outcomes, whether those outcomes be in terms of health and safety, economics, or some other variable. For example, in the realm of nuclear power, Vicente shows how inaccurate mental models of the technical processes led to a nuclear power plant meltdown. Likewise, in the realm of digital curation, human action, machine failure, or human-machine breakdowns can lead to catastrophic data loss. For example, on March 30, 2012, personally identifiable healthcare information of more than 750,000 Utah citizens was stolen when the computer system on which it resided was allowed to retain its out-of-the-box (i.e., “default”) password by a systems administrator (Towns 2012; Henetz 2012; Gibson 2012; Utah Department of Health 2012).

Complex sociotechnical systems are generally composed of yet other systems which are coupled in a variety of configurations themselves. In other words, they are often systems of systems (Ackoff 1971). Because of the complexity of the interactions between all of the components and participants, it is generally difficult or impossible to predict fully the

outcomes of changes in these interactions or to predict the effects on the whole system when a single significant change occurs in one of the component systems. This is because of the large number of possible interaction effects that can occur and because it is not always possible for any given individual to disentangle all of the different ways in which the component systems are coupled. Moreover, because such systems comprise human agency, where agency is defined as “the capability of engaging in action” (Giddens 1984), choice regarding how people will use the technology cannot be fully predicted; thus, the overall impacts of a group of interrelated agents may engender unanticipated consequences. “People adapt systems to their particular work needs, or they resist them or fail to use them at all; and there are wide variances in the patterns of computer use and, consequently, their effects on decision making and other outcomes” (DeSanctis and Poole 1994, 122).

In addition, complex systems are often highly automated, with machinery or computerized technology performing many of the detailed operations, and use of the

technology involving mediated interaction with it. For example, computer interfaces may be used by people in order to present to the people the relevant variables to which they must direct system inputs in order to perform their goal-directed activities.

Finally, complex sociotechnical systems are often characterized by a tendency toward disturbances, where a disturbance is an unpredicted factor that influences the operation of the whole system. For example, financial institutions are prone to economic shocks in the form of unanticipated resource depletion (such as an earthquake influencing supply lines), or external funding resources suddenly drying up due to political shocks (Vicente). Because of this tendency toward disturbances, it is desirable that the system be prepared to respond to unanticipated factors that directly affect some or all of its component properties. In an

exemplary system, people and machines will react flexibility and appropriately to unpredictable shocks.