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Sociotechnical Systems Savvy
[edit]Sociotechnical systems savvy, or systems savvy, is a concept describing an individual's capacity to understand, design, and use sociotechnical systems..[1] More specifically, systems savvy is an individual's ability to see the interdependence of social/organizational and technological systems and to create synergies between them. Systems savvy is a specific form of Robert J. Sternberg's practical intelligence[2][3] that enables individuals to effectively navigate the complexities of modern work environments where technology and social structures are deeply intertwined.
Overview
[edit]Individuals with high systems savvy are better able to recognize, understand, and act upon the integration of technology and social systems.[1] This includes being able to encode elements of both technological and social systems to gain a rich understanding of the problem, and to develop and act on potential relationships between technological and social systems. Sociotechnical systems savvy is similar to systems thinking, but with a specific on the sociotechnical system, rather than systems as a whole.
A recent article in The Hill Times likens systems savvy to other foundational skills like reading and math.
Systems savvy involves several key characteristics that enable individuals to integrate social and technical aspects of work effectively:
- Metacognitive ability: Systems savvy individuals can engage in higher-order planning and avoid being locked into a single perspective or dominant frame.
- Performance component: They can infer and act upon relationships between technology, people, and social systems, including recognizing emerging patterns.
- Knowledge acquisition: They can learn from their interactions with technology and social systems, refining their understanding of sociotechnical synergies.
- Multidimensional thinking: They look for solutions that go beyond technology or organizational approaches alone.
- Adaptability: Systems savvy enables individuals to adapt to, shape, and/or select more effective sociotechnical integrations.
- Systems thinking: Systems savvy incorporates and goes beyond systems thinking. While systems thinking is the capacity to see the whole, systems savvy includes the ability to understand how to intertwine the parts for better, more adaptive performance.
Systems Savvy vs. Other Concepts
[edit]Several other concepts are related to systems savvy, but it remains a unique construct:
- General intelligence: General intelligence is a broad assessment, while systems savvy is a more focused capability[1][4].
- Expertise: Expertise may limit systems savvy if people anchor on present uses or bring prior rigidities[5].
- Personal innovativeness in IT: This is an antecedent that combines with experience in the development of systems savvy[6].
- Mindfulness of technology adoption: Mindfulness is a motivator to apply systems savvy, but it is focused on technology rather than the interaction of technical and social dimensions[7].
- Business competence of IT professionals: Business competence is an outcome of systems savvy. Systems savvy provides the background to build the specific knowledge and skills needed for business competence[8].
- Computer self-efficacy: Systems savvy supports the development of computer self-efficacy[9].
- Task-relevant individual capabilities: Task-relevant individual capabilities can interact with systems savvy to increase both the compensatory possibilities of task-relevant user capabilities and the opportunity for more synergistic engagement of the human and technical dimensions of the task[10]
Development of Systems Savvy
[edit]Systems savvy is a form of tacit knowledge that develops through experience, but not everyone profits equally from experience.[11] It is enhanced by personal innovativeness in information technology.[6] While expertise can be valuable for systems savvy, it is not required, as deep expertise may limit the ability to see new possibilities.[5] Systems savvy can be learned,[1] which offers opportunities to proactively respond to the demands of a technologically complex future of work. Training focused on reflection and hands-on, contextually-situated presentations is expected to support the development of systems savvy.
Measurement of Systems Savvy
[edit]Systems savvy can be measured using several methods:
- Situational Judgment Tests (SJTs): These tests present respondents with scenarios and ask them to rank or rate different courses of action.[12][13] Situational judgment tests are effective in capturing systems savvy by assessing how individuals understand and address sociotechnical situations.[1]
- Machine Learning (ML) Methods: ML can be used to analyze text data (such as comments, written work products) and assess systems savvy based on word vector distances from base responses.[14] This approach is particularly useful for large-scale assessments.[15]
Empirical Evidence
[edit]Both experimental and archival research support systems savvy's ability to predict work and individual outcomes:
- Experienced professionals tend to select multi-dimensional solutions, while novices prefer unidimensional approaches.[1]
- Systems savvy is distinct from self-reported sociotechnical awareness, with systems savvy significantly increasing the ability to differentiate successful professionals from novices.[1]
- Systems savvy can predict individual sentiment toward sociotechnical change.[15]
- Systems savvy offers incremental value beyond more general constructs related to individual situational assessments, such as integrative complexity.[15]
Understanding and measuring sociotechnical systems savvy can be applied in various contexts:
- Recruitment: Identifying individuals with high systems savvy can inform selection and training programs, especially as work becomes more complex and integrated with technology.
- Team Design: Team composition can be optimized by considering the systems savvy of team leaders and members, as systems savvy facilitates more effective collaboration and adaptation.
- Change Management: Systems savvy is essential to managing the changes that accompany the evolution of technical and social systems.
- Technology Design: Understanding systems savvy can guide the design of technology and organizational practices to support effective sociotechnical integration.
- Work Crafting: Sociotechnical systems savvy may support individuals in designing their work and leveraging the resources at hand.
References
[edit]- ^ a b c d e f g h i Griffith, Terri L.; Sawyer, John E.; Poole, M. Scott (2019-06-01). "Systems Savvy: Practical Intelligence for Transformation of Sociotechnical Systems". Group Decision and Negotiation. 28 (3): 475–499. doi:10.1007/s10726-019-09619-4. ISSN 1572-9907.
- ^ Sternberg, Robert J. (1981-07-01). "The evolution of theories of intelligence". Intelligence. 5 (3): 209–230. doi:10.1016/S0160-2896(81)80009-8. ISSN 0160-2896.
- ^ Sternberg, Robert J. (1984). "Toward a triarchic theory of human intelligence". Behavioral and Brain Sciences. 7 (2): 269–287. doi:10.1017/S0140525X00044629. ISSN 0140-525X.
- ^ Sternberg, R. J., Kaufman, J. C., & Grigorenko, E. L. (2008). Applied intelligence. Cambridge University Press.
- ^ a b Kahneman, D. (1992). Reference points, anchors, norms and mixed feelings. Organ Behav Hum Decis Process, 51(2), 296–312.
- ^ a b Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Inf Syst Res, 9, 204–215.
- ^ Sun, H., Fang, Y., & Zou, H. (2016). Choosing a fit technology: understanding mindfulness in technology.
- ^ Joseph, D., Ang, S., Chang, R. H. L., & Slaughter, S. A. (2010). Practical intelligence in IT: assessing soft skills of IT professionals. Commun ACM, 53(2), 149–154.
- ^ Compeau, Deborah R.; Higgins, Christopher A. (1995). "Computer Self-Efficacy: Development of a Measure and Initial Test". MIS Quarterly. 19 (2): 189–211. doi:10.2307/249688. ISSN 0276-7783.
- ^ Serrano, C. I., & Karahanna, E. (2016). The compensatory interaction between user capabilities and technology capabilities in influencing task performance: an empirical assessment in telemedicine consultations. MIS Q, 40(3), 597–621.
- ^ Sternberg, Robert (1999). "The theory of successful intelligence". Review of General Psychology. 3 (4): 292–316.
- ^ Weekley, J. A., Ployhart, R. E. (2006). An introduction of situational judgment tests: their nature and history. In: Weekley JA, Ployhart RE (eds) Situational judgment tests. Lawrence Erlbaum, Mahwah, pp 1–10.
- ^ Chan, D., & Schmitt, N. (2002). Situational judgment and job performance. Hum Perform, 15(3), 233–254.
- ^ Padmanabhan, V., Singh, V., & Mittal, P. (2022). Machine Learning as a Methodological Tool in Management Research: A Review and Recommendations.
- ^ a b c d Kaligotla, Chaitanya; Griffith, Terri; MacLeod, Alex (2024). "Large Scale ML-Based Methods for Studying Individual Responses to Work Using Systems Savvy Measures". Academy of Management Proceedings. 2024 (1): 17186. doi:10.5465/AMPROC.2024.17186abstract. ISSN 0065-0668.