Question B: What Are The Critical Factors To Consider? ✓ Solved

Question B What are the critical factors to consider in the design of a

Question B What are the critical factors to consider in the design of a work system? What role does technology play in the design of work systems? Use data from credible outside resources to backup your response.

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The design of a work system is a holistic activity that requires balancing people, processes, information, and technology to create value for customers and the organization. A strong starting point is Leavitt’s Diamond framework, which argues that any change in an organizational system must consider four interdependent facets: people, tasks (processes), structure, and technology. If one facet changes without corresponding adjustments in the others, performance tends to deteriorate (Leavitt, 1965). This insight remains foundational for evaluating critical factors in work-system design: alignment among people, workflows, governance, and technology, all anchored by strategic purpose and customer needs. In practice, this means ensuring that the work system’s design reflects intended outcomes, supports the required behaviors of workers, and leverages technology to enable, not merely automate, tasks (Hackman & Oldham, 1976; Henderson & Venkatraman, 1993).

First, define the system’s purpose and the customer value it is intended to deliver. Strategic alignment—ensuring IT and business strategies reinforce each other—helps prevent misaligned investments in technology that do not support value creation (Henderson & Venkatraman, 1993). In today’s digitized environments, this requires explicit mapping of customer requirements to end-to-end processes and the information needed to satisfy those requirements. The focus should be on outcomes and capabilities, not just activities. The design should answer: Who is served? What is produced? How is quality defined and measured? How will success be tracked over time? These questions link directly to the strategic alignment concept and to the design principles articulated in the work-system literature (Laudon & Laudon, 2016; Henderson & Venkatraman, 1993).

Second, consider the core processes and workflow configuration. Process design should emphasize end-to-end value creation, rather than isolated task optimization. The work-system approach emphasizes that processes, information, and technology must be co-designed to produce reliable performance. Process redesign should also account for variability, bottlenecks, and error-prone handoffs, with a view toward reducing handoffs and delays while maintaining quality. Classic work-design research shows that meaningful work, autonomy, and task significance—dimensions embedded in the Job Characteristics Model—are associated with higher motivation and performance when tasks are designed to be meaningful and congruent with workers’ capabilities (Hackman & Oldham, 1976).

Third, address the roles, capabilities, and motivation of people in the system. People are not only the executors of tasks; they interpret information, adapt to changes, and learn from feedback. Work-system design must consider capabilities, training needs, and the social and organizational context in which workers operate. Change-management considerations—communication, involvement, and skill development—are critical for achieving adoption and sustaining improvements. The social-technical literature emphasizes that successful interventions require alignment of people, tasks, technology, and organizational structure, with ongoing learning and adaptation (Senge, 1990; Hackman & Oldham, 1976).

Fourth, design the technology architecture to enable, rather than constrain, performance. Technology should enable timely information, reliable automation, and scalable integration across the value stream. It should support decision rights, data governance, and interoperability—principles central to strategic IT alignment (Davenport & Short, 1990; Henderson & Venkatraman, 1993). Contemporary technology keeps raising the bar: smart, connected products and data-driven capabilities create new competitive dynamics and require new governance models, architectures, and cybersecurity considerations (Porter & Heppelmann, 2014; Brynjolfsson & McAfee, 2014).

Fifth, governance, risk, and compliance are essential design factors. Clear decision rights, performance metrics, accountability, and risk controls help ensure that the work system operates within acceptable boundaries and can adapt when external conditions change. Leavitt’s Diamond emphasizes that governance and structure must align with people and technology; misalignment can erode trust, decrease adoption, and degrade performance (Leavitt, 1965).

Sixth, measurement, feedback, and learning loops are critical for ongoing improvement. Establishing meaningful metrics tied to customer value, quality, cycle time, and cost provides feedback that informs iterative redesign. The learning organization literature argues that continuous learning capabilities—shared mental models, reflection, and systemic thinking—are core to sustaining improvements in complex work systems (Senge, 1990).

Seventh, and particularly relevant in the context of digital upgrades, is the role of technology in enabling new capabilities while preserving a humane and usable work environment. Technology can automate routine tasks, augment decision-making with analytics, and enable remote or distributed work. However, automation must be designed with human-in-the-loop principles, ensuring workers can supervise, intervene, and learn from automated processes. This balance between automation and augmentation is central to modern work-system design and is highlighted in discussions of digital transformation and smart-enabled operations (Porter & Heppelmann, 2014; Brynjolfsson & McAfee, 2014).

In the KandyLand case, the organization confronts classic work-system design tensions: (1) misaligned technology across departments (orders placed online are correctly fulfilled 98% of the time, while phone-based order-entry appears erroneous at 98%), indicating a mismatch in information flows and system interoperability (Leavitt, 1965; Davenport & Short, 1990); (2) customer behavior and capability gaps—over half of phone-order customers are not comfortable ordering electronically—creating a risk that a wholesale move to online entry could erode orders or satisfaction if not managed with change programs and support (Hackman & Oldham, 1976); (3) a change-management plan that includes training, communications, and QA feedback loops (Senge, 1990; Alter, 2013); and (4) governance questions about workforce reallocation, staffing ratios, and potential layoffs, which require careful alignment of people, processes, and technology (Leavitt, 1965; Henderson & Venkatraman, 1993).

From a theoretical perspective, the factors above align with established frameworks: Leavitt’s Diamond draws attention to the interdependence of people, processes, technology, and structure; Hackman and Oldham’s work-design insights highlight how task design influences motivation and performance; and modern digital-transformation research emphasizes that technology is a strategic enabler shaping competition and operational capability (Leavitt, 1965; Hackman & Oldham, 1976; Porter & Heppelmann, 2014; Brynjolfsson & McAfee, 2014; Westerman, Bonnet, & McAfee, 2014). The Work System Method and related IS literature further stress that IT projects succeed when they are embedded in a holistic view of value creation, workflow, and governance (Alter, 2013). Practically, the critical factors to consider in any work-system design, including a shift to online ordering as in the KandyLand case, include clear value definitions, end-to-end process redesign, capability-building for workers, interoperable technology architectures, robust governance, and a strong feedback-driven improvement culture (Davenport & Short, 1990; Henderson & Venkatraman, 1993; Senge, 1990).

In summary, technology plays a central enabling role in modern work-system design but must be deployed in a carefully aligned context that considers people, processes, governance, and organizational strategy. A successful redesign—whether moving to online order entry or reconfiguring call-center responsibilities—requires a holistic view grounded in established theory and tested through iterative experimentation, training, and measurement. This approach reduces the risk of unintended consequences and supports sustainable performance improvements aligned with customer value and strategic goals (Hackman & Oldham, 1976; Leavitt, 1965; Davenport & Short, 1990; Porter & Heppelmann, 2014; Brynjolfsson & McAfee, 2014; Westerman, Bonnet, & McAfee, 2014; Senge, 1990; Alter, 2013; Laudon & Laudon, 2016).

References

  • Alter, A. L. (2013). A Work System Method for information systems. Communications of the Association for Information Systems, 32(1), 63-85.
  • Davenport, T. H., & Short, J. E. (1990). The new industrial engineering: Information technology and business processes. Sloan Management Review, 31(4), 11-27.
  • Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250-279.
  • Henderson, J. C., & Venkatraman, N. (1993). Strategic alignment: A model for information technology and business. MIS Quarterly, 17(1), 1-23.
  • Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.
  • Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. Norton.
  • Senge, P. M. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization. Doubleday.
  • Laudon, K. C., & Laudon, J. P. (2016). Management Information Systems: Managing the Digital Firm (14th ed.). Pearson.
  • Leavitt, H. J. (1965). Applied Organizational Change: Why some changes fail. Harvard Business Review.

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