MGT 726 Week 1 Emerging Managerial Practices Example

Innovation or Fashion? Evaluating Emerging Managerial Practices at a Global Instrument Manufacturer

[Student Name]

University of Phoenix

MGT/726: Emerging Managerial Practices

Week 1 Assignment

[Instructor Name]

[Date]

Cedar Valley Instruments and all details are composites written for a model paper.

Cedar Valley Instruments, a composite company headquartered in Cedar Rapids, Iowa, designs and makes laboratory and process measurement instruments sold to pharmaceutical, food and energy companies worldwide. It employs 2,300 people in Iowa, Monterrey, Mexico and Pune, India, including 700 engineers and office staff now working in hybrid arrangements. After a leadership retreat, executives proposed adopting generative AI assistants for all office staff, objectives and key results for goal setting, agile teams across engineering and operations and a people analytics function, while debating hybrid work policies. New management practices arrive with confident promises, and the hardest skill for leaders is telling the ideas that will improve their organization from those that are simply in the air. This paper sets out how Cedar Valley should evaluate emerging managerial practices.

Defining Management Innovation

Birkinshaw et al. (2008) defined management innovation as the invention and implementation of a management practice, process, structure or technique that is new to the state of the art and intended to further organizational goals. They distinguished it from technological innovation and described four perspectives on how it occurs: institutional, fashion, cultural and rational. The rational perspective, in which managers introduce practices to solve real problems, is the one Cedar Valley should aim for, while the fashion perspective describes the risk it faces.

Where New Practices Come From

Mol and Birkinshaw (2009) studied firms that introduced new management practices and found that search for new knowledge, including from outside sources such as consultants and universities, and internal conditions such as performance problems were associated with introducing management innovations, and that innovations were linked to productivity gains.

Why Fashions Spread

Abrahamson (1996) argued that management fashions are shaped by fashion setters, consultants, gurus, business media and business schools, who promote ideas that appear rational and progressive. Practices may spread because adopting them signals modernity, not because they work. Earlier work by Abrahamson (1991) explained that firms often imitate peers under uncertainty, adopting practices others have adopted.

The Risk for Cedar Valley

Several of the proposed practices arrived through conference talks and peer companies. Without evaluation, Cedar Valley could adopt them because competitors have, spend heavily and then abandon them, damaging employees' trust in future initiatives.

Evidence-Based Management

Rousseau (2006) proposed that managers, as physicians do, ground its routine decisions in the strongest available research rather than habit or fashion. Later work describes it as combining four sources: scientific research, organizational data, professional expertise and stakeholder concerns. This approach provides a disciplined way to evaluate new practices.

Criteria for Evaluating Practices

Cedar Valley will use five criteria: the quality and relevance of research evidence, fit with the company's context and work, the availability of local data to test the practice, the cost and reversibility of adoption and the views of employees and other stakeholders affected.

Practice One: Hybrid Work

Research on remote and hybrid work is substantial and mixed. Some randomized studies find productivity and retention benefits in certain jobs, while other studies find reduced cross-team collaboration. Evidence is relatively strong, but effects depend on the type of work, so Cedar Valley should tailor policies by role rather than adopting one rule.

Practice Two: Generative AI Assistants

Early experimental studies find productivity gains for some writing and customer support tasks, especially for less experienced workers. Evidence is promising but new and concentrated in specific tasks. Cedar Valley should pilot AI tools in defined tasks with measured outcomes and safeguards for confidential engineering data.

Practice Three: Agile Teams

Agile practices have evidence of benefits in software and product development but less in routine operations, where stable, standardized work is a strength rather than a weakness. They fit Cedar Valley's engineering and product groups more than its plants.

Practice Four: Objectives and Key Results

Objectives and key results draw on goal-setting research, which is strong, but rigorous evidence on the specific framework is thin. Cedar Valley could test it in a few units rather than company-wide.

Practice Five: People Analytics

People analytics can improve decisions about hiring, retention and development, but depends on data quality and raises privacy concerns, especially across three countries' laws. Cedar Valley should start with specific questions, such as engineer retention, and build data governance first, with clear rules about what data are collected, who sees them and how employees can see their own records.

Testing Practices Locally

Published research rarely matches an organization's exact situation, so evidence-based management stresses local data. Cedar Valley can design small tests: comparing engineering teams that use AI assistants for documentation with similar teams that do not, or tracking collaboration patterns among hybrid and on-site staff using anonymized calendar data. Such tests are inexpensive, respect employees' privacy when designed carefully and give leaders evidence specific to their company.

The Cost of Initiative Fatigue

Employees at Cedar Valley have seen several initiatives arrive and fade, including a lean program that was dropped after two years and a performance management redesign that was reversed. A survey found that 61 percent of employees doubted new initiatives would last. Adopting five practices at once would deepen this skepticism. Choosing fewer practices, explaining the evidence behind them and committing to evaluate them openly can rebuild credibility.

Stakeholder Perspectives

Engineers welcome AI tools but worry about being evaluated by them. Plant supervisors see agile as an engineering fad unsuited to production lines. Employees in Pune and Monterrey ask whether hybrid policies will apply equally to them. These concerns are part of the evidence, as evidence-based management recognizes, and they shape how practices should be introduced.

Practices That Vary as They Spread

Practices rarely transfer unchanged. Adapting them to local context can improve fit but may weaken the features that made them effective elsewhere. Cedar Valley's plants in Mexico and India may need different versions of the same practice.

Sequencing Adoption

The evaluation suggests a sequence rather than a single launch. Hybrid work policies, already in effect informally, should be clarified by role within the next quarter. Generative AI tools should be piloted in two engineering teams and the customer support group with clear rules on data. Agile methods should expand only in product development. Objectives and key results and people analytics should wait until data governance and goal-setting practices are in better shape. A staggered approach lets each practice be evaluated before the next arrives.

Questions for the Course

Several questions follow for the rest of the course: how to build organizational agility, how to adapt best practices, how to design high-performance and distributed teams, how to communicate across cultures, how to foster creativity and what research says about management innovation's effects.

Conclusion

Emerging managerial practices may be genuine innovations or passing fashions. Research on management innovation, fashion and evidence-based management gives Cedar Valley criteria to evaluate them. Applied to five proposed practices, the criteria favor tailored hybrid work, piloted AI tools and agile in engineering, with caution on objectives and key results and data-first people analytics.

References

Abrahamson, E. (1991). Managerial fads and fashions: The diffusion and rejection of innovations. Academy of Management Review, 16(3), 586-612. https://doi.org/10.2307/258919

Abrahamson, E. (1996). Management fashion. Academy of Management Review, 21(1), 254-285. https://doi.org/10.2307/258636

Birkinshaw, J., Hamel, G., & Mol, M. J. (2008). Management innovation. Academy of Management Review, 33(4), 825-845. https://doi.org/10.5465/amr.2008.34421969

Mol, M. J., & Birkinshaw, J. (2009). The sources of management innovation: When firms introduce new management practices. Journal of Business Research, 62(12), 1269-1280. https://doi.org/10.1016/j.jbusres.2009.01.001

Rousseau, D. M. (2006). Is there such a thing as "evidence-based management"? Academy of Management Review, 31(2), 256-269. https://doi.org/10.5465/amr.2006.20208679