Case Studies in Performance Improvement

Mulder, Martin

doi:10.1177/152342239900100106

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…Often these information‐gathering methods and tools try to emulate those long‐utilized by experimental researchers. However, due to the complex nature of organizational phenomena, true experimental designs often gain little traction as a viable option for performance improvement (PI) practitioners seeking tools that are useful and cost‐effective to implement (Mulder, ). As the key purpose of any improvement effort is to learn from the past in order to predict or change the future, or to learn from best practices identified in one work unit in order to scale up or replicate in another work unit, it is important to invest in methods that will enable the practitioner to easily capture information from the particular in order to generalize to other relevant work groups.…”

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confidence: 99%

Case Study Research: A Valuable Learning Tool for Performance Improvement Professionals

Turner¹,

Danks²

2014

Perf. Improv.

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Although it is sometimes recommended that performance improvement (PI) professionals include experimental research designs in their repertoire of PI tools and methods, it has been long understood that experimental designs can be difficult to implement due to impediments resulting from the complex nature of the organizational settings. However, the utilization of case study research has proven to be an effective alternative to aid in the identification of strengths and opportunities for the improvement of organizational procedures, policies, processes, or programs. Case study research helps managers and practitioners make sense of real world problems. This article presents a summary of steps in the design of case study research and provides examples of how these methods have been used within organizational settings.Implications for PI practitioners are provided. PERFORMANCE IMPROVEMENT PROFESSIONALS use a variety of processes, methods, and tools to help in the understanding of problems, to help design interventions that address these problems, and to evaluate the effectiveness of the selected interventions to ensure a proper return on expectations. Often these information-gathering methods and tools try to emulate those long-utilized by experimental researchers. However, due to the complex nature of organizational phenomena, true experimental designs often gain little traction as a viable option for performance improvement (PI) practitioners seeking tools that are useful and cost-effective to implement (Mulder, 1999 ). As the key purpose of any improvement effort is to learn from the past in order to predict or change the future, or to learn from best practices identified in one work unit in order to scale up or replicate in another work unit, it is important to invest in methods that will enable the practitioner to easily capture information from the particular in order to generalize to other relevant work groups. Case study research is an often neglected but useful research methodology that can be utilized to accomplish this. It is an effective tool for managers and practitioners to make better sense of workplace issues, thus further supporting problem solving and PI efforts, and one that all practitioners should have in their PI toolboxes.The purpose of this article is to briefly summarize the key steps involved in the design of case study research, and to present examples of case studies in which the results were used to inform the design of policies, practices, or other processes to improve performance in organizations. Although it is not the goal of this article to present exemplars in case study design, the reader may be able to identify commonalities between the issues and needs inherent in each of the cases and the reader's own organization, and to extract applications that will help in the translation of case study findings into learning opportunities.

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confidence: 99%

Case Study Research: A Valuable Learning Tool for Performance Improvement Professionals

Turner¹,

Danks²

2014

Perf. Improv.

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“…Case studies [Gerring, 2006, Verner et al, 2009 have high potential for analyzing perfor-6.2 mance improvement, and they are appropriate for studying complex performance issues [Mulder, 1999].…”

Section: Research Methods -Multiple-case Studiesmentioning

confidence: 99%

Productivity of agile teams: an empirical evaluation of factors and monitoring processes

Melo¹

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Lower cost and shorter time-to-market expectations are the major drivers of software productivity improvements. To manage productivity effectively, it is important to identify the most relevant difficulties and develop strategies to cope with them. Agile methods, including Extreme Programming and Scrum, have evolved as approaches to simplify software development process, potentially leading to better productivity. They aim to shorten development time and handle the inevitable changes resulting from market dynamics.Although the industry has extensively adopted agile methods, little research has empirically examined the software development agility construct regarding its dimensions, determinants, and effects on software development performance. Understanding this construct could help determine where to concentrate management efforts (and related financial resources) from a practical standpoint and where to focus research efforts from an academic perspective.Considerable research has been directed at identifying factors that have a significant impact on software development productivity. In general, the studied productivity factors were related to product, personnel, project, process, or organizational issues. Continuously evaluating productivity factors is important, as factors may change under new software engineering practices. However, little research has investigated the major factors influencing agile team productivity.The goal of this thesis was to explore productivity definitions, factors, and monitoring in agile teams and to improve the practice based on the collected evidence and gained knowledge. This thesis presents five novel contributions: C1 -Empirical verification of the importance of productivity for companies adopting agile methods and its perceived benefits; C2 -Rationale for the definition of productivity in the context of agile methods; C3 -Empirical verification of agile team productivity factors; C4 -A conceptual framework for agile team productivity factors and their impact; C5 -A team productivity monitoring process considering adaptability and an evaluation of the usefulness of agile team productivity metrics.

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