Best Practices Framework for Enabling High-Performing Virtual Engineering Teams

2019 ◽  
Vol 47 (2) ◽  
pp. 32-44
Author(s):  
Josh Lumseyfai ◽  
Thomas Holzer ◽  
Paul Blessner ◽  
Bill A. Olson
Keyword(s):  
Best Practices ◽  
High Performing ◽  
Engineering Teams ◽  
Virtual Engineering

Virtual Engineering Teams

2010 ◽  
pp. 241-255
Author(s):  
Doug Vogel ◽  
Michiel van Genuchten ◽  
Carol Saunders ◽  
A.-F. Rutkowski
Keyword(s):  
Engineering Teams ◽  
Virtual Engineering

The Prototyping Behaviors of Startups: Exploring the Relationship Between Prototyping Behaviors and Startup Strategies

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Jacob Nelson ◽  
Tobias Mahan ◽  
Christopher McComb ◽  
Jessica Menold
Keyword(s):  
Cluster Analysis ◽  
Best Practices ◽  
New Product Development ◽  
New Product ◽  
High Performing ◽  
Novel Technologies ◽  
Perceived Difficulty ◽  
Survey Responses ◽  
The Relationship ◽  
Crucial Part

Abstract Prototyping is a crucial part of new product development, and engineers and designers rely on prototyping to bring novel technologies to market. In recent years, tech-based startups like Tesla or Udacity have revolutionized their respective industries. However, many tech-based startups are unable to create a viable product with their available resources and fail before ever making it to market. In this work, we analyze survey responses from 34 startup representatives to investigate the relationship between prototyping practice, startup success, and perceived difficulty of startup tasks. K-means cluster analysis shows three distinct groups, differentiated by (1) their amount of available funding, (2) their use of prototyping best practices, and (3) their reported difficulty in startup tasks. High-performing startups reported having the highest funding, experiencing less difficulty in startup tasks, and using prototyping best practices more frequently than their peers.

Differences in transitional care processes among high-performing and low-performing hospital-SNF pairs: a rapid ethnographic approach

2020 ◽  
pp. bmjqs-2020-011204
Author(s):  
Kirstin A Manges ◽  
Roman Ayele ◽  
Chelsea Leonard ◽  
Marcie Lee ◽  
Emily Galenbeck ◽  
...  
Keyword(s):  
High Risk ◽  
Best Practices ◽  
Transitional Care ◽  
Readmission Rates ◽  
High Performing ◽  
High Risk Patients ◽  
Ethnographic Approach ◽  
Care Processes ◽  
Risk Patients ◽  
Postacute Care

BackgroundDespite the increased focus on improving patient’s postacute care outcomes, best practices for reducing readmissions from skilled nursing facilities (SNFs) are unclear. The objective of this study was to observe processes used to prepare patients for postacute care in SNFs, and to explore differences between hospital-SNF pairs with high or low 30-day readmission rates.DesignWe used a rapid ethnographic approach with intensive multiday observations and key informant interviews at high-performing and low-performing hospitals, and their most commonly used SNF. We used flow maps and thematic analysis to describe the process of hospitals discharging patients to SNFs and to identify differences in subprocesses used by high-performing and low-performing hospitals.Setting and participantsHospitals were classified as high or low performers based on their 30-day readmission rates from SNFs. The final sample included 148 hours of observations with 30 clinicians across four hospitals (n=2 high performing, n=2 low performing) and corresponding SNFs (n=5).FindingsWe identified variation in five major processes prior to SNF discharge that could affect care transitions: recognising need for postacute care, deciding level of care, selecting an SNF, negotiating patient fit and coordinating care with SNF. During each stage, high-performing sites differed from low-performing sites by focusing on: (1) earlier, ongoing, systematic identification of high-risk patients; (2) discussing the decision to go to an SNF as an iterative team-based process and (3) anticipating barriers with knowledge of transitional and SNF care processes.ConclusionIdentifying variations in processes used to prepare patients for SNF provides critical insight into the best practices for transitioning patients to SNFs and areas to target for improving care of high-risk patients.

scholarly journals Quantitative Comparison of High- and Low-Performing Teams in a Design Task Subject to Drastic Changes

2014 ◽  
Author(s):  
Christopher McComb ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Design Space ◽  
New Technology ◽  
Problem Formulation ◽  
Target Area ◽  
Design Data ◽  
Design Task ◽  
High Performing ◽  
Engineering Teams ◽  
Solution Strategies ◽  
The Face

Many design tasks are subject to changes in goals or constraints. For instance, a client might modify specifications after design has commenced, or a competitor may introduce a new technology or feature. A design team often cannot anticipate such changes, yet they pose a considerable challenge. This paper presents a study where engineering teams sought to solve a design task that was subject to two large, unexpected changes in problem formulation that occurred during problem solving. Continuous design data was collected to observe how the designers responded to the changes. We show that high- and low-performing teams demonstrated very different approaches to solving the problem and overcoming the changes. In particular, high-performing teams achieved simple designs and extensively explored small portions of the design space; low-performing teams explored complex designs with little exploration around a target area of the design space. These strategic differences are interpreted with respect to cognitive load theory and goal theory. The results raise questions as to the relationship between characteristics of design problems and solution strategies. In addition, an attempt at increasing the teams’ resilience in the face of unexpected changes is introduced by encouraging early divergent search.

scholarly journals Adopting global virtual engineering teams in AEC Projects

2015 ◽  
Vol 15 (2) ◽  
pp. 151-179 ◽  
Author(s):  
M.Reza Hosseini ◽  
Nicholas Chileshe ◽  
Jian Zuo ◽  
Bassam Baroudi
Keyword(s):  
Conceptual Model ◽  
Innovation Diffusion ◽  
Critical Review ◽  
Small Sample Size ◽  
Relevant Literature ◽  
Research Field ◽  
Small Sample ◽  
Content Type ◽  
Engineering Teams ◽  
Virtual Engineering

Purpose – This study aims to present an integrated conceptual model in order to highlight the major aspects of diffusion of innovations in the architecture, engineering and construction (AEC) context. To this end, a critical review of literature is conducted, accompanied by synthesising the findings of previous studies. The driving force behind this study is stemmed from the fragmentation of literature on innovation diffusion, and paucity of research on diffusion of Global Virtual Engineering Teams (GVETs) as the platform for many technological innovations in relevant literature. Thus, the present study is intended to facilitate filling the gap in GVETs literature. That is, the proposed model will offer a foundation for academia for grounding studies on any innovation including GVETs in the literature on innovation diffusion in the AEC context. Design/methodology/approach – This paper draws upon the qualitative meta-analysis approach encompassing a critical review of the relevant literature. To this end, the review builds upon studies found within 15 prestigious journals in AEC. The domain of this review was confined to areas described as “innovation”, “innovation diffusion” and “innovation adoption”, along with keywords used within a broad review of recently published GVETs literature. The rigour of review is augmented by incorporating 35 authoritative works from other disciplines published in 21 well-known journals in the manufacturing, business and management fields. Moreover, the study deploys the peer-debriefing approach through conducting unstructured interviews with five Australian scholars to verify a model presenting an aggregated summary of previous studies. Findings – The key findings of the study include the following items: synthesising the fragmented studies on innovation diffusion in the AEC context. In doing so, a model capturing the major aspects affecting diffusion of an innovation in AEC projects is presented; providing a foundation to address the drawbacks of previous studies within the sphere of GVETs, based on the developed model. Research limitations/implications – The developed model was only enhanced using a small sample size of academics, as such not empirically validated. Originality/value – As possibly, the first literature review of innovation in the AEC context, this paper contributes to the sphere by sensitising the AEC body of knowledge on innovation diffusion as a concise conceptual model, albeit verified through the peer-debriefing approach. This study will also further establish the research field in AEC on GVETs along with other methods reliant on virtual working such as building information modelling (BIM) through providing an expanded foundation for future inquiries and creation of knowledge.

scholarly journals ICT Tools Functionalities Analysis for the Decision Making Process of Their Implementation in Virtual Engineering Teams

2012 ◽  
Vol 5 ◽  
pp. 649-658 ◽  
Author(s):  
Cosmina Carmen Aldea ◽  
Anca-Diana Popescu ◽  
Anca Draghici ◽  
George Draghici
Keyword(s):  
Decision Making ◽  
Decision Making Process ◽  
Engineering Teams ◽  
Virtual Engineering ◽  
Ict Tools

Utilizing QOPI in the quality improvement efforts of the NCI Community Cancer Centers Program (NCCCP).

2012 ◽  
Vol 30 (34_suppl) ◽  
pp. 208-208
Author(s):  
Robert D. Siegel ◽  
Holley Stallings ◽  
Donna M. Bryant ◽  
Pamela Kadlubek ◽  
Laurel Borowski ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Quality Of Care ◽  
Best Practices ◽  
New England ◽  
Community Based ◽  
Quality Initiatives ◽  
Cancer Centers ◽  
High Performing ◽  
Oncology Practice

208 Background: The NCCCP is a network of community based institutions from New England to Hawaii funded by the NCI. Quality of care is a priority of the NCCCP with participation in ASCO’s Quality Oncology Practice Initiative (QOPI) playing a fundamental role. QOPI provides a process for quality assessment but we have also used it as a measure of quality improvement (QI) network-wide. Using QOPI methodology, we have analyzed our performance twice a year in an effort to enhance our implementation of quality indicators relevant to program aims. Methods: A data sharing agreement allows individual practice QOPI data to be electronically sent to the NCI where it is aggregated with the other NCCCP QOPI participants. Data are presented via webinar within the network using a variety of QI strategies. For example, blinded site performance distributions are benchmarked against NCCCP national averages on specific indicators. High performing practices voluntarily present their QI initiatives and best practices to the network. The NCCCP Quality of Care Subcommittee then selects QI projects and areas to focus quality improvement efforts. Results: In Spring 2012, 44 practices affiliated with 25 NCCCP sites participated in QOPI, a consistent pattern since Fall 2010. The table below describes the percent compliance with certain QOPI measures for the NCCCP aggregate over time. Selected measures were perceived as having had suboptimal compliance in Fall 2010. Conclusions: QOPI is an effective tool for assessing quality within a network and for measuring quality improvement efforts. Best practices from within the network can be leveraged and disseminated to enhance the quality of cancer care. This methodology facilitates quality initiatives despite the logistical challenges of working with practices across the country. [Table: see text]

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