Effective interdisciplinary collaboration between statisticians and other subject matter experts

被引:8
作者
Anderson-Cook, Christine M. [1 ]
Lu, Lu [2 ]
Parker, Peter A. [3 ]
机构
[1] Los Alamos Natl Lab, Stat Sci Grp, Los Alamos, NM 87545 USA
[2] Univ S Florida, Dept Math & Stat, Tampa, FL USA
[3] NASA Langley, Res Directorate, Adv Measurement & Data Syst Branch, Hampton, VA USA
关键词
Statistical engineering; interdisciplinary collaboration; team; decision-making; problem-solving; INNOVATION; WELL;
D O I
10.1080/08982112.2018.1530357
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Progress and innovative solutions to challenging problems often come at the intersection of multiple disciplines. Statisticians frequently are presented with opportunities to participate on or lead interdisciplinary teams, where how well their contributions are received is a function of their effectiveness as collaborators. In this article, we outline six fundamentals for effective collaboration: respect, shared common goals, trust, commitment, intercommunication, and execution. We focus on how these core aspects of a successful collaboration can be encouraged by statisticians. Through an example, we illustrate how problems can arise when some of the key components are missing and what strategies can be used to mitigate problems. Finally, we describe how early career statisticians can work to improve their collaboration skills to improve their impact on teams with diverse backgrounds.
引用
收藏
页码:164 / 176
页数:13
相关论文
共 34 条
  • [1] Anderson-Cook C.M., 2015, Quality Progress, V48, P42
  • [2] Anderson-Cook C. M., 2010, QUAL PROG, V43, P36
  • [3] Bayesian stockpile reliability methodology for complex systems
    Anderson-Cook, Christine M.
    Graves, Todd
    Hamada, Michael
    Hengartner, Nicholas
    Johnson, Valen E.
    Reese, C. Shane
    Wilson, Alyson G.
    [J]. MILITARY OPERATIONS RESEARCH, 2007, 12 (02) : 25 - 37
  • [4] Graphics to facilitate informative discussion and team decision making
    Anderson-Cook, Christine M.
    Lu, Lu
    [J]. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 2018, 34 (06) : 963 - 980
  • [5] Statistical Mentoring at Early Training and Career Stages
    Anderson-Cook, Christine M.
    Hamada, Michael S.
    Moore, Leslie M.
    Wendelberger, Joanne R.
    [J]. AMERICAN STATISTICIAN, 2017, 71 (01) : 6 - 14
  • [6] Optimizing in a complex world: A statistician's role in decision making
    Anderson-Cook, Christine M.
    [J]. QUALITY ENGINEERING, 2017, 29 (01) : 27 - 41
  • [7] Statistical Engineering-Roles for Statisticians and the Path Forward
    Anderson-Cook, Christine M.
    Lu, Lu
    Clark, Gordon
    DeHart, Stephanie P.
    Hoerl, Roger
    Jones, Bradley
    MacKay, R. Jock
    Montgomery, Douglas
    Parker, Peter A.
    Simpson, James
    Snee, Ronald
    Steiner, Stefan H.
    Van Mullekom, Jennifer
    Vining, G. Geoff
    Wilson, Alyson G.
    [J]. QUALITY ENGINEERING, 2012, 24 (02) : 133 - 152
  • [8] Statistical Engineering-Forming the Foundations
    Anderson-Cook, Christine M.
    Lu, Lu
    Clark, Gordon
    DeHart, Stephanie P.
    Hoerl, Roger
    Jones, Bradley
    MacKay, R. Jock
    Montgomery, Douglas
    Parker, Peter A.
    Simpson, James
    Snee, Ronald
    Steiner, Stefan H.
    Van Mullekom, Jennifer
    Vining, G. Geoff
    Wilson, Alyson G.
    [J]. QUALITY ENGINEERING, 2012, 24 (02) : 110 - 132
  • [9] Opportunities and Issues in Multiple Data Type Meta-Analyses
    Anderson-Cook, Christine M.
    [J]. QUALITY ENGINEERING, 2009, 21 (03) : 241 - 253
  • [10] Reliability Modeling using Both System Test and Quality Assurance Data
    Anderson-Cook, Christine M.
    Graves, Todd
    Hengartner, Nicolas
    Klamann, Richard
    Wiedlea, Andrew C. K.
    Wilson, Alyson G.
    Anderson, Greg
    Lopez, George
    [J]. MILITARY OPERATIONS RESEARCH, 2008, 13 (03) : 5 - 18