Problem framing: Essential to successful statistical engineering applications

被引:2
|
作者
Hoerl, Roger W. [1 ]
Kuonen, Diego [2 ]
Redman, Thomas C. [3 ]
机构
[1] Union Coll, Mathemat Dept, Schenectady, NY USA
[2] Univ Geneva, Berne & Geneva Sch Econ & Management, Statoo Consulting, Bern, Switzerland
[3] Navesink Consulting Grp LLC, Rumson, NJ USA
关键词
analytics; complexity; data science; problem framing; problem-solving; problem structuring; quality engineering; statistics; statistical engineering; PROBLEM STRUCTURING METHODS;
D O I
10.1080/08982112.2022.2113098
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The first two phases of the statistical engineering process are to identify the problem, and to properly structure it. These steps relate to work that is often referred to elsewhere as framing of the problem. While these are obviously critical steps, we have found that problem-solving teams often "underwhelm" these phases, perhaps being over-anxious to get to the analytics. This approach typically leads to projects that are "dead on arrival" because different parties have different understandings of what problem they are actually trying to solve. In this expository article, we point out evidence for a consistent and perplexing lack of emphasis on these first two phases in practice, review some highlights of previous research on the problem, offer tangible advice for teams on how to properly frame problems to maximize the probability for success, and share some real examples of framing challenging problems.
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页码:473 / 481
页数:9
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