Case Study Solicitation 

One of the best ways we can improve our efforts as statistical engineers is to learn from the successes (and even failures) of our colleagues. Since the inception of ISEA, case studies have been recognized as one of the primary vehicles of sharing this knowledge. We recognize that it can be difficult to find a good journal for case studies, especially those we believe would be the most beneficial for training in statistical engineering. As such, we are submitting a formal call to our members to submit case studies for sharing in our regularly scheduled newsletter. You can submit your manuscript to our review team at this email: casestudies@isea-change.org.

This will be an excellent opportunity for all of us as members to share our experiences, especially those that fall outside of technical methodology. To ensure the best value for our readers, we ask that you please ensure your manuscript aligns with the following guidelines. 

Case Study Guidelines

Tell us a story

This isn’t a methods paper, though your manuscript may well include novel methods or techniques. This is not a place to try and sell us on your latest statistical tool or machine learning algorithm. Instead, we are interested in a story. We want to know how you’ve applied statistical engineering principles and concepts. We want to know about your struggles and what you did to overcome them (or how they overcame you). If your work does include a novel technical method, give us the basics but save the details for a more formal publication, which you can reference in your manuscript. 

Case Study Types

We are looking for content that illustrates statistical engineering principles in practice (or the consequences of their absences). These studies will very likely be used in training future statistical engineers, so the material should be presented in a manner that readers can follow and learn from the events being described. The following are some examples of types of case studies we'd be looking for:

Novel Application of an Old Idea

Tell us about a time you took a standard method and applied it in a unique way or in a setting outside of its usual scope. In what ways did you adapt it to your situation? How well did it address the problem?

If you developed an entirely novel method, we'd love to hear what motivated it. Just make sure not to overwhelm us with the details; save that for a methods journal. 

Example: Using a control chart in an ecological study. 

Success Story

Tell us about a time you were able to overcome a particular non-technical challenge related to a statistics/data science project you were involved in. In doing so, be sure to tell us what you think made your efforts successful. This can cover an entire project or just a particular situation.

Example: Convincing co-workers and/or leadership to switch to design of experiments techniques instead of ad-hoc or one-factor-at-a-time testing. 

Example: Completing a statistics/data science project that saved the company a significant amount of time and resources. 

Cautionary Tale

Tell us about a time you were involved in a project that ultimately did not meet its goals or failed to reach full conclusion. In doing so, be sure to tell us what you think went wrong and what lessons can be learned. NOTE: THIS IS NOT AN AVENUE TO VOICE GRIEVANCES OR PROMOTE SLANDER. CONTENT MUST REMAIN PROFESSIONAL AND UNBIASED.

Example: A project was halted due to the inability of team members to agree on a path forward. 

Example: A project was unable to achieve certain goals due to lack of buy-in from leadership.

Manuscript Formatting

Manuscripts should be no more than 2-3 pages in length. Formulas and mathematical expressions should be used sparingly as these are intended for a general audience.   

The structure of the manuscript need not follow the statistical engineering framework directly, though authors are welcome to use it as a guideline.  

Manuscripts will be reviewed to ensure the material is of good quality and suitable for our readership. We do not guarantee a rigorous review of technical content, though this may be done as part of the review process. This is not a substitute for formal review for a scientific publication.  

We do not plan to hold the copyright for your submission should you choose to submit a more complete version for publication elsewhere. However, we do ask that you confirm you have permission to publish your case study in our newsletter. Please note that by publishing your case study in our newsletter, the content will be made available to our members and potentially referenced in training materials. If some of this content has been published elsewhere, please provide a reference to that publication in your manuscript. 

By submitting this manuscript, you attest that you have permission to share this publication as part of the quarterly ISEA newsletter and have the permission of any co-authors as well. You acknowledge that this publication may be referenced in training material and/or other media developed for the purposes of promoting the discipline of statistical engineering. If you have questions about either of these agreements, DO NOT SUBMIT! Instead, please reach out to us at casestudies@isea-change.org with your inquiry.