Management studies are under scrutiny as to their status as a science (see “The Critique of Empirical Social Science: New Policies at Management and Organization Review”). Critical questions related to whether research results are replicable or simply misleading, have given rise to changes in editorial policies not only at the Management and Organization Review but also in journals such as Strategic Management Journal and American Economic Review. Avoiding sliding into manipulative surrealism akin to “Nothing is true and everything is possible” in Peter Pomerantsev’s incisive title (PublicAffairs, 2014), should provide a scholarly motivation.

Adding a consideration of relevance to this questioning of scientific legitimacy, Henrich Greve in “Show Me the Data! Improving Evidence Presentation for Publication”  points to the puzzle of homogeneous evidence presentation in a field that is broad and varied. He calls for the tailoring of the presentation of evidence to fit its theory and empirical context. He further proposes displaying data graphically:

“…showing relations from the raw data is easy to do and easy to interpret. It is an excellent approach for distinguishing the important phenomena from the less important, and for distinguishing the theory that explains phenomena well that from the theory that only captures a small part of the variation. Showing the data is an initial test of importance that speaks volumes of the relevance of the analyses that follow.”

Taking up Greve’s challenge in the Dialogue, Debate and Discussion, Sheen Levine reminds us that numbers are not substitutes for figures. He goes on to illustrate how wildly different graphical presentations are possible with the same data set. Citing the work by Matejka & Fitzmaurice (2017), which is an extension of Anscombe’s (1973) quartet, a particular data set can gain a visual form including a tyrannosaurus (!), a star, a circle, two horizontal lines, etc etc. Read the article to see for yourself!

Data visualization may go a long way to communicate the shape, or the significance, of the phenomenon that is studied but it may also help eliminate trivial data effects and point to unexplained but potentially significant unexplained variation. With more scrutiny by public funding agencies on the quality of management and organization science, and ever-present private sector questions about its “relevance”, it may be a good time to start communicating our studies and their underlying data in a way that is academically and practically compelling. Besides visuals speak English and Chinese quite fluently!

“Do you see?” ought to be a start.

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