“Best practice” is an appealing concept. It suggests a solution to the question of how something should be done, based on results of research and experience (Bardach and Patashnik, 2016, Part IV). This appeal means it is also a commonly heard term. But it is not without criticism.

There is ambiguity in the term. To an economist, best practice would result in the economic optimum of a production system. To the technologist, it might lead to the technical maximum. At the same time as there is ambiguity, there is rigidity. Patton (2015, pp190-193) note that a “Best practice” is usually a prescription for how to achieve a given outcome. It lacks context. Even more strongly, Patton (2015, pp190-193) states “Designating something a “best practice” is a marketing ploy…”

The observations against best practice from Bardach and Patashnik (2016) and Patton (2015) are based in the implementation of the idea in policy. Policy usually focuses on the human systems and it could be argued that the complexity and uncertainty is much greater there than that of a sugar beet storage system; one clamp does more or less looks like another.

An expansion of the term may then be “best practice*”, where the asterisk designates “in the given context”, or “when there is insignificant variation in the context”. The economist, however, would recognise that the technology set of each system is likely different. They would also recognise that there are different preferences around, for example, risk and different opportunity costs for labour. At both the individual firm and at a higher level of aggregation, this all means that there are many possible outcomes that could result and that all reach very similar total revenue outcomes – the concept known (somewhat unfortunately in the context of 2022s Internet culture) as “Flat Earth Economics” (Pannell, 2006).

The final, indisputable*, argument against the concept of “Best practice” is that it cannot be “…a scientific conclusion” (Patton, 2015). Science does not work in positive absolutes. Bardach and Patashnik (2016, Part IV) similarly warns “Rarely will you have any confidence that some helpful-looking practice is actually the best among all those that address the same problem or opportunity. The extensive and careful research needed to document a claim of best will almost never have been done.”

* the irony of being so absolute in this sentence is not lost on the author.

The “extensive and careful research” needed to claim “best” has not been done in this instance. Indeed, it cannot be done. This work looks to future scenarios around which there is uncertainty. Then what are the practices this work looks at if not “best”? Bardach and Patashnik (2016) and Patton (2015) both offer alternative terms for what it is the author of a best practice report is likely presenting: Bardach and Patashnik (2016) gives “good” and “smart”, Patton (2015) “better”, “effective”, “promising”.

There is a high degree of confidence that the practices discussed as a result of the research of this doctoral project would fit under any of these banners in different ways. There is confidence that there is causality between the practices and better results, and that there are cost and risk reducing practices. In the end, however, the only term that feels like it would hold up to full scrutiny is simply “practices”. But that is just a little boring…

Patton (2015, pp190-193) distinguishes between best practice and guiding principles. Guiding principles hold when they have been tested in many contexts and situations and still prove effective or correct. With all this in mind, it is the opinion of this author that what we should be pushing is: principles + a full toolbox + context. We the scientists are given permission to work in principles (Patton (2015). We the farmers need tools to make decisions. I the lowly PhD student is trying to summarise the former, and add to the latter.

All that said, I don’t really have that much of an issue with Best Practice. It just isn’t what I’m doing in my PhD.


Bardach, E. and Patashnik, E. M. (2016). A Practical Guide for Policy Analysis: The
eightfold path to more effective problem solving
. CQ Press, SAGE, Los Angeles, California,
5th edition.

Pannell, D. J. (2006). Flat earth economics: The far-reaching consequences of flat payoff
functions in economic decision making
. Review of Agricultural Economics, 28(4):553-

Patton, M. Q. (2015). Qualitative Research and Evaluation Methods: integrating theory
and practice
. SAGE Publications, Inc., Thousand Oaks, California, fourth edition.

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.