Using Journal Timing Charts to Improve Manuscript Flow: Part 3
The time to final decision chart includes all the stages from initial submission to final decision and shows the total time taken for each stage. The data gives authors an idea of how long it will take to reach a final decision, and it provides the journal with another indicator to track when looking for whether improvements are needed to shorten the time a manuscript spends in the peer review process.
Looking at the timing charts for the editorial office can also help you identify where processes might be streamlined to improve the throughput time of submissions.
Due to the variability in all editorial timings, it is a good idea to include not only the mean (average) or median but also a measure of the variability in the data, such as standard deviation or interquartile range.
Using Journal Timing Charts to Improve Manuscript Flow: Time to Final Decision, Editorial Office Timing, and Adding Statistics
March 2, 2022
By: Sherrie Hill and Kristen Overstreet
In the last post in this series on timing charts, we will look at the time from submission to final decision and the time a manuscript spends specifically in the hands of the editorial office.
Time to Final Decision
The time to final decision chart includes all the stages from initial submission to final decision and shows the total time taken for each of those stages. The data gives authors an idea of how long it will take to reach a final decision, and it gives the journal another indicator to track when looking for whether improvements are needed to shorten the time a manuscript spends in the peer review process.
The time to final decision chart (below on the right) shows a very similar trend to our previous time to initial decision (below on the left), though there is a slight increase in the 2020 time to final decision.
Just as we broke down the timing charts for initial decisions, we should break down the time to final decision. Since there are elements that the journal has less control over, such as how long the reviewers take to submit their comments and how long the authors take to make the revisions, we will look at the time the manuscript is with the editors and/or editorial office. For example,
Time to assign the Editor-in-Chief and/or Associate/Section Editor. However, if your workflow is set up to automatically assign the editors as part of the revised manuscript check-in process, this chart is not needed.
Time to assign reviewers. However, if the previous reviewers are automatically invited to review, this chart is not needed.
Time from last review submitted to time the editor makes the final decision.
Time from submission to final decision by assigned editor.
Since some revisions do not go back to the peer reviewers, it is a good idea to break out those manuscripts and report them separately from those that do receive multiple rounds of full peer review. In our chart below, we can see that revised submissions that do not go back to peer reviewers but instead receive an immediate decision from the editor take less than a week to receive their final decisions, while revisions sent back to the reviewers take on average more than twenty days to receive their final decisions.
The time to final decision can also be broken down by editor. Manuscripts handled by editors with longer times to final decision should be investigated to determine if the time delays are within the editor’s control or are a result of their areas of specialty, such as manuscripts that require methodology reviews or cover complex topics that require more time to review. Small reviewer pools for specialty topics can also cause delays. However, close investigation may reveal that the editor is processing manuscripts differently than their peers and improvements can be made. The time to final decision by editor chart will give you a starting point for your investigations.
Editorial Office Timing Charts
Most submission systems have not provided journals with an easy method for tracking the time a manuscript spends in the hands of the editorial office. This is unfortunate because these are important stages in the peer review process that need to be tracked to ensure time is not wasted, increasing the total time a manuscript spends in peer review. These are the stages in the peer review process that we have total control over; as editorial professionals, we need to ensure that we are processing the manuscripts as efficiently as possible in these stages.
Quality Check for Initial Submissions
The first stage is the quality check for the initial submissions. Most journal offices have some type of minimum requirements for incoming submissions. If the submission fails this initial quality check, it is typically sent back to the author for corrections before it can be assigned to an editor and continue in the peer review process.
When creating a chart about time from initial submission to editor assignment, we must determine which initial submission date will be used. There is a static and a dynamic submission date. The static submission date is the date that the author first sends their manuscript to the editorial office, and it is never updated by the submission system. The dynamic submission date is the date the manuscript is resubmitted if the manuscript has been sent back for corrections and resubmitted by the author.
Most journals do not have a deadline for submissions that are sent back to an author. Therefore, the author might make the corrections and immediately send it back or sit on it for days or weeks before resubmitting it to the journal. When the submission is sent back to the journal office, the static submission date is not updated but the dynamic submission date is set to the date of re-submission.
For your time from initial submission to editor assignment chart, to get a more appropriate editorial office timing value, use the dynamic submission date as your start date.
Quality Check for Revised Submissions
Another stage where the manuscript is in the editorial offices hands is when the revised submission is submitted and checked in. For some journals, this is when the more extensive check is done on a manuscript. (We don’t want to waste an author’s time with journal-specific corrections when their initial submission may be rejected by an editor for being out of scope, for example, so our initial submission check is lighter.) Therefore, it is useful to look at the data by manuscript revision number. There might be differences in the time taken to check in a revised manuscript if different processes are performed at different stages.
In our example below, this journal checks for copyright issues at the R1 check-in, so that check-in point takes more time than subsequent check-ins.
Since there are fewer submissions that reach the higher revision levels, an outlier manuscript can more significantly impact the average timing value; therefore, the mean (average) data points for the higher revision numbers are less likely to be good predictors of what we would expect to see at those stages. If your data has outliers, you may want to report the median values rather than the mean (average) values, since outliers effect the mean more significantly than the median.
When there are multiple staff members in the editorial office, look at the data by staff member. In our example below, editorial staff member Bells’ performance should be investigated. They may not be following the same procedures as the rest of the team or are taking more time to review items in greater detail than is expected or desired. Further training may be warranted.
Sending Accepted Manuscripts to Production
Another stage for which the editorial office controls the timing is sending accepted manuscripts to production. After an editor accepts a manuscript, the editorial office staff often perform final checks on manuscripts prior to exporting them to the production team. When journals look at the time spent in this part of the process, they often see there is a bottleneck here and room for improvement. One method to improve efficiency is to address some items earlier in the process, for example at the revision stage, so the manuscript doesn’t have to go back to the authors after acceptance. In our example below, the editorial office staff made a more concerted effort to get all author copyright documentation in place before the second revision (R2) stage. This helped them dramatically reduce the amount of time in this final step after acceptance.
When presenting your data to your audience, it is important to help orient them to what they are looking at. For example, since the values for time to initial decision and final decision can vary widely, it is helpful to report the variation in the data along with the mean (average) or median (average) values so that the reader has a better understanding of what you are showing them.
You may want to consider including a companion table that provides additional information about the variation in the data along with a chart showing the mean (average) or median information. Two of the most common stats for variation are standard deviation and interquartile range (IQR). When reporting mean (average) values, you should provide the standard deviation value in a table, since the standard deviation is based off mean (average) values. If you report the median values, then you should use the interquartile range to report the variation in your data, since the IQR is calculated using median values.
Some types of charts, such as box plots, can show both the reported value as well as the variation. In future posts, we will look more closely at presenting statistical variation information and interpreting box plots.
Tips for Best Practices
Submissions that receive immediate accept or immediate reject decisions (decisions made by the editors only, not sent to peer reviewers) should not be included in your Time to Initial Decision and Time to Final Decision charts because these decisions are usually reached much more quickly than decisions on manuscripts that go through full peer review and, thus, they skew your data.
Timing charts are good indicators of how your journal’s peer review process is performing, and the data can identify stages that need improvement. Identifying issues with your peer review workflow will allow you to make data-driven decisions to improve your journal’s policies and processes.