The COVID-19 pandemic may have forced your institution to delay (or freeze) hiring for the near future for open administrative, staff, or even faculty positions. In these times, you are likely, by necessity, to be carefully considering the academic personnel needs at your college or university.

And academic leaders everywhere are assessing how best to handle remote hiring (or other selective academic personnel decisions)—in a time when meeting in person, or even using campus hardware, is not possible.

Luckily, since long before COVID-19 happened, Interfolio has been helping colleges and universities to achieve a digital transformation around their academic hiring and data gathering.

Here, we discuss a few essential guidelines your office should follow when considering a move to online academic recruitment, fellowships, and other competitive processes in higher education. 

The guidelines are:

  1. Ease for committees/reviewers is essential
  2. It’s best to compile data reporting needs and priorities in advance 
  3. Letters of recommendation should be automated

Guideline 1: Ease of reviewing materials is essential

The practical experience of evaluating many applications in a row is an absolutely central aspect of academic recruitment to bear in mind.

Yet, oddly, this is a basic need that can slip out of sight during your digital transformation, amidst conversations with IT, HR, provost and dean’s offices, and the institutional diversity office. Don’t let it!

The page-by-page application review experience will make or break your transition to online faculty hiring. (Just ask Millikin University or Notre Dame.)

Regardless of whether a decision is made by committee or by a simpler administrative review, academic applications are much larger and complicated than the applications for most staff positions. They have many pages, many different kinds of documents, and in many fields, images and multimedia.

As you undertake a digital transformation around selective processes, you must keep sight of the people evaluating the applications. Ask yourself: “How will they reach good decisions under this online hiring model?”

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Guideline 2: It’s best to compile data reporting needs and priorities in advance

In parallel to the goal of actually handling the search and decision process around academic hiring, you will want visibility into a variety of data points after the fact.

It is critical to compile your list of desired data points, beginning early on in your digital transformation effort. Have at least a brief check-in with your institutional diversity, HR, and institutional research offices to make sure you have your bases covered.

Here are a few sample data points around academic hiring that you should consider:

  • Self-reported diversity/demographic information (following federal EEO Commission guidelines)
  • Quantitative ranking of applicants by reviewers, based on standard criteria
  • Other applicant profile information:
    • Highest degree earned; date earned; granting institution
    • Country and state of residence
  • Dates:
    • Position open and close
    • Submission per application
  • Withdrawn applications
  • Other data on positions offered
    • Rank
    • Title
    • Tenure-track or not
    • Full-time or part-time
  • Disposition code (i.e. “Why was this applicant or group of applicants removed from consideration?”)

Keeping this checklist at hand during your digital transformation will help you make sure that, in your new online academic hiring model, you’re able to capture and view all this information later.

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Guideline 3: Letters of recommendation should be automated

Handling confidential letters of recommendation, in an efficient and responsible way, is one of the biggest burdens on administrative time around academic hiring.

In 2020, you do not have to settle for a manual process around recommendation letters in higher education. You should see this as a given in your digital transformation.

This is because letters are a specific bottleneck that make a big difference in the overall flow of recruitment and competitive selection at your college or university. Of course, it is up to the committee, department or institution (not Interfolio) to decide where recommendation letters should fall in the process.

You should expect your automated solution will accommodate all of the following:

  • Either the applicant or the committee should be able to request a letter online.
  • Intended confidentiality status should be clearly marked prior to letter submission.
    • Once submitted, the letter file should be kept confidential from the applicant before, during, and after submission of the application.
    • Also, it should be possible for the applicant to supply a letter held confidentially via their dossier service.
  • The letter should go directly into the proper application (still confidentially). However, the applicant should be able to submit their application even before the letter is submitted.
  • The applicant must be reasonably prevented from submitting a letter for themselves (and getting away with it).
  • The applicant, the writer, and the institution should receive automatic confirmation when the letter is submitted.

The point is, you should make automating recommendation letters a priority. It will reap big benefits for the efficiency of your process.

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These are starting points. For a more thorough free guide, take a look at our System Considerations for Faculty Hiring.

Interfolio is committed to helping the global faculty affairs community and academic leadership continue to play their pivotal role throughout these changing circumstances. 

If you have questions about moving higher education operations online or business continuity in these trying times, we welcome inquiries or conversation at team@interfolio.com