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How'd we prepare? Building the 2023 OSS in partnership with our community


Over the last number of years, GEiHP received regular inquiries about the original Open Salary Spreadsheet, often more than 100 a month. Folks consistently asked for updates, recognizing that the landscape of the job search, salary benchmarking and analysis, and the experience of salary negotiation had changed substantially, even if base salaries had not significantly changed.


Due to this continued interest, we undertook preliminary conversations about the possibility of adding to or expanding the OSS so that it might serve more users. However, given what we learned in our initial 2019 experiment, we wanted to approach this deliberately and with the necessary care and intention that would result in a better quality product, more thoughtfully aligned with our organizational values.


In the summer of 2022, six open focus groups and ten user interviews, engaging more than 50 current and past spreadsheet users, were convened. Participants were queried about what they felt was missing from the original data collection, what might be added, what they hoped to learn in the next iteration of the spreadsheet, and what kind of data they needed. We included more than 20 additional interviews and small group conversations to build on what we learned and help to shape our design. This data was used to shape and map a new survey, which provides the appropriate inputs for our new Open Salary Spreadsheet.


Listening to our users, both our contributors and those using the data, helped us to determine what to include and what felt less urgent. For example, we recognized that in our original 2019 experiment, we did not get the specific location and geographic information that folks needed and wanted, in part because we allowed participants to self-describe their geographic location entirely. Now we strive to refine this properly, and we know that we’re closer to “correct,” but still are certain we leave some folks out. We have defined geography both by where each contributor is located as well as where their workplaces and employers are located, and also include relevant geographic data sorted by region and city/community size. This example helps us to clarify and draw more effective boundaries without compromising our contributors’ anonymity. Our current data collection strives to balance the shifting state of the Jewish workplace and our larger communal ecosystem, as well as changing understandings about the world of work and learning from other similar data collections.



Gathering and inputting new data was an important component of our work, and we hope to eliminate some of the glitches in our original data collection. We have selected AirTable, because it enables us improved flexibility for data collection, an opportunity to update content immediately, a maximum level of data protection and anonymity, and a user-friendly design that enables a better user experience. Sure, we could use a true “open spreadsheet,” but this would be harder to design, less user-friendly, and more easily open to breaches or accidental edits by others. To add one’s data, contributors to our 2023 and beyond data collection will complete an anonymous AirTable survey linked to a spreadsheet that will immediately update with new data.


Sure, no one tool is perfect. No one way of doing this is easiest or will provide the perfect level of anonymity. And we’ve made plenty of mistakes along the way.


Until the last moment, for example, we continued to edit our language for Jewish, ethnic, gender and racial identities, as we are continuing to learn and wanted to make sure that we included as many as possible in our proverbial tent.


Another important adjustment and learning for us was the shift to “self-describe” over “prefer to self-describe,” acknowledging that when folks self-describe, they are not “preferring,” or choosing their description. They just are that person, and they want to identify as such without having to prefer it. Note that all language in this survey includes “self-describe,” to make room for anyone and everyone to include their identification, but not to have to “prefer” it. This is with regard to pronouns (20), for example, but also for the description of your department (2) or organization (29), too.



If you have specific questions about how our survey was constructed or would like to help us reflect on the questions we’ve asked for next time or for future edits, please be in touch. This is an important learning opportunity for us and we relish the opportunity to be in conversation with others as we continue to develop this tool and learn from you.





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