An essential step in the Data Equity Framework is creating a Motivation Touchtone. (Check out part 1, part 2 and part 3 of how to make a Motivation Touchstone.)
One of the most important parts of that process is outlining, in as much detail as you can, the key restrictions and rewards that form the parameters of your data project. Getting everyone on the same page about what you can and can’t do, and what you are aiming for is essential for internal success. Being able to communicate and defend your restrictions and rewards is essential to explaining why you went about your project in the way that you did.
In order to jump-start this process, we’ve compiled a short questionnaire of the most important questions that we ask when shepherding our clients and partners through the Motivation Touchstone process. It’s not too many questions and it’s very versatile in terms of time. It’s invaluable to even spend 20 minutes answering the questions by yourself at the start of a project, while you can (and we have) spend months exploring and answering the very same set of questions across various stakeholders in a project.
3 key things to keep in mind that will make this tool useful to you:
– Explore various perspectives. The answer to these questions will vary between researchers, administrators, funders, bosses, data collectors, designers, and especially the various groups of people that you are trying to center in your project and those who make up the data. We encourage you to use participatory techniques, representatives with learned and lived expertise or at the very least your most imaginative empathy to explore these questions beyond your own answers. Include as many perspectives as you can and recognize that whichever perspective you ultimately adopt is the locus of power in that area of your project.
– Be as detailed as possible. The more exactly you can list the rewards and restrictions that your project will face, the better prepared to accommodate them you will be. Not to mention you’ll be in a better position to explain why your project went how it went.
– Don’t make assumptions. Ask yourself carefully. Ask others explicitly. There may be answers to these questions that would surprise you.
All of these questions would be important to ask in any data science process to make sure it works, but the ones highlighted in red are also key data equity questions, usually relating to the “who” side of the power dynamics in your project. It’s okay if the answers to those questions make you uncomfortable. That’s usually the first sign you are making an equity improvement!
Restrictions:
Time:
How much time do you have for this project?
Who set the timeline?
What would the optimal amount of time be? (Explore various perspectives)
What is the difference between the timeline you have and the timeline you think your stakeholders or data providers (the people represented by your data) would want?
How much flexibility is there in how much time you have?
What do you think the major impacts of this restriction will be?
Money:
How much money do you have for this project?
Who determines the amount of money?
What would the optimal amount of money be? (Explore various perspectives)
What is the difference between the money you have and the money you think your stakeholders or data providers (the people represented by your data) would want you to have?
How much flexibility is there in how much money you have?
What do you think the major impacts of this restriction will be?
Capacity and Expertise
What expertise will be required to explore this question? (technical, methodological, social, administrative, etc.)
What relevant expertise do you not have? (Explore various perspectives)
How much flexibility is there in expanding (either through additional team members or capacity building/learning) the expertise available when answering this question?
What do you think the major impacts of this restriction will be?
Resources:
What resources other than money or expertise will you bring to bear when answering this question?
What resources would be useful that you won’t have?
How much flexibility is there in getting more resources?
What do you think the major impacts of this restriction will be?
Laws, Ethics, and Privacy:
What are the relevant laws, ethical guidelines, and privacy restrictions to this project?
How would adding or subtracting laws, ethical guidelines, or privacy restrictions improve the project? (Explore various perspectives)
What do you think the major impacts of these restrictions will be?
Commitments:
What promises have been made in relation to how this project will unfold? (include to whom)
Who made the promises?
Who is responsible for keeping the promises?
Are there any promises that shouldn’t have been made? (explore various perspectives)
Are there any promises that should have been made? (explore various perspectives)
What do you think the major impacts of these commitments will be?
Rewards:
Profit:
Who will make money from this project?
How much?
How much flexibility is there in this area? (is this a nice-to-have or a must-have for the project to succeed)
Will the amount of funding, income, or services received be affected by the outcome of this project? (explore various perspectives)
Information:
What kind of information are you hoping to get from this project?
Who will see this information?
Who will own this information?
What is the minimum quantity/quality/certainty/meaning required to consider this project a success?
Who decides that?
Prestige/politics:
What results of your project would be “acceptable” or “good”? (explore various perspectives)
Is how the results are received part of what defines success for this project?
Who will be “receiving” results in a way that matters to the success of this project?
Who decides what “good” results would look like?
Additional Rewards:
Are there any secondary things that you are hoping to get out of this project? (Explore various perspectives). Examples: improve service delivery (stakeholders), earn a Ph.D. (personal), build a resource library (team), demonstrate organizational competency (organization), etc.
Which of these secondary rewards are nice-to-haves and which are must-haves?
Who decides which are nice to haves vs must haves?
If you are keen to give these starter questions a go we’ve got this same set available below as a downloadable PDF. If you can think of any other questions that you find useful when setting up the Reward/Restrictions parameters of your projects please let us know in the comment!