How do you handle data analysis requests that conflict with your values?

Every analytical quest begins with a question. Seek out the question that is at the root of the request. Once known, the question itself can illuminate ethical pathways to uncovering the desired insight. Share that journey with the parties making the request. Let them know what can go wrong if the principles of data stewardship are breached. And bring them along in the identification of alternative approaches that can answer their question. If that fails and they insist on the unethical approach, choose integrity.

Identifying the conflict or assessing the conflict solely based on personal values can be subjective and might not align with the broader context of the organization. Relying on company policies and guidelines is a more objective and consistent approach. Also, ethical principles and industry codes of conduct can offer guidance on how to navigate conflicting situations.

The role that shame plays in this conversation can't be overstated. For an individual contributor like a data analyst to say they don't want to or can't do something is a strike to the ego regardless of the context. That comes with shame, no matter the validity of the concern. It can be tempting to debate the reason ("This isn't that sensitive a data set"), but I'd suggest addressing the person first, then the problem ("Thanks for coming to me with this.")

The most important thing at this point is your ability to communicate. It's also good to note that this is not about you but about being ethical. I'll advise not to do anything that goes against your personal values or conviction and also do not do anything that goes against data laws or ethics. Communicate your stand honestly and respectfully as possible.

Remember that it's not just about you and your feelings, but the reputation of others, your department, your company, and possibly the analytics profession as a whole. If you're noticing something, then someone else is probably also noticing it. Speaking up will encourage others to do so.

This final step resonates with me, especially in my role as a program evaluation analyst. Ethical dilemmas often arise when assessing the efficacy and impact of programs. The stakes are high, as the findings can influence decisions on funding, scaling, or discontinuing programs. It’s crucial to remain unbiased and transparent, even when faced with external pressures. Evaluating our own actions, as mentioned in the last step, is a practice I embed in my own work. This not only ensures the integrity of the data but also builds trust with stakeholders. Continuous reflection helps us uphold the highest standards in our profession.

Always check your company’s policies on data ethics. If the policies are not suffice and are breach to values - raise it to your leaders and then if required further to CDO and/or DPO. Educate yourself and your team on data ethics and policies. Keep yourself up-to-date on these policies and encourage your team to implement the same.

Remember that you are an professional who is trusted with other people's data. What you do reflects on you, on your colleagues, your company, and on this vocation as a whole. Strive to be accurate and truthful in everything you say and do.

By offering ample and diverse fact-based perspectives, ethical issues can be minimized. Data itself doesn't inherently possess ethical issues, it is the people who do. Engage in objective discussions and consolidate these perspectives with the individuals making the request. Document their responses. Sometimes, you may gain insights from a new perspective or find yourself in disagreement. Articulate the issue when you require assistance.