With a PhD in statistical astrophysics, David Corliss is lead, Industrial Business Analytics, and manager, Data Science Center of Excellence, Stellantis. He serves on the steering committee for the Conference on Statistical Practice and is the founder of Peace-Work, a volunteer cooperative of statisticians and data scientists providing analytic support for charitable groups and applying statistical methods in issue-driven advocacy.
This month in Stats4Good, we will look at the post-pandemic “new normal” in Data for Good, where the experiences and technology of working remotely are changing Data for Good—for good!
One of the most important changes in the new world of analytics today is globalization. As we have become familiar with working remotely, traditional barriers of distance have fallen away. Today, we live in a much smaller and more inter-connected world. The same tools and skills developed to support working remotely will now drive a research environment in which international projects are the rule, not the exception.
Collaborators we have only read about can become part of our work in Data for Good. Students can participate in far-away research projects. Advocates can reach out directly to organizations working on the ground with the causes they support, wherever that ground happens to be.
The ASA’s Conference on Statistical Practice is just around the corner—February 1–3 in New Orleans, Louisiana. Focused on practitioners, it is full of learning and networking opportunities.
Also, abstract submission for JSM 2022 (all except for invited papers and panels) opened December 1. Now is the time to put together your abstract and submit it for the conference.
Another opportunity D4G practitioners will want to know about this month is the Golden Goose Award, which recognizes federal research that might seem obscure but actually leads to important benefits for society. It’s not for statistics research only, but it is definitely a place in which research for the greater good takes center stage. Nominations for the award are being accepted through December 17.
While this was all possible before, many required extended travel at prohibitive costs. Global is the new normal, creating a literal world of possibilities for starting new projects or joining existing ones, providing access to needed data and subject matter experts, and facilitating other opportunities for collaboration in Data for Good.
Another sea change in our D4G work is how events such as conferences, hackathons, and meetups have evolved. During the pandemic, in-person events needed to go virtual, and ASA conferences were no exception. In learning how things needed to work, we discovered how things could work. New ways of meeting and connecting developed, and new tools were created to support them. Perhaps most importantly, event attendees learned how to meet virtually and developed an understanding of both the advantages and shortcomings.
While the pandemic isn’t over yet, many of the changes to the science, technology, and sociology of scientific gatherings we saw during the pandemic will become the new normal as we emerge from it. Conferences, hackathons, and other gatherings are beginning to revert to in-person events, but more are becoming hybrid. Hybrid conferences aren’t completely new—we occasionally saw international speakers live-stream talks before the pandemic—but hybrid meetings will become more widespread and even expected by some.
One increasingly common format is to have all speakers record their presentations, stream them during a virtual or hybrid conference, and then take Q&A live. Two years ago, the conversation was, “What do you mean it’s going to be virtual?” Increasingly, the conversation will be, “What do you mean there’s no opportunity to present online?” Conference planners and managers will need to leverage the technology of the new normal to bring a wider array of speakers and global networking opportunities to attendees.
Another important development that can make a big impact on D4G projects is Agile methodology. It’s a set of project management tools focused on breaking projects into small, iterative steps called “sprints,” which are often just a week or two in length. Agile has been around in industry for a long time but was little used in research. Agile methods really took off during the pandemic due to their ability to effectively manage remote work.
As an example, I had my own Agile baptism by fire in 2010, before most people had ever heard of it. My dissertation adviser, Nancy Morrison, took an early retirement and moved 700 miles away while I still had more than a year remaining on my dissertation. I set up weekly meetings so we could review work from the week and set up tasks for the next week. More than 11 years later and long after I completed my dissertation, we continue meeting weekly, reviewing progress and planning tasks for the next weekly sprint. We meet in person when we can, usually around conferences, and continue to publish research together.
Classes on Agile methodology are certainly helpful, but it’s even better to find people with experience in Agile who will mentor you or even join your project team. Agile, in particular, is one area in which an outside subject matter expert, who isn’t otherwise involved in your work, can be helpful.
While much has changed, much has stayed the same. Statistics and data science still move at the speed of trust, where relationships must be cultivated before science can be brought to bear on problems. Developing new relationships in an interconnected global environment can be a challenge, but it also means there is a world of opportunities in Data for Good and we all have a place to use our statistics and data science skills for the greater good.
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