This year’s SIOP was definitely action-packed. I know that action-packed isn’t the first thing you think of when you imagine an academic conference, but it’s true! This week, I’m going to follow up on Patricia’s SIOP recap to provide what I learned from this year’s conference. I went to many sessions, networking events, and coffee meetings. There were three themes, outlined below, that describe what I learned.
Diversity is Taking a New Direction
First, as I’ve talked about before, my research centers on diversity and inclusion. This year, there were more diversity and inclusion sessions than I’ve ever seen at SIOP. Much of the conversation about diversity in past years has been about the negative experiences that minority individuals have in the workplace. For example, minorities have been documented to experience discrimination or lack of acceptance at work. While this work is extremely important, the research has already covered a lot of ground in this area. For example, we know that minority employees continue to experience discrimination. We also know this negatively affects the whole organization, by decreasing job satisfaction and commitment. But, we know less about how to solve this problem.
This year, at SIOP there was a lot of great conversation about how to be actively inclusive at work. I attended sessions discussing how to be a good ally. I also presented on how to show courage in the face of injustice and how to be resilient in the face of discrimination. While it is always useful to document experiences that detract from well-being, there are other questions we might answer. First, how can we promote well-being by being inclusive at work? In the diversity and inclusion arena, people haven’t been talking about this as much. But, it seems to be top of mind now. How can we create organizations that are inclusive? How can we do better than just avoiding discrimination?
Big Data and Machine Learning Are Powerful – But They Have Limits
There was also a lot of discussion at SIOP about the importance of data and analytics in organizations. But, it wasn’t just about keeping track of employee engagement and performance. The conversation was about how to use every piece of data employees produce to predict trends in the bottom line. For example, Google has launched a whole machine learning arm of their organization.
Machine learning is a computer science field that has recently been growing in popularity as our technology improves. If you’re not familiar with what machine learning is in the context of using employee data in organizations, here is a recap. First, it’s basically putting every piece of information about every employee, all of the data that they produce on a daily basis (even emails!), and all of the performance data the organization tracks into one giant dataset. Once you have all of this data together, you can ask really cool questions. For example, does the weather make sales people more effective? Or, do people who were hired on a Tuesday perform better that month? Or, are people with names that start with M better performers than people with names that start with L?
But, there were also conversations about the limits of this kind of data. Interestingly, when you take the human element out of things, data can be pretty dangerous. For example, maybe people with names that start with M are more effective than people with names that start with L. On the surface, if the machine tells you that, you might think that you should hire more people with names that start with M. But, what the machine might not tell you is whether or not people with names that start with M are just more likely to be from an older generation, so they have more experience. Or they might be more likely to have come from a region with better school systems.
Any combination of factors, that has nothing to do with the actual letter, could be driving the relationship. So, the take-home point is that, while big data is very powerful – you still need humans to interpret and understand the results.
Social Support Made My SIOP Special
Finally, I’ll share a personal observation. While the research definitely supports that having close friends and confidantes is important for your well-being, I personally experienced this at SIOP as well. It was so much fun to connect with friends from graduate school (like Patricia!). I was also able to meet with collaborators on research projects. I also met some new colleagues who I would like to form relationships with. We were able to celebrate a year of hard work, come up with new and interesting ideas for upcoming projects, and just hang out and relax. I realized, as the week continued, how nice it was to be able to set aside some time to refocus and reenergize myself with some of my favorite people.
If it’s been a while since you have taken time to really slow down and appreciate your coworkers, colleagues, or other folks in your field, make sure to do so soon! It can be really good to take time to have some fun and talk about new ideas that might get lost in the shuffle of the daily grind. It’s honestly really refreshing to get to know more about people and to dedicate some time to thinking about future projects and collaborations.
What are some of the biggest trends you see happening in your industry? Have you noticed anything changing in your field that you’re excited about? Let us know in the comments below. We would love to hear from you!
