Jim Rebar / Wednesday, February 6, 2019 / Categories: Items of Interest Lights, Camera, Action! SIOP Administrative Office Are You Turning Insights Into Action With Big Data? Today’s advanced technology gives us the ability to access mountains of data. Although this is helpful for organizations, it can be difficult to implement all that data for smart business decisions. Big data alone can’t create insight, knowledge, or change. That’s where industrial and organizational (I-O) psychologists come in. As experts in workplace psychology, I-O psychologists ask the right questions at the right time to harness large amounts of data that solve business challenges. To show the value that I-O psychologists bring to the big data table, SIOP’s Visibility Committee has released a video on the SIOP YouTube page. The video “Getting the Best Out of Big Data in Business,” emphasizes how I-O psychologists turn insights from big data into actions for enhancing organizational productivity and effectiveness. To do this, these five rules of thumb are used: Always start with a question, problem, or a decision – don’t start with the data or analyses. This will increase the likelihood that your big data initiative will lead to an action. Utilize the appropriate research methods, data sources, sampling techniques, measurement tools, and statistical analyses. This will increase the accuracy of your findings. Don’t mistake “data mining” for sound research – keep in mind that findings from digging expeditions may just be error (i.e., due to chance). Don’t forget to do something with your findings – your big data plan should drive action and business decisions. Tell a story with data and use data visualization to communicate findings in a clear and consumable manner. If a table or graph cannot be interpreted in 3 seconds or less, it’s too complicated. To learn more about these steps, watch the video here. The video was inspired by a white paper prepared by the Visibility Committee of the Society for Industrial and Organizational Psychology. “Big Data at Work: Lessons from the Field,” features insights on big data from SIOP members Alexis Fink, Rick Guzzo, and Sara Roberts. The interview-based white paper was written based on a SIOP Top Minds and Bottom Lines event held to engage members of the business community in the science of I-O psychology and to help promote the use of evidence-based management. To find more I-O psychology white papers, visit www.siop.org/whitepapers. One valuable aspect of big data that’s being recognized by both business leaders and the human resource (HR) community is talent analytics. Increasingly, organizations are investing in or upgrading their efforts in this area of big data. SIOP Fellow Evan Sinar explains, “The value of foundational talent analytics – often focused on predicting retention, engagement, and other traditional HR outcomes – is well-established. For these efforts to achieve long-lasting business-level payoffs, however, maximizing mere prediction is no longer enough: Explainability and ethics are critically important as well.” Sinar continues, “I-O psychologists bring rich backgrounds in behavioral science, fair and ethical approaches to employee decision making, change management, business communication, and the advanced statistics and research methods underlying artificial intelligence and machine learning. These skillsets make I-O psychologists uniquely suited as key business partners to HR and analytics functions seeking to unlock the full potential of big people data.” SIOP is currently planning a conference specially for talent analytics. The goal of this event is to help business leaders connect with experts in the field that will drive successful action for their organizations. It’s set to take place in 2020. For a more in depth look at big data at work, read the SHRM-SIOP white paper “Trends and Practices in Talent Analytics,” Previous Article Consortia, Workshops, and Seminars Next Article National Science Foundation Funding Opportunities Print 1147 Rate this article: No rating Comments are only visible to subscribers.