By: Greta Roberts, Conference Chair, Predictive Analytics World for Workforce 2017
In anticipation of his upcoming Predictive Analytics World for Workforce conference presentation, Enhancing the Quality of Predictive Modeling on College Enrollment, we interviewed Feyzi Bagirov, Chief Business Officer at 592 LLC and Analytics Instructor at 
Harrisburg University of Science and Technology. View the Q-and-A below to see how Feyzi Bagirov has incorporated predictive analytics into the workforce of 592 LLC and Harrisburg University of Science and Technology. Also, glimpse what’s in store for the new PAW Workforce conference, May 14-18, 2017.
Q: How is a specific line of business / business unit using your predictive decisions? How is your product deployed into operations?
A: One of the ways enrollment departments in higher education are using data science is identifying students who are most likely to enroll, less likely to enroll and unlikely to enroll. This helps prioritizing marketing efforts.
Q: If HR were 100% ready and the data were available, what would your boldest data science creations do?
A: Identifying and hiring the right student candidates.
Q: When do you think businesses will be ready for "black box" workforce predictive methods, such as Random Forests or Neural Networks?
A: When businesses will answer these three questions to themselves:
1. What questions need to be answered to achieve our objectives?
2. What data do we need to answer them?
3. How do we get that data?
Q: Do you have suggestions for data scientists trying to explain the complexity of their work, to those solving workforce challenges?
A: Ask them to talk about their business and look for the pain points. Once identified, give a 10,000 feet overview of how the data insight can help in making a decision.
Q: What is one specific way in which predictive analytics actively is driving decisions?
A: A monetary outcome (either making or saving) or a public/private benefit of a decision.
Q: How does business culture, including HR, need to evolve to accept the full promise of predictive workforce?
A: Managers need to realize that:
- Data science insights will SUPPORT, but will not MAKE the decisions for them
- Utilizing organizational data is more than running descriptive dashboards. Getting into a predictive component quickly is important.
- Very few Data Scientists know everything about Data Science.
- Maintaining data quality is important if you want quality insights. Sacrificing data quality for the sake of moving forward needs to be an exception.
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Don't miss Feyzi’s conference presentation, Enhancing the Quality of Predictive Modeling on College Enrollment, at PAW Workforce, on Wednesday, May 17, 2017, from 10:15 to 10:35 am. Click here to register for attendance.
By: Greta Roberts, CEO, Talent Analytics, Corp. @gretaroberts and Conference Chair of Predictive Analytics World for Workforce