By: Eric Siegel, Founder, Predictive Analytics World
In anticipation of his upcoming conference presentation,
The Impact of Predictive Analytics 
on Maritime Safety and Efficiency, at Predictive Analytics World San Francisco, March 29-April 2, 2015, we asked Bryan Guenther, Qi Program Manager at RightShip, a few questions about his work in predictive analytics.
Q: In your work with predictive analytics, what behavior do your models predict?
A: In essence our models predict the likelihood of an incident at sea. We are also developing other models to predict specific kinds of shipping accidents, e.g., accidents that cause pollution, ships running aground, etc.; as well as models that drive efficiency – e.g., in loading/unloading at port.
Q: How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?
A: As we work in the services industry, our customers – who use our models for their vessel selection – are the ones that ultimately get the value from the models (which they then pay us for).
Predictive analytics provides us with the ability to identify vessels that may have an incident, and therefore remove them from our customers’ supply chain – so indirectly we are reducing the likelihood of a vessel having an accident. As such it’s not just about money: the value our analytics provides is about limiting risk, saving lives, and reducing environmental damage.
Q: Can you describe a successful result, such as the predictive lift of your model or the ROI of an analytics initiative?
A: Each time our customer avoids an unsafe vessel it’s a ROI, and a success, so the prediction actually does this. In 2013 alone we removed over 950 vessels from customer supply chains – so we see that as potentially 950+ incidents that were avoided.
Q: What surprising discovery have you unearthed in your data?
A: Analytics showed us the complexity of the relationships between various factors. If you take age as an example, we previously had assumed this to be a fairly linear factor that operated independently; however predictive analytics showed us this is not the case. We discovered that the way age affects a vessel is dependent on a lot of other factors such as tonnage, past casualty history, owner, manager, parent, flag, class, crew, etc. There are many complex relationships and interactions.
Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.
A: I’ll provide some practical examples of how predictive modelling has made a real difference. Our next predictive model may save someone’s life, keep oil out of the water & birds in the air! I must say that although our prescriptive model has done a fantastic job so far in reducing casualties; predictive modelling will take us to the next level. This transition is being driven through technology – we can’t move on and improve with old technology.
Don't miss Bryan Guenther’s conference presentation, The Impact of Predictive Analytics on Maritime Safety and Efficiency, at Predictive Analytics World San Francisco, on Tuesday, March 31, 2014 from 11:45 am-12:05 pm. Click here to register for attendance.
By: Eric Siegel, Founder, Predictive Analytics World
Eric Siegel, Ph.D., founder of Predictive Analytics World and Text Analytics World, and Executive Editor of the Predictive Analytics Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the bestselling, award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor, and a renowned speaker, educator, and leader in the field.