In this video, Matthew Lee talks about how Protecht.ERM's historical models provide users with a better view of their enterprise risk management data.
Today I'm going to tell you how you can improve your insight into risk management using Protecht's historical models.
Historical models allow us to look at data in the past. Existing clients have the advantage that they don't need to start all over. They can use their existing ERM data with historical models.
Now, historical models allows us to do things like compare risks over time, compare the trends of risks over time, or even look back at a point in time for a value of a risk. The risk in motion trend dashboard allows us to link a number of different risk entities together, such as risk, control, actions, incidents, compliance, and shows the trend over time which helps decision making for a risk manager.
We can also apply predictive analytics to the historical models which helps us do things like predict trends of risks of over time, optimise decision making, and also prescribe decision making, so it actually tells a user how best to use a Protecht.ERM system.
For more information and to see the screenshots of the dashboard, please download our white paper from protecht.com.au.
Matthew joined Protecht in 2017, as the Manager of Business Intelligence and Analytics having extensive experience in senior roles within government and private organisations delivering large transformation projects, providing hands-on expertise and thought leadership in data and software. He graduated with a PhD in Applied Mathematics in 2001 from the University of Wollongong and more recently with an Executive MBA in 2008 from RMIT.