Recent Webinars

Bringing Clarity to Analytics Projects with Decision Modeling: A Case Study

To succeed, an analytics or data science team must effectively engage with business experts who are often inexperienced with advanced analytics, machine learning and data science. They need a framework for connecting business problems to possible analytics solutions. Decision modeling brings clarity to analytics projects, linking analytics solutions to business problems to deliver value.

IIA Expert James Taylor shares four key lessons learned by the central analytics team at a global leader in information technology. These lessons underscore that decision modeling builds a shared understanding with their business clients, revives projects that have lost their purpose, brings clarity to problems long thought difficult and delivers value quickly. The webinar will also introduce the basics of decision modeling and provide practical recommendations for adoption. A Leading Practice Brief based on this case study will be available for all registrants.

Ensuring analytics projects have clarity of purpose is critical to delivering business value. Learn how decision modeling helps a leading organization bring focus to its data science and analytic investments.

Watch the webcast here.


Framing Analytic Requirements with Decision Modeling

One of the most important steps in a predictive analytic effort is correctly framing the problem a way that creates a shared understanding of the business problem across business, IT, and analytics teams. A decision requirements model makes it clear how to best leverage analytics.

How to Succeed with Advanced Analytics at Scale

Leading organizations today are looking to scale their advanced analytics capabilities, especially data mining and predictive analytics, to improve business performance, reduce fraud and improve customer responsiveness. However traditional analytic project approaches are hard to scale and difficult to implement in the real-time environment required in modern enterprise architectures. Learn best practices from leading organizations […]

Predictive Analytics Deployment to Mainframe or Hadoop

Learn how to achieve a standards-based, efficient approach to analytics deployment from open source like R and commercial analytics products to a wide range of platforms including mainframes like IBM zSystems and new data infrastructure like Hadoop. The big challenge for analytics-driven organizations today is closing the gap between deriving an analytic result and getting […]

How to Innovate Risk Management and Customer Centricity

Operational decision making is not optimized in the majority of organizations because it is buried in business processes and information systems. This matters because business processes are ultimately what deliver value to the business. More and more of this value creation is associated with decisions and approvals. This trend is accelerating as more processes are […]

Smarter Mobile Apps with Process and Decision Management

Learn the decision and process management capabilities that drive excellence in mobile applications with leading experts Sandy Kemsley and James Taylor.  Mobile devices have gained enough traction with consumers and employees to require mobile applications as a part of an enterprise strategy. However, these mobile apps must be more than mere information presenters. In this […]

DecisionsFirst Modeler Enterprise Edition Integration with IBM ODM

DecisionsFirst Modeler decision modeling software enables organizations to accurately specify their business using decision requirements models; structure and manage the supporting business rules; and streamline business process design. The newly available integration with IBM Operational Decision Manager (ODM) delivers traceability from business objectives through decision requirements to the business rules running in production. The Enterprise […]

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