I am giving a webinar on “Framing Analytic Requirements with Decision Modeling” April 2, 9am Pacific/Noon Eastern:
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. Established analytic approaches such as CRISP-DM stress the importance of understanding the project objectives and requirements from a business perspective, but most organizations do not apply a formal approach to capture this understanding in a repeatable, understandable format. Decision modeling closed this gap.
In this webinar you will learn how to use Decision Requirements Modeling for analytic project requirements in order to:
- Compare multiple projects for prioritization, including allowing new analytic development to be compared with updating or refining existing analytics.
- Act on a specific plan to guide analytic development that is accessible to business, IT and analytic teams alike.
- Reuse knowledge from project to project by creating an increasingly detailed and accurate view of decision-making and the role of analytics.
- Value information sources and analytics in terms of business impact.
With the growing focus on using analytics to improve decision-making, it makes sense to drive analytic requirements in a decision-led way. A decision requirements model makes it clear how analytics can/should influence decision-making, where that decision-making fits in terms of business processes and systems, and which organizations will have to play a role in approving or using any analytic being developed. Constraints on decision-making like policies and regulations as well as the information available are likewise part of the model.