Summary
If "what" your organization seeks is to exploit the potential of data science to power your business models, then the Data Science Value Engineering Framework provides the "how" your organization can do it.
The Value Engineering Framework starts with the identification of a strategic business initiative that not only determines the sources of value but provides the framework for a laser-focus on delivering business value.
A diverse set of stakeholders is beneficial because they provide different perspectives on the key decisions upon which the data science effort seeks to optimize in support of the targeted business initiative.
The heart of the Data Science Value Engineering Framework is the collaboration with the different stakeholders to identify, validate, value, and prioritize the key decisions (use cases) that they need to make in support of the targeted business initiative.
After gaining a thorough understanding of the top priority use cases, the analytics, data, architecture, and technology decisions now have a value-centric framework within which to make those decisions (by understanding what's important AND what's not important).
