An analytic project, no matter how brilliant, is worth nothing if it does not inform decisions and drive actions. In this chapter, we address techniques you can use to get your project adopted in your organization. We cover testing of the solution to validate it delivers as expected, training of target users to promote understanding and adoption, and phased rollout to build momentum and a solid user base.
The type and degree of testing needed for your solution is dependent on the scale and level of automation. Will the solution be rolled out enterprise-wide or will it be deployed to a small user group? Will one or two developers be responsible for Data Development, the Analytical Structure, and Guided Analytics, or will a team of developers be involved?
Large and complex projects designed for enterprise deployment with a high degree of automation require a more formal and structured testing, training, and rollout process. Smaller, focused projects impacting a small group of users can adopt a more agile process. Let's review both scenarios.
Decision Architecture projects on an enterprise scale involve several departments working together in cross-functional teams with a number of roles. A team working on an enterprise-wide Decision Architecture project typically requires a wide scope of capabilities, comprising facilitation, documentation, data architecture design, data analysis, data science and decision theory, ...