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- W2796463237 abstract "We now have all the tools in place to optimize one or more data-to-learning-to-action processes and, more specifically, to maximize the value of learning that is associated with data-to-learning-to-action processes. So, in this chapter, we’ll work through some common patterns of learning constraints and potential solutions that are applicable to a wide variety of organizations and functional areas. The solutions invariably rely on people-, process-, or technology-based capabilities and, most typically, combinations of the three. We’ll work through these examples by traversing backward along the chain from the targeted decision, which is the sequence that is most appropriate to be applied in any real-world setting. And, of course, that targeted decision should be one that has been determined to have significant leverage on a value driver for the organization. We will spend time on each element of the data-to-learning-to-action chain and discuss some of the common constraints that are associated with each element and some typical potential solutions to these constraints. These examples will hopefully resonate with some of the data-to-learning-to-action processes in your own organization and help jumpstart your analysis." @default.
- W2796463237 created "2018-04-13" @default.
- W2796463237 creator A5024590179 @default.
- W2796463237 date "2018-01-01" @default.
- W2796463237 modified "2023-09-25" @default.
- W2796463237 title "Patterns of Learning Constraints and Solutions" @default.
- W2796463237 doi "https://doi.org/10.1007/978-1-4842-3531-7_9" @default.
- W2796463237 hasPublicationYear "2018" @default.
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