# Sequencing development The Palantir ["levels" framework ↗](https://blog.palantir.com/levels-9be772098942) provides a map for enterprise-wide digital transformation. For a use case, the framework embodies one reasonable approach for the implementation sequence. | | | | -- | -- | | sequencing-development | The article linked above shares a number of considerations. Most relevant to the use case implementation sequence is the importance of first establishing a *data asset* **(1)** and *guided decision-making* **(2)** - in this context, the data pipeline, ontology structure, and initial interfaces. You can then proceed into decision space expansion and enrichment, incorporating data science techniques for model-driven operational workflows. | Specifically, this means putting development effort and focus into the use case foundations: * a robust and efficient pipeline * a balanced, reflective, and practical object model * a flexible approach to enriching data with labels and metrics based on data science, rules, and manual approaches * re-usable interface components for object views and decision capture. At the same time, you can explore and understand the integration story for model-driven feedback loops, digital twins, and chained scenario planning while recognizing that lower-level building blocks enable valuable multiplier technologies. You should remember that these building blocks are not the entirety of your use case potential. Building a set of comprehensive views on top of an integration pipeline and ontology structure is your *starting point* for unlocking potential for flexible, interconnected, and data-driven operational workflows.