High-efficiency manufacturing involves the transmission of copious amounts of data, exemplified both by trends in the automotive industry and advances in technology. In the automotive industry, products have been growing increasingly complex, owing to multiple SKUs, global supply chains and the involvement of many tier 2 / Just-In Time (JIT) suppliers. On top of that, recalls and incidents in recent years have made it important for OEMs to be able to track down affected vehicles based on their components. All of this has increased the need for OEMs to be able to collect and analyze component data. The advent of Industry 4.0 and IoT has provided manufacturing with the ability to efficiently collect and store large amounts of data, lining up with the needs of manufacturing-based industries. However, while the needs to collect data have been met, corporations now find themselves facing the need to make sense of the data to provide the insights they need, and the data is often unstructured, incorrectly formatted or incorrectly collected. This paper discusses a possible use case of leveraging automation to help meet these needs. By automating data cleaning and analysis, companies obtain insights more quickly, reduce the need for manual-based data intervention, and minimize the risk of human error. Beyond streamlining data analysis, automation enables real-time interventions, such as cleaning data as it comes in (event-driven automation) and providing continuous system monitoring. This paper explores the significant role of automation playbooks in enhancing these processes. Playbooks facilitate the creation and management of automation flows by treating scripts and tasks as modular blocks that can be easily arranged and modified to suit different environments and setups. This modular approach allows for greater flexibility and a "hands-off" automation model, where processes can be deployed on a scheduled basis with minimal manual oversight. In essence, automation can play a critical role in manufacturing's needs to reliably make sense of their data, and the use of playbooks further optimizes these benefits by simplifying the management and execution of automated tasks.