Enterprises invest significantly in supporting critical service level agreements (SLAs), stocking crucial parts, and collaborating with external contractors. After-sales service represents a significant portion of revenue and profit. Things break unexpectedly, and sometimes emergencies need to be attended to before scheduled jobs. How can an Enterprise Service logistics team become proactive?

Ascendo's PredictGPT module is the answer to the questions related to all the missed SLAs by your team. Ascendo Cognitive Parts Planning is introduced as a solution involving proactive management of parts, tools, and locations to deliver spare parts efficiently. By analyzing enterprise service, install-base, and materials planning data, valuable insights can be gained to accurately predict demand and prepare the service organization accordingly. The application of machine learning principles helps implicitly learn failure patterns, enabling the development of prediction algorithms for component demand.

Ascendo Cognitive Parts Planning is presented as a solution, leveraging modern technologies like AI (Artificial Intelligence) and machine learning to proactively manage spare parts. Ascendo’s PredictGPT module analyzes enterprise data to predict demand, allowing for more efficient and prescriptive service operations.

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