| Status | |
| Owner | LEIGHTON-ext, Dean |
| Stakeholders | The persons consulted or otherwise involved in making this decision. Type @ to mention people by name |
This Key Decision Document (KDD) serves as a comprehensive guide outlining critical decisions, considerations, and recommendations essential to the implementation and management of Asset Performance. It aims to clarify the rationale behind exploring and evaluating whether to extend advanced and data-driven approach to asset maintenance across all plants based on selected assets in comparison to standard SAP preventative maintenance process.
Key areas covered in this document include:
Overall, the purpose and structure of the KDD ensure clarity, transparency, and accountability throughout the process of adopting and utilising Asset Performance Management functionalities within Syensqo.
Summarise the recommendation being made for the reader, leaving the pro/con evaluation and exact decision-making process to the subsequent sections.
Syensqo currently employs preventive maintenance for a diverse range of assets across all their plants, including those critical to safety and production operations. However, asset management is handled individually at each plant, lacking a standardized approach. This leads to inconsistencies in how similar assets are proactively maintained, resulting in potential inefficiencies and varying maintenance standards.
Currently, only one plant utilizes advanced maintenance functionalities such as predictive maintenance and real-time asset monitoring. These advanced features allow for data-driven decision-making and proactive issue resolution. In contrast, the rest of the organization relies on standard SAP preventive maintenance, which focuses on scheduled tasks and routine inspections without leveraging advanced analytics or real-time data. This disparity in maintenance practices highlights the need for a cohesive and standardized approach across all plants to ensure consistent asset management and optimization throughout the organization.
As-Is Summary
At present, only the Tavaux plant leverages the advanced functionalities of asset performance management, which encompass predictive maintenance, real-time monitoring, and comprehensive asset performance insights. The rest of the organization relies on standard SAP preventive maintenance, which focuses primarily on scheduled maintenance tasks without advanced analytics and predictive capabilities.
Opportunities
There is an opportunity to standardize and improve maintenance practices organization-wide, potentially closing the gap between strategy and execution.
Introducing strategies such as predictive maintenance, asset health monitoring, and risk-based maintenance, integrated with a program like SAP APM, can significantly enhance asset reliability, minimize downtime, and increase efficiency.
Clearly describe the underlying assumptions which informed or limited the choices available, or impacted the decision: cost, schedule, regulatory requirements, business drivers, country footprint, technology, etc. Include links as necessary. This section is important because a future change in circumstances might invalidate some key assumptions, which then prompts a decision to be revisited.
Capture any additional constraints that the chosen alternative (i.e. the decision made) might impose on other parts of the overall design, solution, or processes.
Licensing: APM - Asset Performance Management requires a separate license, based on number of objects (Equipment)
Currently, no specific business rules have been identified. Further updates may be determined during the detailed design phase.
Option A: Implement S/4HANA - APM (Asset Performance Management)
This option involves extending the implementation of S/4HANA APM across the entire organization for selected assets. APM is a comprehensive solution designed to optimize asset reliability and performance through advanced analytics and strategic maintenance practices. It facilitates a holistic view of asset health, enabling organizations to implement effective maintenance strategies. Key functionalities include:
By improving collaboration among maintenance teams and offering tools for performance benchmarking, APM helps organizations minimize downtime, reduce maintenance costs, and extend the lifespan of their assets.
It is important to note that while time series data significantly enhances the predictive capabilities of S/4HANA APM, the module still offers numerous benefits that can improve overall asset management, maintenance strategies, and operational efficiency.
High Level Capability Process

Data - As shown in the below flow diagram, data is not required to be maintained separately in 2 applications. Master data held within S/4HANA is the primary source of truth and then replicated into APM

This option involves continuing with the standard SAP preventative maintenance approach currently used by most plants. It focuses on scheduled maintenance tasks without incorporating advanced analytics or real-time monitoring capabilities.
Decribe the option in sufficient detail for a reader familiar with the subject matter to understand it properly
Decribe the option in sufficient detail for a reader familiar with the subject matter to understand it properly
Outline why you selected a position. The best format could be a pro/con table (sample below), but is up to you as the author. You must consider complexity, feasibility, cost/effort to implement, but also ongoing operational impact and cost. You must consider the program principles and explain any deviations in detail. This is probably as important as the decision itself.
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Insert links and references to other documents which are relevant when trying to understand this decision and its implications. Other decisions are often impacted, so it's good to list them here with links. Attachments are also possible but dangerous as they are static documents and not updated by their authors.
