SAP and KPIs: The right tool for every task

To continuously improve maintenance, companies cannot get around working with key performance indicators (KPIs). However, KPIs on their own are of little value. They must be embedded in a holistic strategy to truly provide direction. 

That’s why companies should answer the following questions first: 

• What specific objectives are we pursuing with our maintenance? 
• How can these objectives be measured and managed using KPIs? 
• What target values do we aim to achieve? 

For KPIs to reach their full potential, one other factor is critical: They must be monitored and analyzed with minimal effort. Otherwise, controlling remains an ambitious task, too often sidelined by the demands of daily operations. 

IT along the KPI lifecycle

IT plays a key role in practical, KPI-driven controlling. The more seamlessly software supports each stage of the KPI lifecycle, the more effective controlling usually becomes. 

In essence, the KPI lifecycle can be broken down into four stages: 

1. Data capture 
2. Consolidation & storage 
3. Analysis & evaluation  
4. Visualization 

Stage 1: Data capture

KPIs are derived from raw data, either aggregated into absolute KPIs or put in relation to other data as relative KPIs. The first step, therefore, is to capture the necessary data. 

Ideally, this happens automatically through IT systems, for example, sensors that continuously record equipment statuses. When automation isn’t possible, employees must enter the data manually. In such cases, mobile devices are especially valuable, as they enable data capture directly at the point of action. 

Stage 2: Consolidation & storage

To get meaningful KPIs, data from multiple sources often need to be combined. Structured storage is essential to enable later analysis. In maintenance, the ERP system – specifically its underlying database – is typically the primary source of relevant data. However, additional valuable information may also reside in a Manufacturing Execution System (MES) or other specialized application. 

Stage 3: Analysis & evaluation

Data evaluation typically relies on straightforward mathematical formulas to distill information into meaningful KPIs. In most cases, basic arithmetic – addition, subtraction, multiplication, and division – is sufficient to generate the necessary insights. 

Stage 4: Visualization

While AI will increasingly assist in decision-making, it is still people who most often rely on KPIs to guide their choices. This makes clarity and accessibility essential. Effective visualization should be role-oriented and tailored to the specific purpose, ensuring that decision-makers can quickly interpret and act on the information. 

IT support across all four stages

IT is integral to every stage of the KPI lifecycle. However, two key requirements, in particular, must be met: 

1. High data quality: Data should be captured completely and in a standardized format to ensure accuracy and consistency. 
   • Ease of use: Systems must be intuitive and user-friendly. This not only promotes high data quality but also encourages regular use of KPIs in day-to-day decision-making.

What does the SAP portfolio offer?

Companies using SAP can draw on a broad set of tools to support every stage of the KPI lifecycle. Some are ideal for straightforward evaluations, while others enable more advanced, in-depth analyses. 

From our perspective, the following tools are particularly relevant for maintenance KPIs: 

• SAP ABAP List Viewer (ALV) 
• SAP Query and SAP QuickViewer 
• SAP Plant Maintenance Information System (SAP PMIS) 
• SAP S/4HANA Embedded Analytics/Apps for maintenance 
• SAP Analytics Cloud (SAC) 

The choice of technology depends largely on the company’s specific situation and project needs. SAP ABAP List Viewer, SAP Query, and SAP QuickViewer are best suited for generating lists and performing simple aggregations, such as totals or counters. In contrast, the SAP Plant Maintenance Information System (SAP PMIS) is designed for maintenance-focused evaluations and KPIs such as damage and failure analyses, or metrics like Mean Time Between Repair (MTBR) and Mean Time To Repair (MTTR). 

Conclusion: State-of-the-art analysis with SAP S/4HANA and SAC

Looking ahead, SAP is focusing its analytics strategy entirely on SAP S/4HANA Embedded Analytics and the SAP Analytics Cloud (SAC). Together, these solutions enable advanced and flexible evaluations. SAP continuously expands their capabilities by releasing new apps, available through the SAP Fiori Apps Reference Library. 

SAP S/4HANA Embedded Analytics offers a highly operational approach, delivering real-time analysis and visualization directly within the ERP system. In contrast, SAP Analytics Cloud serves as a comprehensive business intelligence platform, facilitating deeper analysis by consolidating data from multiple sources, aggregating it into KPIs, and presenting it through interactive stories or digital boardrooms.