Digital Supply Chain (DSC)
Read more
Embedded Analytics in SAP DM No more Excel reporting on the store floor
There is plenty of production data available today, but decisions in manufacturing are often made too late or on the basis of historical evaluations. The reason is rarely a lack of digitalization, but rather system breaks in reporting: data is exported, manually consolidated and prepared in Excel. Meanwhile, production continues.
This is problematic for managers: downtimes, quality losses or material bottlenecks only become visible when the shift is long over.
This is precisely whereembedded analytics in SAP Digital Manufacturing (SAP DM) comes in and shifts the basis for decision-making to where it has an operational impact: the store floor.
Architecture without system discontinuity: what "embedded analytics" in SAP DM really means
Embedded analytics are analysis and reporting functions that are natively available in the SAP DM context. Instead of extracting production data from the MES, key figures are visualized directly in the process.
Technologically, this is achieved via SAP Digital Manufacturing for Insights (DMi) is used to realize this. Production data is structured there in Manufacturing Data Objects (MDOs) and evaluated via an embedded SAP Analytics Cloud.
Important for decision-makers:
The data is up-to-date and available close to the shift, without Excel detours or external BI systems. At the same time, it is clear that this is operational analytics, not a company-wide data lake.
This results in four key effects for production managers, plant managers and operations managers:
- Faster response in the current shift
Deviations become visible while they can still be influenced. - Reduction in manual reporting effort
Excel exports and manual consolidation are largely eliminated. - Fact-based root cause analysis
KPIs are in the context of orders, materials and resources, not in isolation. - Standardized KPI logic
Discussions about "the right number" are reduced.
Particularly in the store floor environment, it is not the quantity of KPIs that is decisive, but their direct relevance to management.
The KPIs that really count in practice
From IGZ's point of view, projects show time and time again that a manageable set of key figures provides the greatest benefit:
- OEE (Overall Equipment Effectiveness)
As a product of availability, performance and quality - with drill-downs to downtime or quality causes. - Downtimes & downtime categories
The decisive factor is not the downtime itself, but its proper classification. - Quality indicators
Rejects and rework have a direct impact on costs and delivery reliability. - Throughput and cycle times
Central parameter for capacity evaluation and adherence to delivery dates. - Traceability / as-built
Relevant for quality assurance, complaints and compliance.
The decisive factor here is not the sheer number of KPIs, but their semantic link to orders, materials and resources. SAP DMi does not present KPIs in isolation, but embedded in the operational production context, making them directly relevant to management.
The OEE (Overall Equipment Effectiveness) calculation deserves special attention, as it is the gold standard of production KPIs. SAP DM calculates OEE strictly as a product of three factors: availability, performance and quality. Each of these dimensions can be broken down in the system down to the lowest resource level. Multi-level drilldowns show immediately whether a loss of OEE is due to unplanned downtime, gradual loss of speed or acute quality problems.
Practical example: When data changes behavior
A frequent case in practice: micro downtimes are not or only insufficiently recorded. Over the course of a shift, they add up to considerable production losses without any visible cause.
With SAP DM and Embedded Analytics, the machine reports every downtime automatically. The reason is systematically recorded via the Fiori interface and visualized in real time.
Several projects have shown:
The problem was not the machine, but a lack of material at the workstation. The actual optimization was therefore not in maintenance, but in integration with SAP EWM and just-in-time material provision.
This is precisely where the added value of embedded analytics becomes apparent:
No longer "What's wrong?", but "Why?" and where to start.
Where the SAP standard deliberately ends
Embedded analytics in SAP DM is strong in an operational context. Dashboards and reports support shift, line and plant management very effectively.
For strategic issues, such as
- Cross-plant consolidations,
- combination of production, logistics and commercial key figures,
- long-term trend and capacity analyses,
the pure DMi context is not sufficient in many cases. This is where the data architecture determines the sustainable benefit.
From IGZ's point of view, the decisive factor is therefore
Which data belongs in the store floor context and which belongs at a higher analytics level?
Embedded analytics as part of an overall strategy
In modern architectures, SAP DM forms the operational basis. Supplementary components such as SAP Datasphere, SAP Business Data Cloud and the enterprise version of SAP Analytics Cloud then enable a bridge to be built between production, logistics and management.
Embedded analytics is therefore not a competing approach to enterprise analytics, but the operational basis on which reliable decisions can be made.
IGZ perspective: Why technology alone is not enough
IGZ does not support companies in "activating dashboards", but in the structured introduction of a controllable analytics landscape:
- Use case definition from a management perspective
Which decisions should be made faster or better? - KPI and data governance
Standardized definitions, responsibilities and data quality. - Architecture design
Clear separation between the operational SAP DM context and the overarching analytics level. - Integration of adjacent SAP systems
In particular SAP EWM and SAP S/4HANA.
This transforms SAP DM from a data collector into a genuine management tool.
Conclusion: Transparency becomes a competitive advantage
Embedded analytics in SAP DM creates transparency where it has the greatest leverage: directly on the store floor.
Real-time key figures replace delayed Excel reports and enable decisions to be made during the ongoing process.
The SAP standard convincingly covers operational requirements. However, sustainable success can only be achieved if embedded analytics is embedded in a clean overall architecture.
It is precisely at this interface that IGZ contributes its experience to ensure that transparency is not only visible, but also effective.
We look forward to hearing from you!
