Precision Data

From raw data to a basis for decisions

Our approach follows a clear path: we capture your operational systems, clean up the data streams, and transfer them into an analysis model that maps your key figures in real time. Every step is designed so that your management team no longer has to guess at the end—they know what matters.

Current-state analysis and data sources We inventory your ERP, CRM, and production systems, check interfaces, and identify gaps in data storage. This results in a source directory that forms the basis for all further steps.

Data model and preparation Raw data is normalized, duplicates are removed, and missing values are added in a traceable manner. The result is a consistent data model suitable for automated evaluations and forecasting models.

KPI framework and dashboards Together with your specialist departments, we define the key figures that are truly relevant for management and strategy. From this, we build dashboards that clearly visualize these values and allow drill-downs into the detailed data.

Predictive models and scenarios Based on historical data, we calibrate forecasting models for sales, capacity utilization, or cost development. You receive not only a forecast but also the uncertainty range, so decisions can be made with risk awareness.

Rollout and training The platform is deployed in your data center or in the cloud. Your teams learn how to use the dashboards and interpret the key figures—practically, using your own data.

Monitoring and further development After go-live, we support operations, monitor data quality and model performance, and adapt the evaluations to changing business processes. This keeps the platform reliable even during growth and new requirements.

Analysis functions for operational decisions

The platform consolidates data from production, sales, and finance in a unified environment. Instead of static reports, the system continuously delivers updated key figures that can be integrated directly into the workflows of specialist departments.

View module overview

Automated data preparation

Raw data from ERP, CRM, and logistics systems is automatically harmonized. Duplicates, missing values, and format deviations are detected and cleaned before the data enters the analysis environment.

Reduces manual effort for data maintenance by up to 70 percent.

Predictive forecasting models

Machine learning methods analyze historical sales and operational data to predict demand trends, inventory levels, and capacity peaks. The models automatically adapt to changing market conditions.

Provides reliable sales forecasts for the next twelve months.

Custom KPI dashboards

Managers receive role-based dashboards with the key figures relevant to their areas of responsibility. Drill-down functions allow switching from the overall view down to individual transactions.

Significantly reduces the time required for monthly reporting meetings.

Real-time anomaly detection

The system continuously monitors operational processes and reports deviations from expected patterns. Whether production failures, delivery delays, or unusual cost developments—relevant deviations become visible immediately.

Enables early corrective action instead of subsequent damage analysis.

Scenario simulations

Planning teams can play through various assumptions: price adjustments, staffing levels, or supplier changes. The effects on revenue, contribution margin, and liquidity are calculated in real time.

Creates a reliable basis for investment and budget decisions.

Integration into existing system landscapes

The platform connects to common ERP and CRM systems via standardized interfaces. Existing databases remain unchanged; the analysis environment is built up in parallel and rolled out gradually.

Minimizes migration risks and shortens implementation time.