AI & BI use case · Business Intelligence

Cost-centre analysis

Break down and control costs transparently.

What it's about

Cost-centre analysis links booking data with production and personnel data to identify cost drivers, variances and savings potential.

  • More transparency
  • Cost reduction
  • Better decisions
Business case & ROI
−10 %

overheads

+15 %

transparency

3–6 Mon.

payback

−20 %

variance analysis

Calculated from identified savings and reduced controlling effort.

How we do it
  1. 01

    Data integration

    Consolidate data from ERP, MES and further sources for Cost-centre analysis.

  2. 02

    Data quality

    Clean, harmonise and validate data for plausibility.

  3. 03

    Model development

    Train and validate the Cost-centre analysis model on historical data.

  4. 04

    Pilot

    Pilot Cost-centre analysis in one area and collect feedback.

  5. 05

    Rollout

    Scale the solution and integrate it into operational processes.

5

Steps

6

Data sources

4

Stakeholders

From first data access to production – every step delivers a tangible interim result.

Data typically needed

Financial data

Cost centres, budgets, cash flows and invoices.

ERP data

Master and transaction data from ERP.

MES data

Production orders, feedback and machine data.

HR data

Shift plans, qualifications and absences.

Energy consumption

Electricity, gas, water and steam per area.

Documents

Specifications, quotes, contracts and reports.

Stakeholders
  • CFO

    Receives reliable financial and risk metrics.

  • Controlling

    Quantifies effects and supports budgeting.

  • Production manager

    Uses insights directly in daily operations.

  • IT

    Builds on a scalable and secure data infrastructure.

Typical business value
01

More transparency

02

Cost reduction

03

Better decisions

04

Better planning

05

Higher efficiency

The data platform advantage

With a solid data foundation this use case gets faster, cheaper and far more stable.

Central data platform

Real-time data integration

Scalable analytics pipelines

Reusable data products

Build a data platform
Synergies & positive side effects

Automated reporting

Metrics are provided without manual effort.

BI reporting

Metrics are delivered in dashboards.

Demand forecasting

Data flow enables more precise forecasts.