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AI & BI use case · Business Intelligence

Investment planning

Prioritise investments based on data.

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What it's about

Data-driven investment planning evaluates projects by cost, benefit, risk and strategic relevance, making decisions traceable and reproducible.

  • Better decisions
  • More transparency
  • Lower risk
Business case & ROI
+15 %

return on capital

−20 %

bad investments

6–9 Mon.

payback

100 %

transparency

Calculated from higher portfolio returns and fewer failed projects.

How we do it
  1. 01

    Data integration

    Consolidate data from ERP, MES and further sources for Investment planning.

  2. 02

    Data quality

    Clean, harmonise and validate data for plausibility.

  3. 03

    Model development

    Train and validate the Investment planning model on historical data.

  4. 04

    Pilot

    Pilot Investment planning 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.

Project data

Projects, milestones and resources.

Sales data

Orders, revenue, channels and customer feedback.

Production data

Orders, quantities and feedback.

Documents

Specifications, quotes, contracts and reports.

Stakeholders

  • CFO

    Receives reliable financial and risk metrics.

  • Controlling

    Quantifies effects and supports budgeting.

  • Management

    Receives reliable metrics for strategic decisions.

  • IT

    Builds on a scalable and secure data infrastructure.

Typical business value
01

Better decisions

02

More transparency

03

Lower risk

04

Better planning

05

Higher margins

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.

Demand forecasting

Data flow enables more precise forecasts.

BI reporting

Metrics are delivered in dashboards.

More use cases

Management Cockpits

Revenue, margin and cash at a glance – updated daily instead of once a month.

Finance & Controlling Reporting

Month-end close and cost-center reports without an Excel marathon at the start of the month.

Sales & CRM Analytics

Make pipeline, forecast and customer potential visible instead of guessing in the CRM.