Data & AI Strategy
Strategy before technology
A data & AI strategy answers which data you need, how information flows, who is responsible – and which measures measurably improve revenue, costs and risk.
Five pillars
From vision to planning
Along these five pillars we develop the data & AI strategy together with you.
Vision
- Business model
- Market situation
- Vision
Data
- Internal and external data sources
- Data quality
- Data availability
- Data security and data privacy
Information
- Design of information gathering
- Information flow
- Real-time and in-time availability
- Data tools and methods
Knowledge
- Data-driven thinking
- Organisation and responsibilities
- Rating, evaluation, accuracy
- Prioritisation
Planning
- Prototyping
- Make or buy
- Team setup
- Milestones
Data strategy – concrete measures for
- More revenue
- Less cost
- Improved risk management
Data & AI Assessment
Keeping the interfaces in view
Developing a data & AI strategy also means paying particular attention to the many interfaces within the company.
The interfaces exist not only between the IT systems, which can be the source and target systems for any AI application. Business processes and stakeholders such as suppliers and customers are also important interfaces.
- IT systems
- Data
- API
- AI
- Business process
Data Analytics Evolution
Four maturity stages of analytics
The value grows with each stage – and so does the complexity. We pick you up where you stand.
- 01
Descriptive
What business events did happen – and when? Standard reporting, BI, OLTP/OLAP.
- 02
Diagnostic
Why do business events happen? Causality analysis on clean data.
- 03
Predictive
Which business events will happen – and when? Forecasting models with big value.
- 04
Prescriptive
How to configure the business to reach the optimum? Optimisation – the full value.
Data vs. Digital
More data thanks to digitalisation
Digitalisation generates data: applications in hardware and software fill databases and data lakes. Only analysis with data science, big data and AI turns it into knowledge that flows back into the applications.
- 01
Application (hardware)
- 02
Application (software)
- 03
Databases (data lake)
- 04
Analysis (data science)
Where does your company stand?
With a data & AI assessment we create clarity within a few weeks about your data foundation, interfaces and the most effective next steps.