Method
Our
six-field framework.
A data-driven organization develops through many concrete changes. Our framework helps me coordinate them across six connected fields.
Create conditions
that work in practice.
People use data when it makes their work easier. I work with you on workflows, decision rights and incentives as well as the technical foundations. The guardrails should make the intended way of using data the easiest one.
The six fields can reinforce or hold back one another. Access to data does little if nobody owns the numbers. We identify dependencies, choose manageable actions and build a coordinated plan from there.
One task.
Several fields of action.
A concrete task shows how organizational and technical changes depend on one another.
ILLUSTRATIVE EXAMPLE
Automate a monthly report
Sales leadership needs variance analysis without monthly manual preparation.
- 01
People: An internal team member helps run the process and later takes over.
- 02
Data Quality: Checks stop incomplete data before release.
- 03
Data Architecture: A documented data connection supports other compatible reports.
- 04
Data Governance: The business team defines orders and how to treat cancellations.
- 05
Automation: Calculation and checks run on a schedule, with a process for failures.
- 06
Analytics & AI: The report answers the agreed business question.
POSSIBLE NEXT STEPCheck the next reporting cycle for remaining manual work.
Examples and distances are illustrative, not measured client results or maturity levels. One action need not improve every field.
The six
fields of action.
01People
What do people need to put the strategy into practice?
We agree roles, learning needs and decision rights. With leadership, we make time and align incentives so people can share data and take responsibility.
- WHAT WE PUT IN PLACE
- A clear role with time, access and decision-making authority.
- WHAT MAKES IT WORK
- People need to exercise their new responsibilities in practice, with onboarding and leadership support.
02Data Quality
Which error would distort the decision?
The business team sets quality requirements. We implement checks and agree who fixes errors.
- WHAT WE PUT IN PLACE
- Validation rules and a process for dealing with failures.
- WHAT MAKES IT WORK
- Stop incorrect reports and fix the cause at the source.
03Data Architecture
What architecture and infrastructure do we need?
We develop the target architecture from the strategy and build the required components step by step. Existing systems, permissions and operation help determine the route.
- WHAT WE PUT IN PLACE
- A reasoned target architecture and usable infrastructure for the next tasks.
- WHAT MAKES IT WORK
- Other applications reuse the connection where meaning and requirements match.
04Data Governance
How are data owned and decisions made?
We shape data management around clear ownership, shared definitions and usage rules. Approvals and change handling become part of the workflows.
- WHAT WE PUT IN PLACE
- Agreed responsibilities and rules with a practical route to decisions.
- WHAT MAKES IT WORK
- People need to understand the rules and be able to apply them in their workflows.
05Automation
Which manual steps can we remove?
We clarify and change the workflow before automating suitable steps. This includes data preparation, checks and handling exceptions.
- WHAT WE PUT IN PLACE
- A repeatable process with validation logs and error handling.
- WHAT MAKES IT WORK
- The old manual process must be ready to retire.
06Analytics & AI
What should happen as a result?
We agree with users which decision the application supports and compare its value with the current process.
- WHAT WE PUT IN PLACE
- An application people use, with an agreed way to assess its value.
- WHAT MAKES IT WORK
- Actual use determines whether and how we develop the application further.
Tested in my work.
Documented in our book.
I developed the framework with Dr. Mariana Hebborn and Prof. Dr. Heiko Beier and have used it successfully on several occasions in my work. Our experience became “How to Become a Data-Driven Organization”.
After each implementation, we review whether people use the improvement and what still holds them back. This informs the next actions and refines the data strategy. Your company develops the ability to put that strategy into practice.
More about our bookData architecture and implementation in motionWhere would you
like to start?
You do not need a fully defined brief. We can work out together where I can help.