Data-driven Process Automation

Manual routines slow down end-to-end processes

Every product development process includes tasks that no one performs for their professional value: following up, forwarding information, checking status, sending deadline reminders, or transferring data from one place to another. When these routines are handled manually, they consume time, trigger follow-up questions, and can slow down end-to-end processes. At the same time, business departments need to adapt processes quickly to new requirements without requiring programming effort for every change. Data-driven Process Automation addresses this by linking data events with rules and automated follow-up actions.

Benefits

Use data to trigger processes
Reduce manual routines and accelerate action
Empower business users with a no-code approach
Improve process quality
Build trust through traceable processes

Event, condition, action – use data to trigger processes

Every automation follows a simple pattern: An event occurs in the data, a condition determines whether and which rule applies, and a defined action is executed. Triggers can include a status change, a changed metric, a missed deadline, or a signal from a connected system. The rules are therefore tied directly to the current state of the data. This also makes it possible to handle branching scenarios without defining every possible sequence as a rigid process chain: The rule specifies what should happen in a particular situation, and the follow-up action starts automatically.

Event, condition, action – use data to trigger processes

Design process logic in the business department without programming

Those responsible for a process from a business perspective need to adapt rules quickly as requirements change. Data-driven Process Automation supports this with a no-code approach: select triggers, define conditions, specify actions, assign responsibilities, and pass on information. This enables business departments to remain in control when designing and adapting their process logic. IT provides the necessary framework through permissions, approvals, and interfaces, but does not have to program every individual rule change. This allows operational processes to evolve flexibly without losing sight of platform governance.

Design process logic in the business department without programming

Automate routine tasks and improve process quality

Reminders, forwarding, status updates, completeness checks, and data transfers between systems consume capacity and are prone to errors when handled manually under time pressure. Automation and transformation rules reliably take over these recurring tasks. This reduces effort, follow-up questions, and rework while ensuring that defined processes are executed consistently. Employees gain more time for activities where professional expertise and judgment are essential, such as engineering, evaluation, and decision-making.

Automate routine tasks and improve process quality

Make automated processes traceable and build trust

Automation must remain traceable. Rules are visible, and triggered actions are logged, including information about who created the action, when it was executed, and what happened as a result. This makes it possible to understand why an automated process occurred and which follow-up action was triggered. This transparency builds trust in data-driven processes and supports standardized, quality-assured execution. At the same time, rules can be reviewed and adjusted as requirements change.