01Manage cases
Get an overview of ongoing investigations in a workspace
Open stories, statuses, and responsibilities are all visible to everyone. Teams can immediately see which cases require attention or a decision.
IoT Data Hub · Collaboration
Analyses are transformed into shared production knowledge.
Data Stories connect data, hypotheses, decisions, and actions into a coherent case study. This turns the resolution of a problem into valuable knowledge for the entire team.
Part of the IoT Data Hub
Diese Fähigkeit arbeitet auf derselben Konnektivität, Semantik, Historie und Governance wie alle Data-Hub-Werkzeuge.
When a problem is solved, but the solution is lost
Data Stories integrate analysis and decision-making right where the relevant production data is located.
- 01
Process knowledge remains in individual minds
Lessons learned from malfunctions and quality issues are lost during shift or team changes.
- 02
Data and discussion take place in separate channels
Charts are in the analysis system, hypotheses are discussed in meetings, and actions are listed in emails or to-do lists.
- 03
The solution will no longer be traceable later on
Without a shared context, it remains unclear which observation led to which decision and action.
- 04
Similar incidents start from scratch time and time again
The lack of search functionality and structure prevents teams from reusing proven analyses and countermeasures.
A Joint Approach to a Solution
From Eye-Catching to a Reusable Experience
The entire process remains tied to data and the production context—even across teams and shifts.
- 01
Ensure Visibility
A relevant situation is recorded as a data story directly from the analysis or dashboard.
Chart · Time Period · Investment · Signal
- 02
Add context
Notes, annotations, assets, and process knowledge give the anomaly its operational significance.
Station · Product · Shift · Event
- 03
Investigate together
Production, Quality, and Maintenance use the same data set to test hypotheses.
Comments · Authors · Hypotheses
- 04
Document the action
Decisions, implementation, and status remain linked to the original observation.
Action · Status · Ownership
- 05
Reusing Knowledge
Closed cases become searchable and provide quicker assistance in similar situations.
Search · Labels · Best Practices
02Preserve the context
Combining Data, Hypotheses, and Actions in a Story
Charts, annotations, and the context of the process are preserved along with the discussion and the solution path.
03Get AI support
Creating a Structured Design Based on Notable Features
AI can synthesize existing observations and lay the groundwork for a joint investigation. The technical evaluation remains the responsibility of the team.
Collaboration and Knowledge
How Data Stories Fit into the Improvement Process
How Is a Data Story Created?
A story can be created based on an existing analysis or anomaly and then supplemented with charts, annotations, asset context, comments, and actions.
Who can participate in a study?
Production, Quality, Maintenance, and Data teams all work on the same story in the browser. Responsibility assignments and edit statuses make collaboration transparent.
How are similar cases identified?
Stories remain searchable based on assets, stages, processes, labels, and other contextual features. In this way, documented solutions become a shared knowledge base.
What role does AI play?
AI assists with summarizing and organizing information. It does not replace either the expert assessment or the documented decision of the responsible teams.
30-minute product demo
Which production scenario would you like to depict as a data story?
We show how data, discussion, accountability, and actions come together in a transparent investigation.
Product demo featuring a specific incident