We develop consistent KPI models and calculation logic so that metrics can be interpreted consistently across business units and reliably compared. Together with the relevant permissions, these definitions are embedded in a semantic layer. Dashboards, self-service analytics, and Conversational Analytics therefore all access the same KPIs, deliver consistent results, and only display information users are authorized to see.
Analytics, BI & Visualization
Business Intelligence for consistent key performance indicators and well-informed decisions
jambit develops standardised KPI models, decision-oriented reporting and interactive dashboards. We create transparent metrics frameworks and enable self-service analytics for business units – ensuring that decisions are based on a shared, reliable information base.
Promoting transparency and enabling informed decisions
Data alone does not create added value. It is only through structured analysis and clear visualisation that a reliable basis for decision-making is established. Yet in many organisations, there are multiple reports, manual Excel analyses and contradictory key figures. Decisions are delayed or made on the basis of incomplete information.
With Analytics, BI & Visualization, jambit creates the foundation for consistent KPIs, transparent analysis, and informed decision-making. We also develop Conversational Analytics solutions that enable business users to ask questions about their KPIs in natural language.
Analytics, BI & Visualization at jambit means:
We develop analytics solutions that make data understandable and support decision-making. This ranges from consistent KPI models and interactive dashboards to self-service analytics and Conversational Analytics, enabling business users to explore and clarify questions about their KPIs through dialogue.
Responsibility & Scope – What Analytics, BI & Visualization Covers
This area is about more than reporting or isolated dashboard development. We create the foundation for informed decision-making through consistent data models, intuitive visualizations, and modern analytics concepts that make business data easier to access.
Our scope of responsibility covers four clearly defined dimensions:
KPI Modeling & Semantic Layer
Reporting and Dashboard Structures
We develop dashboards that clearly communicate relationships and correlations and support decision-making – rather than simply visualizing data.
Self-Service & Conversational Analytics
Business units gain structured access to relevant data without relying on ticketing processes or manual workarounds. With Conversational Analytics, we extend dashboards with a natural-language interface: the language model manages the dialogue, while calculations and validation are performed in a dedicated analytics layer based on the semantic layer. This ensures that answers remain transparent, traceable, and reproducible.
Data Lineage & Transparency
KPIs, data sources, and calculation logic are documented transparently. Answers generated through conversational interfaces also indicate the source, time period, and filters they are based on. This creates traceable analyses and a reliable foundation for data-driven decision-making.
Our Approach to Decision-Making – Turning Data into Actionable Insights
Insights emerge when KPIs are understandable, consistent, and usable in the day-to-day business environment. Our approach combines structured analytics with language models as an additional way of accessing data. This creates traceable insights and verifiable courses of action.
1. Understand Decision-Making Needs
Which decisions need to be made regularly? Which KPIs and information are actually relevant to making them?
2. Make KPIs Comparable
Define clear KPI models with unambiguous calculation logic and clear responsibilities.
3. Use Visualization with Purpose
Dashboards are designed to support decision-making processes – not merely to display data.
4. Bring Analytics into the Dialogue
Business users can ask follow-up questions about their KPIs in natural language instead of requesting new analyses. Our own implementation, KPIxplain, demonstrates what this can look like. We presented it at LogiMAT 2026: A KPI dashboard for order picking is extended with a dialogue interface that identifies anomalies, presents potential factors influencing the error rate as testable hypotheses, and derives possible courses of action.
Services at a Glance
Depending on the starting point and maturity level, Analytics, BI & Visualization typically includes the following components. The specific scope can range from optimizing existing reporting structures to building a fully integrated and consistent BI landscape from the ground up.
- Analysis and consolidation of existing data, reporting, and KPI landscapes
- Selection, consolidation, and migration of BI tools and reporting platforms
- Development of consistent KPI models and calculation logic, embedded in a semantic layer
- Design and implementation of interactive dashboards and visualizations
- Embedded Analytics in proprietary applications, products, and customer portals
- Conversational Analytics using the native capabilities of established cloud and data platforms, in collaboration with our technology partners or as a custom development
- Self-Service Analytics for business units, including user enablement and training
- Documentation and transparency of data sources, KPIs, and calculation logic
Positioning Within the Overall Data Solutions Model
Analytics, BI & Visualization forms the transparency and decision-support layer within Data Solutions. We create the foundation for turning data into transparent information and reliable decision-making foundations. On this basis, the other areas of expertise work together – from Data Strategy & Governance and Data Engineering & Architecture to Data Activation.
Impact & Business Value
A structured analytics and BI landscape creates reliable foundations for decision-making and enables sustainable management and control.
When Analytics, BI & Visualization Makes Sense
This area is particularly relevant when:
- Reports provide conflicting figures
- Multiple BI tools are operated in parallel
- KPIs are not clearly defined or are calculated differently
- Decision-making processes are delayed by manual analyses
- Business units are heavily dependent on IT tickets
- Follow-up questions about dashboards regularly trigger ad hoc analyses
- Transparency across business units is lacking
Next Step – Build Transparency Systematically
Reliable decisions require clear, consistent, and traceable KPIs.
If you want to systematically evolve your reporting and governance logic, let’s talk.
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