Use Cases

How BI dashboards help executives see the real business picture

At most large companies, the executive receives reporting weekly or monthly with data delays and source contradictions. This affects management decision quality and speed. This scenario covers how to build a BI contour that delivers a real-time business picture.

Discuss Your Challenge

Applied scenario: building a BI contour with actual data for the executive. Effect on management decision quality, reaction speed, data-driven culture.

Trigger

A company or unit leader makes a decision requiring data on business state — investment prioritization, team effectiveness assessment, market change response. In today's model, the data request goes through IT, the answer arrives in 1-3 days as an Excel table. By the time data arrives, it is stale or the question has changed. In the right model, the leader opens a dashboard and sees the actual picture, drills the metric of interest down to source.

What banks usually do today

At most regional companies, BI tools exist but are used limitedly. Standard reports are built weekly or monthly on stale data. Each unit builds its own dashboards with different metric definitions — revenue is calculated differently in finance and product blocks. Ad hoc data requests go through IT with delay. Analysts spend significant time reconciling data between sources.

What the bank loses

Management decision quality — on stale or contradictory data
Speed of reaction to market changes or internal signals
Analyst and IT time — handling repetitive leader requests
Data trust — contradictory numbers in different reports undermine BI trust altogether
Ability for early problem identification — before they become big losses
Systemic organization learning to work with data — without accessible BI, data-driven culture does not form

How this can be improved

Build a BI layer with unified metric definitions on a single data source (data platform). Dashboards for leaders at different levels tied to their decision agenda. Real-time data access with ability to drill metrics to source. Alerting on anomalies and significant deviations. Leader and team training on BI work as mandatory program part. Regular dashboard review based on actual management questions.

What you need

Unified data model with agreed metric definitions
Real-time sources — operational systems publish events to the data platform
Data quality management layer — source errors are visible and processed
Metric catalog — definition of every key metric with author and owner
Historization — ability to analyze trends over long periods
Security — sensitive metric access control

What the bank gets

Management decisions made on actual data, not weekly snapshots
Reaction time to business signals shortens from days to hours
Analyst time on repetitive requests shortens significantly — frees up for deep analytics
Data trust grows through unified definitions and quality
Early problem detection through alerting — before they become big
Data-driven decision culture forms through tool accessibility

How to start realistically

Start with one leader and one business area with clear decision agenda. Build a minimum viable dashboard based on that leader's actual questions. Run for 1-2 months, adjust based on actual usage. In parallel — work on unified company-level metric definitions. After 6-9 months — expansion to other leadership positions with their own dashboards. After 12-18 months — data platform update to support growing load and complexity.

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