Term

Data visualisation

Presenting numbers in charts, tables and dashboards so trends, comparisons and deviations are clear at a glance. Good visualisation speeds up decisions; bad visualisation can distort the figures.

Updated

What it means

Data visualisation means presenting numbers in charts, tables and dashboards so that trends, comparisons and deviations are clear at a glance. People take in the shape of a line or a colour faster than a column of figures, so good visualisation shortens the path from data to decision.

Each chart type suits a different purpose. Line charts show change over time, bar charts compare categories, pie charts show shares of a whole for a few items, and scatter plots show the relationship between two variables. Project management uses the Gantt chart.

Visualisation is the foundation of business intelligence and management accounting. An owner does not need the whole balance sheet but an overview of how revenue, margin, cash flow and overdue receivables are developing, ideally on one screen.

How it works in practice

A good report starts with a question, not a chart. If management wants to know whether the plan is on track, the chart should show actuals against plan and last year. Each important KPI needs just one clear visual with a title stating the main finding.

For financial data, waterfall charts showing how revenue turns into profit, or ageing charts for receivables, are useful. Linking to a balanced scorecard lets you track not just finances but also customers, processes and people.

Tools range from spreadsheets to specialised BI platforms that pull data directly from accounting software. Automatic connections save time and reduce manual copying errors, but they require consistent code lists and correctly posted documents.

What to watch out for

A chart can distort figures. A y-axis that does not start at zero exaggerates small differences, 3D pie charts warp proportions and too many colours look chaotic. Before presenting, check that the visual gives the same impression as the numbers themselves.

A beautiful dashboard with wrong data is worse than none because it creates false confidence. Every view should make clear where the data come from, what date they refer to and whether they are closed in the books or only preliminary.

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