Start with the decision
Ask who will look at the dashboard, how often and what they will decide as a result. A weekly sales review, a daily operations check and a monthly board pack need different views. If no decision changes, the chart probably does not belong.
Agree the definitions first
Revenue, active customer and on-time delivery can mean different things to different teams. Write down each metric’s definition, source and owner before building anything. Many dashboard arguments are really definition arguments.
Fix the data pipeline, not the chart
Reliable reporting depends on clean, consistently refreshed data. Connect sources such as your ERP, CRM and ecommerce platform through a pipeline that records when data was last updated and flags failures. Tools such as Power BI, Looker Studio and BigQuery work best on well-modelled data.
Design for a quick read
Put the most important figures at the top, show trends and targets rather than isolated numbers and keep each page focused. Microsoft’s Power BI guidance recommends designing for the audience and keeping the most important information prominent.
Add AI where it saves effort
AI can summarise what changed, answer plain-language questions about the data and flag unusual movements. It works best on trusted, well-defined data, and its summaries should link back to the figures they describe.
Prepared with AI assistance; technical references checked against the documentation linked above. These are planning considerations, not a guarantee of project results.
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