Step 1: Agree the questions and KPIs
Start with decisions, not charts. Ask each team which decisions they make every week and which numbers they need to make them. Define every KPI precisely — for example, exactly what counts as an "active customer" — and write the definitions down. This single step removes most arguments about whose numbers are right.
Step 2: Find and connect the data
List every source: accounting software, CRM, e-commerce platform, marketing tools, databases and the spreadsheets people maintain by hand. Connect them through official connectors or APIs so data refreshes automatically instead of being copied and pasted.
Step 3: Model the data once
Clean and combine the data into a simple model — typically fact tables (sales, orders, tickets) and dimension tables (customers, products, dates). For growing companies a cloud data warehouse becomes worthwhile; smaller teams can often start with direct connections.
Step 4: Design dashboards people will use
- One dashboard per audience: leadership, sales, operations, finance
- The most important KPI at the top left, with trend and target
- Filters for period, region and product instead of dozens of pages
- Plain-language titles that state the insight, not just the metric
Step 5: Drive adoption
A dashboard that nobody opens has no value. Replace the old spreadsheet report rather than running both, review the dashboard in regular meetings, and collect feedback in the first weeks. Small improvements made quickly build trust.
Step 6: Go further with data science
Once reporting is reliable, the same data can power forecasting, customer segmentation and churn prediction — turning hindsight into foresight.
Our data analytics services team builds BI solutions in Power BI, Looker Studio and Tableau. To build these skills, explore our Data Analytics & Visualisation program.