Sales and market-share dashboards from IQVIA and NHS open data, field-force activity views and national-to-account drill-down — one governed Power BI model that refreshes itself, not a folder of exports rebuilt by hand every month.
In most pharma commercial teams, reporting is a monthly ritual: an analyst downloads the latest IQVIA extract, reworks a stack of Excel pivot tables, pastes charts into slides and emails a pack that is out of date before the brand review ends. Every question that follows — why is share down in that region, which accounts moved — means another manual cut of the data.
Power BI dashboards built properly for pharmaceuticals replace that ritual with one governed reporting layer. IQVIA sell-out, internal sales, CRM activity and NHS open prescribing data are consolidated into a single data model, often built on a pharmaceutical data warehouse, and every dashboard — national market share, sub-national performance, field-force activity — reads from it. When the source data lands, the dashboards update; nobody rebuilds anything.
Dashboards are usually the most visible part of applying AI in the pharmaceutical industry — the point where consolidated data actually reaches decision-makers. You can explore live, interactive examples of our work on the demos page.
A dashboard pack earns its place when it reflects how pharma actually measures the business — not when it displays the most charts.
Molecule and brand share built from IQVIA sell-out data, with market growth and share movement separated — so a falling number can be explained, not just reported.
Hospital medicines and primary-care prescribing datasets published by the NHS add a sub-national view that panel data alone can't give — once molecules, packs and geographies are mapped consistently.
Calls, coverage and frequency from the CRM shown next to the sales response in the same accounts — so activity is judged by what changed, not by how busy the calendar looks.
One model drives every level: national market, region, ICB and account. Definitions stay consistent as you drill down, so sub-national numbers always sum back to the national picture.
Distribution designed around how Power BI licensing actually works — workspace apps, capacity-based sharing and embedded reporting — so the whole team sees the numbers without licence sprawl.
Scheduled refresh aligned to each source's cadence, documented lineage and access control by role and territory — so the pack is always current, and two dashboards never disagree.
Sales, share and activity all read from the same governed dataset — so meetings spend their time on actions, not on whose number is right.
The monthly pack assembles itself. When IQVIA and NHS data land, the model refreshes and every dashboard is current before the review meeting.
Field teams, brand leads and leadership open the same dashboards — filtered to their role and territory, not forwarded around as screenshots.
Dashboards are thin views on a single documented data model — measures defined once, reused everywhere. No copy-paste datasets quietly drifting apart.
Each page answers a commercial question — where is share moving, which accounts changed, is activity landing — instead of displaying every metric we can compute.
We agree the distribution model — workspaces, apps, capacity or embedding — before building, so roll-out cost and access are known from day one.
You keep the workspace, the data model and the documentation. Your analysts can open, understand and extend every report — no agency lock-in.
Bring us the reporting your team rebuilds by hand every month. We'll consolidate the data, build the governed model and hand over dashboards that refresh themselves — see how we did it in our AI & BI dashboards case study, or explore our wider AI & data consulting services.
Most pharma commercial teams already run on Microsoft 365, so Power BI fits the tools people use every day and the security model IT has already approved. It handles IQVIA-scale datasets through a governed semantic model, supports row-level security so field teams only see their own territories, and lets one central model feed every report. That combination — familiarity, governance and scale — is why it has become the default reporting layer in pharma.
Part of our guide to AI in the pharmaceutical industry. See also pharma commercial analytics.