Eight hundred organisations. The right one was never at the top.
Field teams at a life sciences platform needed to understand how hundreds of health care organisations connected to each other, and which people inside them mattered for a given plan. Before this tool, they worked from static exports and one-off reports. There was no way to explore a large hierarchy directly, or to narrow it down to the people who actually mattered.
Every project turns on one question: is the obvious explanation the right one?
The problem was visibility. Give people a tree view of the hierarchy, and they will find what they need.
Visibility alone does not help at this scale. One health system has 818 direct organisations. A tree of 818 organisations is not more useful than a spreadsheet of 818 rows, because the user still has to know where to look. The real problem was narrowing the list down, not showing all of it. When the same system is filtered down to organisations with neurologists, the list drops to 91, about a ninth of the size. That drop is the whole argument. The tool's job is not to display the hierarchy. It is to collapse it down to the part that matters for the question being asked.
Nobody needed to see all 818. A rep planning around neurology needed the 91 that answered the question in front of them, and needed to get there without knowing the structure in advance. That made narrowing, not display, the design problem.


Keep organisation filters and person filters separate
The Active Filters dialog splits organisation-level filters, like corporate name, state, HCO type, city and class of trade, from person-level roll-up filters, like HCP type, relationship type, specialty and medical degree.A user filtering for neurologists is answering a different question than a user filtering for HCOs in one state. Splitting the dialog into two groups keeps those two questions from turning into one long list of checkboxes.
Split every roll-up count into direct and total
Every HCP count in the hierarchy is broken into two numbers: how many professionals report directly to this organisation, and how many report to it once every indirect affiliate is included.A compensation or territory decision needs to know which number it is using. Collapsing the two into one count would hide that difference and make the math downstream wrong.
Let people switch between exploring organisations and exploring people
Inside one hierarchy, a user can switch between an Explore HCOs view, with child organisations and roll-up counts, and an Explore HCPs view, with every health care professional, their specialty, and which organisations they are affiliated with.These are different jobs. One is about structure. The other is about finding a specific person. A toggle keeps each view readable instead of merging them into one dense table.
Make export a first-class action
Selected HCOs or HCPs can be exported straight to Excel from inside the widget.The real decision usually gets made downstream, in a compensation tool or a territory plan. Export exists because the widget's job ends at giving someone the right subset of data, not at replacing every tool they use after that.

One long listorganisation and people filters, mixed
Organisation filters and person filters, kept apart instead of one long checklist.
Every roll-up count split into direct and total, so a territory or compensation call knows which number it is using.
Anmed Health Admina health system, 0 direct HCPs
Every organisation818 direct HCOs, nothing narrowed yet
The argument redrawn: a dense, undifferentiated cluster fades down to a small, countable one once a filter actually narrows it.

When a hierarchy gets large enough, showing it is not the same as making it useful. Before you build a better viewer, check whether the real ask is a better filter.
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