The scope selector at the top of the page applies to everything you see, including the headline figures. A score read on one department is not the same as the score read across the whole company, and both are correct.

Before comparing two figures, check that they were read with the same scope.

To protect employee privacy, Beamy never shows a result carried by fewer than seven people.

Two things can then happen. The group disappears from the chart, and a chip tells you which ones were removed. Or the whole section shows a message instead of the data.

A department missing from a chart is usually a department that is too small, not missing data.

On every time series, the last point covers a period that is still running. It always looks lower than the others. That is not a drop in usage.

An application you have archived, or one Beamy does not recognise yet, appears nowhere. If usage you expected is missing, start by checking the application status.

Everything is recalculated once a day, outside office hours. Usage from today shows up tomorrow.

The number of different people who genuinely use this application.

Beamy does not count passing visits. Real usage is required.

In a given month, a person counts if they meet one of these two conditions:

The figure then covers the past 30 or 90 days, depending on the period you selected.

A sharp rise on an unauthorized application is worth a Redirection or Investigation campaign before the habit settles in.

The share of employees who use this application.

The reference total is not your headcount. It is the people whose activity Beamy observes, over the same period and the same scope.

Someone who opens no monitored application counts on neither side.

This answers the question « why is this percentage not the one I calculate on my side ».

A high share does not mean deep usage. An application can reach a lot of people very superficially. Always cross-check with average weekly time and usage frequency.

How long one person spends on this application in an ordinary week.

If you read 50 minutes, someone who uses this application spends around 50 minutes a week on it.

The count starts from the first time each person was seen on the application, not from the start of the period. Someone who arrived two weeks ago is measured over two weeks.

Few users but a high time often signals a valuable niche tool, not a candidate for removal.

Many newcomers pull the average up, because they are measured over a shorter span. Check the trend chart before concluding that usage is growing.

A bar that sorts users into three groups according to how they use the application: high, medium, low.

Beamy looks at three things:

The first one counts far more than the other two. Someone who opens the application one day in five lands in the high group, even if their visits are short.

A large share of high-engagement users on an unauthorized application is a priority signal: the tool is already part of the routine.

Bars for the measure you select, and a line that keeps the number of users in view at all times.

You can track active users, weekly time, stickiness, or organization share. Two views are available: week by week over six months, or month by month over a year.

Read this chart for the shape of the curve, not for the exact value of one point. Measures are recomputed period by period, so an individual point can differ slightly from the headline figure.

A curve going up while the user count stays flat means the same people are doing more.

How people open this application: in their browser, with software installed on their computer, or both.

The three shares do not overlap: each person is counted once, in the group matching their usage.

How many people use this application every day, how many every week, and how many only a few times a month.

The three labels correspond to rhythms observed over three months:

These are reference bands, not exact cadences. Someone labelled daily does not necessarily use it every single day.

A fourth value, No usage, appears when nobody uses the application.

In the application list, the Usage frequency column shows the most common rhythm, the one covering the most users. It is not an average.

A majority of monthly users often points to usage tied to a specific moment, a month-end close for instance. That is not necessarily a sign of low value.

What kind of email address people sign in with: work, personal, or one Beamy could not recognise.

The three shares are counted separately. Someone who signed in once with their work address and once with a personal one appears in both.

Read the proportions as an order of magnitude, not as an exact split of your users.

Among the users of this application, how many work for the company and how many come from outside.

This comes from your organizational mapping. People with nothing filled in appear as unknown.

A significant share of externals on a sensitive application deserves a look.

A significant unknown share means your mapping is incomplete, not that you have anonymous users.

A ten-column chart showing whether time on the application is spread across everyone or concentrated on a few people.

Beamy sorts users from the lightest to the heaviest, then splits them into ten equal groups. Column D1 is the 10% who spend the least, column D10 the 10% who spend the most. The height of each column is the average weekly time of that group.

The overall shape is what matters, not the values.

A sharp climb on the right: the application rests on a handful of intensive users. Talk to them before renegotiating licences or planning a replacement.

A flat profile: the tool is evenly embedded in everyone's habits.

A mosaic where each rectangle is a department of your organization. Two menus, at the top right of the card, change what the mosaic tells you.

The size of a rectangle is the number of people using the application in that department over the past 90 days. That size never changes: it does not follow the period you pick at the top of the sheet.

The colour, on the other hand, depends on the left menu. You pick the measure that colours the rectangles: organization share, weekly time, or share of highly engaged users.

The right menu changes the organizational level. You move from top-level departments down to their sub-departments, and the mosaic redraws at that level.

Clicking a rectangle takes you to the detail of that department.

Departments worth less than 1% of the total are grouped into a single grey rectangle labelled « Other ». Grey also means that no value is available to colour the rectangle.

A large pale rectangle: many people, shallow usage.

A small dark rectangle: a pocket of intensive usage that a plain headcount ranking would miss.

A single dark rectangle in an otherwise uniformly pale mosaic: read the note below before concluding that the rest of the company does not use the application.

A column chart showing, period after period, who arrives and who leaves.

Each column covers 30 days. A menu at the top of the card switches to weekly columns if you are following a rollout closely.

Four groups share each column. Recurring users were already there last period. New users are discovering the application. Recovered users had not touched it for the previous 30 days and came back. Lost users were there the period before and stopped.

Lost users are drawn below the line, in negative, so you can see at a glance whether arrivals offset departures.

Below the chart, Beamy sums up in one sentence what the period is telling you.

Lost users growing period after period while new users stay flat: usage is draining, even if the headline figure still looks healthy.

A wave of new users usually corresponds to a rollout or a group of joiners.

Many recovered users, period after period: the application serves in bursts, for a monthly deadline or a one-off case, rather than every day.

A single chart where a menu lets you pick which of the three measures of attachment to the application you want to follow over time.

Stickiness: do people come back every day, or only now and then during the month. Beamy compares attendance on an average day with attendance over the whole month. At 100%, everyone who uses the application during the month uses it every day. At 25%, the average person is there about one day in four.

30-day retention: among the people who just discovered the application, the share still using it the following month. This figure only concerns newcomers, not all users.

Transversality: whether the application is used across the company or concentrated in one department. It is the same score as in the Governance tab, but followed month after month instead of frozen on one value.

A second menu sets the time step, monthly or weekly. Retention is the exception: it reads monthly only, and the weekly choice disappears when you select it.

Stickiness falling while the number of users rises: the application is recruiting, but the newcomers are not really adopting it.

Transversality rising: usage is spilling out of its original department. That is often the moment to decide whether the application becomes a standard or should stay contained.

How much this application matters to the company's work, and what would stop if it disappeared.

Beamy looks at three things:

The score comes with an impact level, from strongest to weakest: Mission Critical, Process Critical, Productivity Critical, Medium, then Not/Low.

A vital but rarely used application, a payroll tool for instance, naturally comes out low until someone has been asked. That is exactly what the business criticality campaign corrects.

A score telling you whether the application is spread across the organization or confined to one place, with a Local or Global chip.

Four elements make it up:

The 50% mark is the only boundary that matters. Below it, usage is local. Above it, transversal.

Do not try to interpret the gap between 35% and 42%. Compare applications with each other inside one scope, and use the 50% mark as your reference.