Create a custom dashboard in Advanced Analytics

Custom dashboards let you build your own views of your Robin data. Show the metrics your organization cares about, arranged the way you want them. Custom dashboards use the same data as Robin's pre-built dashboards.

Follow the steps below to go from an empty dashboard to your first chart. You do not need experience with reporting tools.

What you can build

A custom dashboard holds as many charts, tables, and numbers as you want, across as many pages as you need. You choose which Robin data tables to pull from, how to filter them, and how to display the result.

• Combine desk, meeting room, presence, and custom resource data in one place
• Build any of 17 chart types, plus tables and pivot tables
• Add filters your viewers can change themselves, such as a building picker or date range
• Join two tables together, for example employee records with office attendance
• Keep a dashboard private, or share it with your team
• Schedule it to arrive by email on a recurring basis

For the full list of tables and fields, see Robin's Data Dictionary for Advanced Analytics. Read it before you build. It explains what each table counts.

Decide what to build first

The most common mistake is to open an empty dashboard and drag fields around. Answer these 3 questions first, and the build takes minutes, not hours.

1. What question are you answering?

Write it as a sentence someone would ask. "How full are our meeting rooms during business hours?" is a question you can build. "Room data" is not.

2. What is the denominator?

Any percentage needs a denominator, and your choice changes the answer. "Desk utilization" could mean bookings divided by all desks, or by only bookable desks, or by desks in open buildings. Each gives a very different number from the same data.

Decide which you mean before you build. Then write it in the description, so nobody has to guess later.

3. Who reads it?

An executive summary and a facilities working document are different dashboards. If you start to build both at once, build 2 dashboards.

Create your dashboard

You can start in 2 ways, and they are not the same.

Start with Save as if you can. It is usually faster to copy a pre-built dashboard and remove what you do not need than to build from nothing. Your copy keeps the filters and formatting that already work.

Both ways open the same window.

• My documents is private. Only you can see it.
• Shared is visible to others in your organization with analytics access.

Check this before you select Save. My documents is selected by default. If you build for your leadership team and leave it in My documents, nobody else can open it. Robin does not warn you.

Find your way around

The toolbar in the middle is how you add things: Data, Charts, Controls, UI, Layout.

The panel on the right shows settings for whatever is selected. With nothing selected, it shows settings for the page.

The bar along the bottom holds your pages. Add a page with the plus button. On the right is the Publish button, which is more important than it looks. See Publish before you share.

Set up your data page

Do this before you build a chart. It takes a few minutes. It keeps your dashboard easy to manage, so you can still change it later.

Load each Robin table you need onto one page, once. Then build every chart from those loaded tables. Do not go back to the source each time.

Why it matters

• One place to change things. Filter your data page to the last 90 days and every chart built from it follows. Otherwise, you edit the same filter on 8 separate charts.
• Your numbers agree with each other. Charts built from one table cannot drift apart. Charts built separately from the same source do drift apart, and you do not notice until somebody adds up your bars.
• Changes flow downward. Add a calculation to your data page table, and everything built from it can use it right away.

Step 1: Add a page and name it Data

Select the plus button in the bottom bar. To rename it, select the caret on its tab and choose Rename.

Step 2: Add a table

On your Data page, select Data in the toolbar, then Table.

The Select source window opens on the Suggested tab, which is empty the first time. This is expected. The tab lists sources you have used before.

Go to:

Data sources > Workspaces > Prebuilt > Datasets

Step 3: Open the table, then select the item in it

When you select a table name here, Robin does not add it. It opens the table, which contains one item with the same name. Select that item to add it.

If you selected a table and nothing seemed to happen, look for the matching name and select it.

Your table loads onto the page.

Repeat for each table your dashboard needs.

Step 4: Hide the page

Select the caret on the Data page's tab and choose Hide page. While you edit, a hidden page shows a crossed-out eye on its tab. Viewers do not see the page at all.

Know these 4 things about hidden pages:

• It is not a security control. The data is still in the dashboard. Hiding tidies the view. It does not restrict access.
• Anyone who can edit the dashboard still sees hidden pages.
• At least 1 page must stay visible.
• If someone copies your dashboard with Save as, every hidden page becomes visible in their copy.

Add pages and components

With your data page in place, everything else you build is a component on a visible page. Add pages and components, and point them at your data.

Add a page

Select the plus button in the bottom bar. To rename it, select the caret on its tab and choose Rename.

Add a page for these 2 reasons:

• Length. A page that scrolls past about 2 screens is easier to read as 2 pages.
• Theme. When several components answer related questions, give them their own page. A page each for desks, meeting rooms and attendance reads better than one page with all 3. Readers can go straight to the part they care about.

Add a component

The toolbar has 5 buttons. Each opens a menu of component types:

Point it at your data page

A word on the word "tab". Your dashboard has pages, shown as tabs along the bottom: your hidden Data page and one or more visible pages. Elements is not one of those. It is a tab in the Select source pop-up, next to Suggested and Data sources. You see it only while you choose where a new component gets its data.

Build your charts on a visible page. Each time you add one, point it at the table on your Data page. Do not go back to Datasets.

1. Go to your visible page.
2. Add the element you want, from Data or Charts.
3. In the Select source pop-up, select the Elements tab, next to Suggested and Data sources.
4. Elements lists what already exists in this dashboard, grouped by page. Open Data and pick your table.

Each entry has a Preview option. Use it to confirm you have the right table before you choose it.

This is the whole point of the data page. When you choose from Elements, Robin links your new chart to that table, not to the original dataset. Sigma calls the result a child element: the table is the parent, your chart is the child, and changes to the parent flow down.

If you go back to Datasets for every chart, each chart gets its own filters and its own numbers. Nobody can safely change that dashboard later.

If you build on the data page, move the chart, do not copy it

When you hover over a table, you see a plus icon labeled Create child element. It builds a chart from that table on the same page. You can work this way, including on your data page.

What matters is how you put the finished chart on a visible page.

To move a component: hover over it, open the more menu (three dots), choose Move to, and pick the destination page.

Either build the chart on the visible page and choose its source from the Elements tab, or build it on the data page and move it. Both leave you with one table feeding everything. Only copying breaks that, and it gives no warning.

Add filters people can use

Filters come from the Controls button on the toolbar. When viewers can narrow the dashboard themselves, they ask you for far fewer one-off reports.

There are 16 types, in 5 groups.

Top N is often overlooked. It trims a chart to the few largest categories. This helps any chart with a long tail, especially pie and donut charts.

To set up a filter:

1. Add the filter to the page and select it. Then select the "Properties" tab on the right.
2. Choose the Value source. This is the dashboard that contains the column for your filter.
3. Select "Source column", and select the column to apply to the filter.

   

4. Go to the "Targets" tab and select the components to apply the filter to. You choose them by hand, because you may not want the filter on some components.

   

Put the same filter on more than one page

Here, the obvious action is the wrong one. If you copy or duplicate a filter onto another page, you get a second, separate filter. A viewer sets one, moves to the other page and finds the other filter still at its default. The 2 pages then disagree, and the viewer trusts neither.

Use Create a synced copy instead:

1. Hover over the filter.
2. Open the more menu (three dots).
3. Choose Create a synced copy.
4. Use Move to to send it to the page you want.

Synced copies act as one filter. Change the value on any of them, and every copy updates, along with everything they filter. There is no original and no hierarchy, so if you delete one, the rest stay.

Build the chart on the page where you want it, and pick its source from the Elements tab. That is the only route that leaves you with one table feeding everything.

Choose the right chart

Decide what shape your answer has, then pick from this table. The next section has the steps for each one.

If your answer is not one of those, the question usually needs narrowing before you pick a chart.

The rest of the chart types

The eight above cover almost every workplace question. Robin offers eleven more, listed here so you know they exist and what they are for. Sigma's documentation covers each in detail.

Charts to be careful with

• Pie and donut stop working past about five categories. Either switch to a sorted bar chart, or cut the list down: add a filter to the component, change its type to Top N, and show only the largest few.
• Gauge needs a real target. Inventing one to fill the dial is worse than showing a plain number.
• Stacked area becomes unreadable past three series. Use a line chart.
• Treemap is marked Beta. Avoid it for anything other people rely on.
• Maps only earn their space across many cities. For one campus, a bar chart by building says more.

Build a heatmap

There is no heatmap chart type, but Robin's own dashboards use the heatmap look. "Expected occupancy next 7 days" on Desk Insights is a pivot table with conditional formatting. To build it, see Pivot table below.

Build each visualization

Each of these starts the same way and uses the same kind of slots. The first one is slow, and the rest go fast.

The pattern. Add the component, choose your source from the Elements tab of the Select source pop-up, then fill its properties in the panel on the right. You do most of the work with 2 buttons:

After you add a field, its dropdown gives you Set aggregate to switch between sum, average and count, Truncate date to roll a timestamp up to day, week or month, and Format to control how it displays.

The components below go roughly from easiest to hardest.

Table

The simplest component. Use it when somebody wants to see the records, not a summary.

1. Add the component from the toolbar, then in the Select source pop-up select the Elements tab and choose the table on your data page.
2. Use the Columns list to add or remove fields.
3. Select a column heading dropdown to sort, or to hide the column.
4. To summarize instead of listing, add a field to Groupings and the table collapses into groups with subtotals.

Tables are a good fallback. If your audience does not understand a chart, a well-sorted table often works better than a bad chart.

KPI

One large number. Use it for the headline figure at the top of a dashboard.

1. Add the component from the toolbar, then in the Select source window select the Elements tab and choose the table on your data page.
2. In Value, select + Add calculation and choose the field you want to measure.
3. Open that field's dropdown and use Set aggregate to pick sum, average, or count.
4. Optionally, in Timeline, select + Add column and choose a date field to draw a trend line under the number.

A KPI with no timeframe on it invites the question "since when?". Either add a timeline or say the period in the title.

Bar

Compares a measure across categories. It is the safest default when you are not sure what to use.

1. Add the component from the toolbar, then in the Select source window select the Elements tab and choose the table on your data page.
2. In X-axis, select + Add column and choose your category, such as Building.
3. In Y-axis, select + Add calculation and choose your measure. Row count is there if you just want to count records.
4. Sort by value using the column dropdown.
5. Under Chart type, switch between vertical and horizontal, and choose no stacking, stacked, or stacked 100%.

Sort by value, not alphabetically. A ranked bar chart answers "who is highest" at a glance. An alphabetical one makes the reader do the work. Switch to horizontal when category names are long.

Line

Shows change over time. Use it when your X axis is a date.

1. Add the component from the toolbar, then in the Select source window select the Elements tab and choose the table on your data page.
2. In X-axis, select + Add column and choose a date field.
3. Open its dropdown and use Truncate date to set the grain: day, week, or month.
4. In Y-axis, select + Add calculation and choose your measure.
5. To draw one line per category, set Color to By category and choose the field.

Truncating to week smooths out the weekday and weekend sawtooth that dominates most workplace data and hides the real trend.

Pivot table

Crosses 2 dimensions, with a measure in the cells. It is the most flexible component, and the basis for the heatmap look.

1. Add the component from the toolbar, then in the Select source window select the Elements tab and choose the table on your data page.
2. In Pivot rows, add the field you want down the side, such as Building. Add a second, such as Floor, to nest it underneath.
3. In Pivot columns, add the field you want across the top, usually a date.
4. In Values, add the measure that fills the cells.
5. For the heatmap look, go to the Format tab, choose Conditional formatting, select + Add rule, pick your column, and apply a color scale.

Conditional formatting also offers a single color or data bars. Color scale is what produces the graduated heatmap.

Combo

Shows bars and a line on one chart, with separate scales. It is the clearest way to show a count and a rate together.

1. Add the component from the toolbar, then in the Select source window select the Elements tab and choose the table on your data page.
2. Set the X-axis to your category or date, as with a bar chart.
3. In Y-axis, add your first measure. This becomes the bars.
4. Add a second measure to Y-axis. This becomes the line.
5. Use each series' dropdown to control which is drawn as bars and which as a line, and which axis it belongs to.

Bookings as bars with check-in rate as a line is the most convincing chart in workplace analytics. It shows reservations climbing while actual use stays flat.

Scatter

Shows one dot per item, placed by 2 measures. Use it to find outliers, not to report totals.

1. Add the component from the toolbar, then in the Select source window select the Elements tab and choose the table on your data page.
2. In X-axis, add your first measure with + Add calculation.
3. In Y-axis, add your second measure.
4. In Color or the grouping property, add the field that defines one dot, such as Space.

Room capacity on one axis and average attendees on the other, one dot per room, is how you find four-person meetings booked into twenty-person rooms. The dots far below the diagonal are your oversized rooms.showing all of its property slots.

Donut or Pie

Shows parts of a whole. Use it only when you have a few categories and the split is the point.

1. Add the component from the toolbar, then in the Select source window select the Elements tab and choose the table on your data page.
2. In the category property, select + Add column and choose the field to split by.
3. In the value property, select + Add calculation and choose your measure, or Row count.

Past about five slices this becomes unreadable. If the legend is hard to read, rebuild it as a sorted bar chart.

Write a description for every element

Every chart and number has a description field. Use it. People question a percentage with no explanation, and answering takes longer than writing the sentence.

Say what the number counts, over what period, and what is left out. Write it for someone who has never seen the underlying data.

Publish before you share

Robin saves your edits automatically, but as a draft. A draft is visible to you and anyone else who can edit the dashboard.

Select Publish, at the bottom right, to send your work to everyone you shared it with.

If you do not publish, your team sees something other than what you built. Building a dashboard and publishing it are 2 separate actions.

Robin keeps a version history of everything you publish. If a change does not work, you can go back to an earlier version.

A checklist before you share

• Your tables are on a hidden data page, and every chart takes its source from the Elements tab rather than from Datasets
• Every number has a description saying what it counts
• You know the denominator of every percentage, and it is written down
• Bar charts are sorted by value, not alphabetically
• Your date range does not end mid-week or mid-month, which makes the last point look like a collapse
• No table is exposing meeting titles, personal email addresses, or anything else your viewers should not see
• The dashboard is in Shared, not My documents, if other people need it
• You selected Publish
• You opened it as a viewer would and checked it looks the way you expect

Worked example: average room booking per open hour

This example builds one number from start to finish. The same pattern works for anything else you build.

The question: during the hours our offices are open, how much of each hour is a meeting room actually reserved?

The data: Hourly Space Utilization has one row per room per hour, and a Minutes Booked field between 0 and 60. So the average of Minutes Booked across open hours answers the question directly. A result of 25 means the average room is booked 25 minutes out of every open hour.

Step 1: Filter your data page to open hours

On your Data page, select the Hourly Space Utilization table and add a filter on Office Open, set to true.

This step matters most. Every room has 24 rows per day, including 3 a.m. If you leave the closed hours in, you average across a day that is roughly three times too long. A room booked 25 minutes per open hour then shows about 8. Because you filter the data page, every chart you build afterward uses the filter.

Also filter out disabled rooms, which still generate rows: add a filter on Space Disabled Time and keep only rows where it is empty.

Step 2: Add the KPI

Go to your visible page. Select Charts, then KPI. In the Select source window, select the Elements tab and choose the Hourly Space Utilization table from your Data page.

Step 3: Set the value

In the Value property on the right, select + Add calculation and choose Minutes Booked.

Sigma aggregates it automatically, and the default is a sum. A sum of minutes across millions of rows means nothing, so change it: hover over the column name, select the dropdown arrow, choose Set aggregate, and pick Average.

You should now see a number between 0 and 60.

Step 4: Check that the number makes sense

Check whether the number makes sense before you format it. A result near 60 means every room is booked solid, which is almost certainly a filter problem. A result near 0 means your Office Open filter did not apply, or you are averaging over the wrong rows.

Cross-check it against Space Insights. If your custom number and Robin's pre-built number disagree, they use different filters. Find out why before anyone else sees it.

Step 5: Add a trend

In the Timeline property, select + Add column and choose Time Local. The KPI now shows the latest period with a trend line behind it.

Use Time Local, not Date. Time Local is the hour in the building's own time zone, so a dashboard covering several regions still lines up.

Step 6: Name it and describe it

Give it a title someone outside your team would understand. "Average minutes booked per open hour" is better than "Utilization."

Then write the description:

Average minutes a meeting room was reserved during each hour the office was open. Out of 60. Excludes disabled rooms and hours the office was closed.

With this sentence, people do not need to ask you about the number later.

Step 7: Publish

Select Publish. Until you do, your team sees the dashboard without this on it.

Turning it into a percentage

Dividing by 60 turns the same number into a percentage of each open hour. That needs a calculation, not a built-in aggregate: in the Value property, choose + Add new column and do not pick a column. Write the formula there.

Decide which version you want before you build it. Both are valid, but they are not the same. The description must match the one you pick.

Learn more in the Sigma documentation

Robin's Custom Dashboards are built with Sigma Embedded Analytics. Use these links for more information:

• Custom dashboards (Workbooks) overview: use the table of contents on the left for more guides.
• Function index: browse the function index by category to learn about the types of functions you can use.