Overview of Reports
Reports show information about many Scorecard items, Initiative items, or Dataset records at once. They have formatting, grouping, sorting, filtering, and aggregating. In short, Spider Impact now has a full-featured report designer for all of the data it tracks. For example, you can choose to view all of the downward trending KPIs, all of the initiatives owned by a particular person, or aggregated data about every Canadian employee.
Creating a Report
To create a new report, click the “New Report” button in the Reports section.
Each report is for a single type of data. First, we’ll choose Scorecards.
You can choose between several pre-built reports like the Red KPIs report and Missing KPI Values report. These reports get you started with “canned” reports that you can configure.
Instead, we’ll build a report from scratch by choosing the Advanced Report Designer option on the bottom.
The Advanced Report Designer for scorecard items starts by showing the scorecard item name, owners, and three periods of data for all KPIs.
Let’s start a new report, and this time we’ll choose Initiatives. A new Initiatives report starts with showing the budget and schedule information for all non-archived initiative items.
The third type of report is Datasets.
A dataset report shows data from a single dataset, which we’ll choose next.
Dataset reports are a little different from Scorecard and Initiative reports because every dataset field is unique to each dataset. Because of this, dataset reports start blank.
Finally, users with the right permissions can choose SQL reports. This allows them to write SQL queries against a database that you have set up in Admin > Import Connections.
View and Edit Tabs
Regardless of whether you’re writing reports for Scorecards, Initiatives, or Datasets, the general flow is the same. The Reports Edit tab always shows the first three records so you can get a preview of what your report will look like.
When you switch to the View tab, you’ll see your entire report.
When you’re viewing a report, you can temporarily change the sorting by clicking on the column headers.
Adding and re-ordering columns
Select a report and click the edit tab
To add a new column, click the “Add” button where you want the new column to go.
This brings up a list of all available fields from which to create columns. Here you can see the placeholder where the new column will go, right before we click to add the “Data Type” field as a column.
Immediately after the new column is added, the “Add Column” tooltip stays open, and you can see a new placeholder column to the right of the new column. This allows you to add multiple columns quickly with a few clicks.
To change the order of columns, you can just drag and drop them to where you want them to be.
Most reports will contain at least one row filter. The idea here is that you’re choosing which scorecard items/initiative items/dataset records you want to show. In this example we’ve created a new scorecard item report, and there’s already a filter to only show KPIs. Let’s add a new filter by clicking the “add” button.
The default row filter is “Specific Scorecard Items” and we’ll use that here.
This allows you to manually choose which scorecard items you want to see. We’ll add the entire “Mobileworld Balanced Scorecard” and click Done.
Now we only see the two of the KPIs in the Mobileworld Balanced Scorecard.
To edit a filter, just click on it. This opens the same dialog we saw before, and this time we’ll choose to make this an OR filter.
Now we see all scorecard items that are either KPIs or in the Mobileworld balanced scorecard.
Setting column labels
To edit a column, just click on it. You’ll see the column that you’re going to edit highlighted, and it shows a tooltip with your editing options.
In this example we’ll click the Edit button, and we’ll choose “Set Column Label.”
This opens a dialog where you can choose to override the Default column label and type a value of your own. In this example we’re going to change the “Sale Price” label to “Value.”
Editing column data
Every report column gets its data from somewhere, and to edit what data is showing, choose “Set Data Source” from the Edit Column menu.
The default column type is Basic. This means the column is showing the value for a single field.
You can also choose to show a Calculated value in a column. Here we’ll change the Type to Calculated and we’ll click the “Set Equation” button.
In this example we’re building an equation that shows the value of the “Sales Price” field, but with an additional 7% sales tax added if the value of the Country field is “United States.”
Finally, it’s important to note that you can reach this “Set Data Source” menu when adding a new column. Most of the time you’ll want to choose a field from the list when adding a column. But, if you know your new column is going to be more complicated than that, you can just click the “More Options button that’s in the “Add Column” tooltip.
This shows the same “Set Data Source” menu, but this time it’s for a column that hasn’t been created yet.
Show values for
Sometimes when you click on a column, you’ll have a “Show Values For” dropdown. In this example we’ve clicked on a date column that’s showing data from the Sale Date field, and we’re currently showing “Every Sale Date”.
Here we’ve chosen to show values for the Quarterly calendar. The column now shows which quarter the sale happened in instead of the specific date.
You’ll see other options in the “Show Values For” dropdown depending on what data your column is showing. For example, our dataset has four ranges set up for the Sale Price field.
When we click on the column showing the Sale Price field, we can see that it defaults to “Every Sale Price”.
If we change “Show Values For” to “Every Sale Price Range”, we’ll see values that look like this.
To edit a column’s formatting, choose “Edit Formatting” from the Edit tooltip.
The Edit Formatting dialog gives you a preview of what your formatted data will look like. Here we’ve changed the font size to large, changed the color to dark, abbreviated the data, and aligned everything right.
You can choose to sort on any field in your report. The default sorting for scorecard and initiative reports is first by organization, and then by tree order. You can change this default sorting by clicking on a column and turning on “Sort using this field.”
You can then choose to sort that column ascending or descending.
You can group by a column by clicking on the column and turning on the Group switch.
This shows all unique values for that column as large group headers, and then lists all of the records with that value underneath. In this example we’ve grouped by the Sales Employee column, so each group is a different sales employee. The Edit tab only shows the first three groups, but switching to the View tab will show the full report.
You can create another level of grouping by selecting another column and turning on “Group Again”.
In this example the Sales Employees are also grouped by Sales Department.
Hiding individual records
Adding a group to your report opens the door to many new data presentation possibilities. The most powerful is the ability to turn off “Show Individual Records”. In this example, we’re grouping records by the Sales Employee column, and we’re showing columns for the Sale Date, Sale Price, and Sales Department.
When you turn off “Show Individual Records”, the report now only shows the groups. As you can see, the columns remain the same, but now they’re showing aggregated data for each group. Number columns like Sale Price are summed by default. The default aggregation type of Date and Text columns is counting the number of unique values.
Let’s say we want to show the Average sale price for a group instead of the Sum of all sale prices. To do this, just choose Set Data Source like we did before.
Now that we’re showing aggregated data, however, we have an Aggregation Type choice in this dialog. We’ll choose Average.
Once we click Done, we have a report showing the average sale price for each employee.
Finally, we’ll change the Sale Date aggregation type to “Latest Date”. Our finished report looks like this on the Edit Tab.
And like this on the View tab.
Column filters when hiding individual records
Once you’re hiding individual records and your report is showing aggregated data, you can start adding filters to your columns. In this example we’re going to choose “Set Data Source” for a Sale Price column.
We’ll leave the aggregation type as sum and click the “Add” button in the filters panel.
Next, we’ll create a filter to only include data from records where the sales country is Canada or Australia.
This is what our new column filter looks like.
When we click Done, we now have a column showing the sum of all sales in Australia and Canada for each employee.
Repeating columns for scorecards
You can create repeating columns for Scorecards, Initiatives, and Datasets reports, but they’re a little bit different for every report type. For Scorecards, values that change over time are always inside of a repeating column. Whenever you add a column like KPI Value or Goal, you’ll automatically see that field repeating by calendar period. As you can see in this example, it doesn’t make sense to show a KPI value without knowing what period that KPI value is for.
To edit repeating columns, just click on them. Just like when you select a column, selecting a repeating column header shows a tooltip. We’ll click the Edit button.
This opens the Edit Repeating Columns dialog. We’ll change the calendar to Quarterly, and we’ll choose a range of 4 periods.
When we click Done, we now see the KPI value being repeated for four quarters.
Repeating columns for initiatives
As we mentioned above, repeating columns work a little differently for every report type. Repeating columns for Initiatives are similar to repeating columns for Scorecards because there are values like Money Spent that change over time. Initiatives are different, however, because their repeating columns aren’t required and aren’t added by default. Whenever you have a column for a field that changes over time and it’s not repeating, the report will just show the latest value.
In this example we have a column showing the projected budget variance for every initiative item. The projected budget variance field does change over time, but because this column isn’t inside of a repeating column header, the report just shows the most up-to-date values for the projected budget variance. We do, however, see a “Repeat this column by calendar period” button.
When we click the button, we now have repeating columns showing how the projected budget variance has changed over time.
Repeating columns for datasets
You can only add repeating columns to dataset reports when individual records are turned off. That’s because we need to first aggregate dataset records for each group before we can disaggregate the data into repeating columns. Scorecard and Initiative reports don’t have this restriction because their repeating columns can show values that change over time.
In this example we’re grouping by Sales Employee and are hiding individual records. We now see a “Repeat this column by…” button when you click on any column other than the one you’re grouping by.
We’ll click the “Repeat this column by…” button and then choose to repeat by Country.
We now have a separate Sale Price column for every country.
Multiple blocks of repeating columns
You’re not limited to one range of repeating columns. In this example we’re going to add a new column outside of the first block of repeating columns.
We’ll choose to add another KPI Value column, and now we have two identical blocks of repeating columns.
Finally, we’ll edit each repeating column block to contain a single period, and we’ll drag and drop the blocks next to each other. Now we have a report showing the KPI value for the current month and the KPI value from the month one year ago.
Repeating columns again
Scorecard, Initiative, and Dataset reports can all repeat columns a second time when individual records are turned off. For Scorecard and Initiative reports, repeating again is almost always used when multiple organizations have the same initiative or scorecard items and you want to compare them across organizations. For datasets, repeating again is common with all field types.
To repeat again, click on the repeating column header to select it.
Then click “Repeat again by” and choose a field. Here we’ll repeat by Sales Department.
The result is a report with two levels of repeating columns, first by Sales Department and then by Country.
On the Edit tab there are all 0s for Corporate sales, but when you go to the View tab you can see that in this example employees either sell retail or corporate, never both.
Changing header order
To put the columns on top, just drag and drop them vertically.
Now the report first groups by column, showing the three periods for KPI Value and then the three periods for Goal.
Hiding repeating column headers
Some reports have only one column, for example KPI Value. Other reports have only one repeating value, for example a single calendar period. In these situations, you can choose to hide either the column or the repeating value header.
For example, here we’re showing the KPI Value for three months. The KPI Value isn’t adding a lot to the report in this situation, so we’ve dragged the column header to the top.
On the View tab the column header is no longer visible.
When you’re repeating again, you can even hide two levels of headers. In this example we’re showing data for a single field and for a single calendar period. We’ve chosen to hide all of the headers except the KPI name.
When you add a notes column to your report, there’s a “Set Note Display” option in the menu.
This allows you to choose not only the type of notes to show for your report, but also the information from each note you want to see.
A scorecard item’s weight can change over time, but it often doesn’t. If you add a Weight column to your report, it will show the most recent weight for that item.
If you add a Weight column inside of repeating calendar periods, it will show what the weight was at the end of the period. In the example, the “SEO Project Spend” KPI weight changes in August.