Target-Based Variance

Important

Target-Based Variance app updated in Arria for MicroStrategy 3.4.0

After upgrading to Arria for MicroStrategy 3.4.0, you can no longer reconfigure existing Target-Based Variance narratives. When you see the pop-up shown below, click Cancel to keep the existing narrative or Continue to overwrite it and configure a new narrative using the redesigned app.

See NLG Apps optimizations for further guidance.

Details covered in the analysis

The length of the narrative and the insights it includes depend on the configuration of the Narrative length option. Choose to generate a Summary that describes only the most significant insights derived from the dataset or configure a more detailed narrative using My key insights.

Example: Variance analysis of Actual Sales vs.Target Sales by Country, Segment, and Product

The narrative includes:

• A summary of the overall variance between Actual Sales and Target Sales, and the most significant drivers and offsets that contributed to it by Country.

• For each Country: the variance between Actual Sales and Target Sales, and the most significant drivers and offsets that contributed to it by Segment.

• For each Segment: the variance between Actual Sales and Target Sales, and the most significant drivers and offsets that contributed to it by Product.

Rises from zero and falls to zero are also called out in the narrative.

Tip

Set the order of dimension drilldown in Step 2 of the NLG Apps wizard.

Set the threshold for including drivers and offsets (dimension instances) and the order in which they're described (ascending or descending) using the Narrative length field in Step 3.

See Narrative options for further guidance on configuring the narrative.

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Data requirements

All NLG apps have the same data requirements for field names and formats. See Data requirements for details.

In addition, each app has specific data requirements:

If your data selection and configuration do not meet the requirements, the wizard disables the app and displays a warning:

The requirements for dimensions and measures are:

Minimum

Maximum

Two measures.

Two measures and three non-time dimensions*.

Note

Before you can sign in to your Arria account and use Arria for MicroStrategy, you must add at least one measure (metric) and one dimension (attribute) to the visualization.

You can remove measures and dimensions from individual NLG apps in Step 2 of the wizard.

*The Target-Based Variance app treats time dimensions in the same way as non-time dimensions. For example, select the Year, Country, and Quarter fields to drill down into each year in the data by country and quarter:

To analyze variance over time, use the Time-Based Variance app.

Not all combinations of aggregation and entity types are supported for measures. The Target-Based Variance app can analyze the following combinations:

Note

Entity types and other data attributes are set in Step 2 of the wizard.

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Narrative options

You can configure these narrative options in Step 3 of the NLG apps wizard:

You have two options to control the verbosity of the narrative and the priority of the insights found:

Summary

Choose Summary to generate a brief overview of the main insights.

My key insights

Choose My key insights to control which insights are included in the narrative.

For each level of drilldown, the Time-Based Variance and Target-Based Variance apps sort dimension instances in order of their contribution to the dimension's variance trend.

The Time-Based Variance example below shows part of an analysis of Profit by Country and Segment. The narrative describes the variance trend for each Country — here, Profit has increased in France — then highlights the drivers and offsets of this trend.

The drivers are the Segment dimension instances in which Profit in France increased (e.g. Departmental), and the offsets are instances in which Profit in France decreased (e.g. Brand Store). The app sorts all dimension instances (whether drivers or offsets) according to their contribution to the Profit increase in France.

At each level of drilldown, the My key insights option offers three ways to set the sort order for dimension instances and control how many instances are described in the narrative.

Number of instances
• Select the number of instances to include in the narrative.

Default: 2 instances

• Choose to sort dimension instances in ascending or descending order.

Default: Descending

Example

Assume the sort order is descending.

If you select 2 instances, the narrative only drills down into the two dimension instances that made the biggest contribution to the variance trend.

Contribution
• Select the threshold percentage for including dimension instances in the narrative.

Default: 50%

• Choose to sort dimension instances in ascending or descending order.

Default: Descending

Example

Assume that the threshold percentage is 50% and the sort order is descending.

In this case, the app sorts the dimension instances from highest to lowest in terms of contribution to the variance trend. The app then works through the list of dimension instances from top (highest contributor) to bottom (lowest contributor), summing the contributions until the total represents a 50% (or greater) contribution to the variance trend. If the app reaches the threshold by summing just the top two dimension instances, the narrative only drills down into those two dimension instances.

Let Arria decide
• The list of dimension instances is sorted in descending order.

• Arria's algorithms select the most significant insights to include in the narrative.

This option controls how the narrative describes the Actual measure equaling or exceeding the Target/Budget measure. Choose:

• Good when this is positive (e.g. Actual Sales vs. Target Sales).

• Bad when this is negative (e.g. Expenditure vs. Budget).

• Neutral when this is neither positive nor negative.

This option affects the narrative's language and tone. It also affects the color markup when the Show variance values in color option is ON — green for a change that is considered positive; red for a change that is considered negative.

Default: Good

Examples

Assume the Use color for variance values option is ON.

 Actual ≥ Target/Budget is Outcome Example narrative Good Actual Sales > Target Sales Actual Sales outperformed Target Sales by $12M (4.82%). Actual Sales = Target Sales Actual Sales exactly matched Target Sales at$56M. Actual Sales < Target Sales Actual Sales fell by $1.3M from$2M to $724.9K (-63.6%). Bad Expenditure > Budget Actual Expenses exceeded Target Expenses by$52.9K (1.2%). Expenditure = Budget Actual Expenses exactly matched Target Expenses at $1.2M. Expenditure < Budget Actual Expenses were below Target Expenses by$24.9K (-0.2%). Neutral Full-Time Personnel > Part-Time Personnel Full-Time Personnel were 900 or 20% higher than Part-Time Personnel. Full-Time Personnel = Part-Time Personnel Full-Time Personnel exactly matched Part-Time Personnel at 90,000. Full-Time Personnel < Part-Time Personnel Full-Time Personnel were 200 or 10% lower than Part-Time Personnel.

This option controls whether the narrative uses color markup to highlight positive and negative outcomes.

When this option is ON:

• Green highlights a positive change or outcome.

• Red highlights a negative change or outcome.

Default: ON

This option works with the Actual ≥ Target/Budget option, which controls which outcomes are considered positive and negative.

Note

The Show variance values in color option has no effect when Actual ≥ Target/Budget is set to Neutral.

Examples
 Actual ≥ Target/Budget is Outcome Example narrative Good Actual Sales > Target Sales Actual Sales outperformed Target Sales by $12M (4.82%). Actual Sales = Target Sales Actual Sales exactly matched Target Sales at$56M. Actual Sales < Target Sales Actual Sales fell by $1.3M from$2M to $724.9K (-63.6%). Bad Expenditure > Budget Actual Expenses exceeded Target Expenses by$52.9K (1.2%). Expenditure = Budget Actual Expenses exactly matched Target Expenses at $1.2M. Expenditure < Budget Actual Expenses were below Target Expenses by$24.9K (-0.2%).

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