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Time-Based Variance

Important

Time-Based Variance app updated in Arria for Qlik Sense 3.3.0

After upgrading to Arria for Qlik Sense 3.3.0, you can no longer reconfigure existing Time-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.

arria-apps-update-time-based-variance.png

See NLG Apps optimizations for further guidance.

About the narrative

Details covered in the analysis

The length of the narrative and the insights it includes depend on the number of dimensions selected and 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: Quarter-over-quarter analysis of Profit by Country, Segment, and Product

The narrative includes:

  • A summary of the overall variance in Profit between the two quarters and the most significant drivers and offsets that contributed to it by Country.

    arria-apps-time-based-variance-d1.png
    • For each Country: the variance in Profit and the drivers and offsets that contributed to it by Segment.

      arria-apps-time-based-variance-d2.png
      • For each Segment: the variance in Profit and the drivers and offsets that contributed to it by Product.

        arria-apps-time-based-variance-d3.png

        Rises from zero and falls to zero are also called out in the narrative, as shown above.

 

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 field names and formats for details.

In addition, each app has specific data requirements:

Dimensions and measures

The requirements for dimensions and measures are:

Minimum

Maximum

One measure and one time dimension*.

One measure, four time dimensions*, and three additional dimensions.

*Time dimension requirements for each analysis period:

Analysis period

Required fields

Required fields for Period-to-date analysis

Month

DateorYear + Month

DateorYear + Month + Day

Quarter

DateorYear + Quarter

DateorYear + Quarter + Month + Day

Year

DateorYear

DateorYear + Month + Day

Aggregation and entity types

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

arria-apps-entity-aggregation-time-based-variance-qs.png

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.

arria-apps-narrative-length-summary.png

My key insights

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

arria-apps-my-key-insights.png

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.

arria-apps-drilldown-variance.png

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
arria-apps-narrative-length-number.png
  • 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
arria-apps-narrative-length-contribution.png
  • 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
arria-apps-narrative-length-arria.png
  • The list of dimension instances is sorted in descending order.

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

Use this option to select the period for comparison. The options are Month, Quarter, and Year.

Default: Month

 

Your selected data must contain the date fields required for the chosen period:

Analysis period

Required fields

Required fields for Period-to-date analysis

Month

DateorYear + Month

DateorYear + Month + Day

Quarter

DateorYear + Quarter

DateorYear + Quarter + Month + Day

Year

DateorYear

DateorYear + Month + Day

 

See also: Analyze period to date and Comparison.

Set this option to ON to compare the current period to date with a previous period of equivalent duration.

Default: ON

 

Example: Month-over-month analysis of Sales

Assume the following:

  • Today is April 16, 2022.

  • The dataset contains data from January 1, 2020 to today.

  • The Period option is set to Month.

  • The Comparison option is set to Latest vs. previous.

The table below shows the effect of the Analyze period to date option:

Analyze period to date

Behavior

ON

The sales total for April 01–16, 2022 is compared with the sales total for March 01–16, 2022

OFF

The sales total for April 01–16, 2022 is compared with the sales total for March 01–31, 2022

Note

If the latest period in your dataset is not the current period, this option has no effect.

 

See also: Period and Comparison.

Use this option to set the comparison criteria for your narrative:

  • Latest vs. previous

  • Latest vs. earliest

For example, you might compare the latest month with the previous month, or the latest month with the first month in your dataset.

Default: Latest vs. previous

 

Example: Month-over-month analysis of Sales

Assume the following:

  • Today is April 16, 2022.

  • The dataset contains data from January 1, 2020 to March 31, 2022.

  • The Period option is set to Month.

  • The Analyze period to date option is OFF.

 

The table below shows the effect of the Comparison field:

Comparison

Behavior

Latest vs. previous

The sales total for March 2022 is compared with the sales total for February 2022.

Latest vs. earliest

The sales total for March 2022 is compared with the sales total for January 2020.

 

See also: Period and Analyze period to date.

Examples: Time-Based Variance

Assume the Use color for variance values option is ON.

Increase in value is

Change

Example narrative

Good

Sales increased

Sales jumped by $3.2M from $1.6M to $4.8M (196%).

Sales remained the same

Sales remained stable at around $12.4M.

Sales decreased

Sales dropped by $1.3M from $2M to $724.9K (-63.6%).

Bad

Expenditure increased

Expenditure rose by $6.6M from $10.5M to $17.1M (63.4%).

Expenditure remained the same

Expenditure remained stable at around $17.1M.

Expenditure decreased

Expenditure fell by $61.5K from $688.4K to $626.9K (-8.94%).

Neutral

Personnel increased

Personnel increased from $1.5M to $3M (100%).

Personnel remained the same

Personnel remained stable at around $1.5M.

Personnel decreased

Personnel decreased from $3M to $1.5M (-50%).

 

See also: Show variance values in color.

 

Top: Narrative Options

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 Increase in value is option, which controls which outcomes are considered positive and negative.

Note

The Show variance values in color option has no effect when Increase in value is set to Neutral.

 

Examples: Time-Based Variance

Assume the Use color for variance values option is ON.

Increase in value is

Change

Example narrative

Good

Sales increased

Sales jumped by $3.2M from $1.6M to $4.8M (196%).

Sales remained the same

Sales remained stable at around $12.4M.

Sales decreased

Sales dropped by $1.3M from $2M to $724.9K (-63.6%).

Bad

Expenditure increased

Expenditure rose by $6.6M from $10.5M to $17.1M (63.4%).

Expenditure remained the same

Expenditure remained stable at around $17.1M.

Expenditure decreased

Expenditure fell by $61.5K from $688.4K to $626.9K (-8.94%).

 

See also: Increase in value is.

 

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