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Key Drivers Widget (EX)

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Qtip: This page describes functionality available to dashboards in Engagement, Lifecycle, and Ad Hoc Employee Research projects. For more details on each, see Types of Employee Experience Projects.

About Key Drivers Widgets

Let’s say that you’ve asked how employees rank their job satisfaction, in addition to asking them to rate their managers’ effectiveness. You want to see if these two are related, and if a rating of manager effectiveness drives job satisfaction. Using the Key Drivers widget in your dashboard allows you to see the correlation between one Outcome Metric field and one or more Potential Driver fields.

Example of a Key Driver plot

Field Type Compatibility

Only Number Sets, Numeric Values, and individual items from categories are compatible with the Key Drivers widget.

Widget Customization

For basic widget instructions and customization, visit the Widgets Overview support page. Continue reading for widget-specific customization.

Outcome Metric

The Outcome Metric is a measure of progress that is influenced by key drivers. For example, a company might be concerned about the pace at which their employees promote. The Outcome Metric in this case would be the timespan of promotion.

Key Driver Plot with widget editing pane opened to the right

Potential Drivers

Potential Drivers are performance based metrics that influence the Outcome Metric. For example, if a company’s Outcome Metric is timespan of promotion, Potential Drivers might include how the employees rate their sense of involvement with important decisions, their understanding of their roles in the company, and whether they feel they are given the right resources to do their work.

Dots on the Key Driver plot highlighted to indicate they match the potential drivers listed in the editing pane

As soon as you add Potential Drivers, the option to edit the Performance Axis, Importance Axis, Legend Values, and Display Options appear.

Performance Axis

The vertical line on a Key Plot is highlighted to show it is the Performance Axis referenced in the editing pane

  • Label: The Performance Axis can be renamed by typing your desired name here.
  • Metric: Select whether the metric should be Average or Top Box/Bottom Box.
  • Threshold Marker: Adjusting this number will move the vertical threshold line left or right. Moving the Threshold Marker allows you to decide the point at which an average score changes from performing well to performing poorly.

Importance Axis

Like the Performance Axis, you can rename the Importance Axis by typing the desired name in the Label text box. You can also adjust the Threshold Marker, which will move the horizontal threshold line up or down. Moving the Threshold Marker allows you to decide the point at which a driver becomes a reliable and accurate predictor of your Outcome Metric.

The horizontal line on a Key Plot is highlighted to show it is the Importance Axis referenced in the editing pane

Legend Values

Click on the color swatch to change the color of the driver circles for each quadrant. You can also select the default text and type in your own legend values.

The legend underneath the Key Driver Plot is indicated

Display Options

Select from the different Display Options to further customize the widget.

Select Show X Axis to display the Performance percentages along the bottom of the widget.

The Show X Axis setting is highlighted

Select Show Y Axis to display the Importance values along the left side of the widget.

The show Y Axis option is indicated.

Select Show Labels to show the labels next to the drivers within the widget.

The Show Labels option is indicated.

Select Scale Range Automatically to adjust minimum and maximum axis values automatically. This does not adjust your Threshold Markers. Rather, it serves to “zoom in” or “zoom out” to give you the best possible view of your key drivers.

The Scale Range Automatically option is indicated.

Select Show Legend to include a legend of the Key Drivers colors. Deselect this option to  hide the option.

Show Legend option last

Interpretation

The Y-axis, also called the Importance Axis, is a value between 0 and 1 that represents how strongly a given driver is correlated with the Outcome Metric. It is calculated by taking the absolute value of Pearson’s r, such that:

Importance = | r |

As the Importance value gets closer to 1, the relationship between the driver and outcome is understood to be stronger.

The X-axis, also called the Performance Axis, is a normalized scale. This means the value ranges from 0% to 100%. This axis is normalized because it is dependent on the average score. Normalizing makes it possible to compare Potential Drivers with different scales. This percentage is calculated by taking the average value for the Outcome Metric’s Potential Driver and dividing it by the maximum value selected by participants of the Potential Driver.

Example: Let’s say you ask respondents to answer a question on a scale from one to five. If the highest score a participant gives for this question is a four, then four will be used as the denominator when calculating the percentage on the Performance Axis.

The Key Drivers widget is divided into four quadrants:

  • Important and highly rated: These values fall in the top right quadrant and indicate drivers that play a large role in determining the Outcome Measure.  These drivers also have higher average scores. For example, “motivation” drives promotion in such a way that higher sense of motivation is related to faster rate of promotion.
    Top-right quadrant of Key Plot is highlighted
  • Important but poorly rated: These values fall in the top left quadrant and indicate drivers that play a large role in determining the Outcome Measure. However, these drivers have lower average scores. For example, an employee’s rating of “manager effectiveness” plays a big role in determining promotion in such a way that lower perceived manager effectiveness is related to slower rate of promotion. In this case, participants indicated that this company is not doing well in regards to maintaining effective management. This is an area of improvement for this company.
    Top-left quadrant of Key Plot is highlighted
  • Not important and poorly rated: These values fall in the bottom left quadrant and indicate drivers that are not important in determining the Outcome Measure. These drivers also have low average scores. For example, “resources” employees have on the job doesn’t drive promotion, but participants also indicated this company was not doing well in providing job resources. However, this company might not need to improve on this driver because it isn’t affecting their employees’ rate of promotion.
    Bottom-left quadrant of Key Plot is highlighted
  • Not important but highly rated: These values fall in the bottom right quadrant and indicate drivers that are not important in determining the Outcome Measure. These drivers also have a high average score. For example, “confidence in leadership” does not drive rate of promotion, but it was given high scores by participants. While one might argue that employees having confidence in company leadership is always a good thing, it does not influence rate of promotion.
    Bottom-right quadrant of Key Plot is highlighted

FAQs