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Key Drivers Widget (EX)

What's on This Page:

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.

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.

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.

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

Specifying Field Bounds

You can specify field bounds when your metric is set to either average or top / bottom box. Depending on the selected metric, the setup is different.

If you would like to specify the upper and lower absolute limits of a field value (so the widget knows how to make its calculations), you can specify the field bounds for any potential driver that you add to your widget if the metric is average. You will click on the name of the potential driver, check the box for Specify Field Bounds, and then set your field minimum and field maximum for the selected driver. The purpose is to allow the bounds to be greater in both directions than what is observed in your response data.

Example: For example, you may have a multiple choice question where respondents can select choices 1-10, but only choices 2-7 have been selected thus far. If you’d still like to make your calculation based on the highest possible choice, you can do so by specifying your minimum and maximum field bounds as 0 and 10, respectively.

If you would like to specify the upper and lower absolute limits of a field value and the metric is top / bottom box, you can do so by specifying the box range. You will click on the name of the potential driver and then move the sliders for the Box Range to set your field minimum and field maximum for the selected driver.

Qtip: The values come from your selected field’s recode values.

Performance Axis

The performance axis refers to the x-axis of the key drivers widget. This axis can be renamed by typing your desired name in the Label text box.

The Metric determines how the key drivers are calculated. See the Interpretation section for more.

Lastly, you can determine the Threshold Type, which will adjust the vertical line along the x-axis:

Static: Determine where the vertical threshold line will lie on the x-axis. Moving the Threshold Marker allows you to decide the point at which a score changes from performing well to performing poorly.
Dynamic: The threshold line will automatically be set to the median values of the drivers being pulled into the widget.
Qtip: Customer satisfaction data is often driven by the data collected, not hardcoded standards. In cases where there are no industry standards, this option can be favorable.

Importance Axis

The importance axis refers to the y-axis of the key drivers widget. This axis can be renamed by typing your desired name in the Label text box.

Here, you can determine the Threshold Type, which will adjust the horizontal line along the y-axis:

Static: Determine where the vertical threshold line will lie on the y-axis. Moving the Threshold Marker (not pictured) allows you to decide the point at which a score changes from performing well to performing poorly.
Dynamic: The threshold line will automatically be set to the median values of the drivers being pulled into the widget.
Qtip: Customer satisfaction data is often driven by the data collected, not hardcoded standards. In cases where there are no industry standards, this option can be favorable.

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.

If you don’t want to display the legend in the widget, you can deselect Show Legend.

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.

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

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

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.

Select Scale Data Points by Sample Size to adjust the size of each driver circle relative to the other driver circles’ sample sizes. The larger the circle, the larger the sample size.

Show number of responses for each data value in tooltip ensures that when someone hovers over a data point, a tooltip will show them the performance, importance, and sample size for that data point.

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, and depending on whether you selected average or top / bottom box for your metric, is either dependent on the average score or the top / bottom boxes of scores. Normalizing makes it possible to compare potential drivers with different scales. The percentage for average is calculated by taking the value for the outcome metric’s potential driver and dividing it by the maximum possible value 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 percentage for top / bottom box is calculated by taking the value for the outcome metric’s potential driver and dividing it by 100.

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.
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.
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.
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.