Data Enrichments

Visier’s data services allow you to enrich your existing data with predictions and standardizations.

Visier provides out-of-the-box data enrichments. Data enrichments improve your analytics by adding predictive capabilities, transforming unstructured data into accessible structured analysis, and allowing you to make comparisons to industry benchmarks.

Data enrichment types:

Prediction: Forecasts of future events with advanced machine learning models.
Standardization: A set of standard industry values that are matched to your unique data values.

To view your data enrichments, open a project and navigate to Model > Data Enrichments.

Note: Configuration changes do not come into effect immediately. When making changes to data enrichment configurations, you must publish your changes to production and wait for the scheduled job to run. By default, the prediction and standardization jobs run weekly. If you want to see changes immediately, you can run a data enrichment job in the production project.

Predictions

Accurate predictions are the cornerstone of effective workforce analysis and planning. By forecasting how many employees are likely to leave, for instance, you'll be better able to plan for the right number of new employees to hire. Expect too little attrition, and you'll fall behind on hiring and workforce productivity will drop. Expect too much, and you'll waste money ramping up talent acquisition programs. Better predictions make it easier to match workforce supply with demand. Even a small increase in accuracy means significant savings, given that the workforce accounts for the biggest slice of the budget for most organizations.

Visier's predictive models will help you identify employees who are most likely to resign, should be considered for a promotion, or are most likely to internally change jobs. You can also validate and report on how close the number of actual exits, promotions, and internal moves were to the predicted values inside the application. This will help you increase the trust of your stakeholders by confirming exactly how accurate your past predictions were.

For more information, see Predictive Models.

Standardizations

Note:

To enable this feature, contact Visier Technical Support.

Standardizations match your unique data to well defined names and taxonomies. With standardizations, your unique data becomes accessible for structured analysis, and can be easily used to make comparisons to industry benchmarks. For more information, see Standardizations.

The standardizations and the objects they add are listed in the table below.

Standardization	Object Type
Employee Standardized Location	Visier Location (Dimension) Visier Location Match Score (Property)
Requisition Standardized Location	Visier Location (Dimension) Visier Location Match Score (Property)
Visier Employee Standardized Contract Type	Visier Contract Type (Dimension) Visier Contract Type Match Score (Property)
Visier Employee Standardized Employment Type	Visier Employment Type (Dimension) Visier Employment Type Match Score (Property)
Visier Employee Standardized Occupation	Visier Job Name (Dimension) ISCO (Property) Visier Occupation (Dimension) Visier Job Automation Index (Property) Visier Job Remote Index (Property) Visier Job Match Score (Property) Skills (Analytic Object)
Visier Requisition Standardized Occupation	Visier Job Name (Dimension) ISCO (Property) Visier Occupation (Dimension) Visier Job Automation Index (Property) Visier Job Remote Index (Property) Visier Job Match Score (Property) Skills (Analytic Object)

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