Would your employees recommend your company as a good place to work? Would they recommend purchasing your company’s goods and services? Smart companies convert the answers to those questions into an Employee Net Promoter Score (eNPS).
The score not only reveals a great deal about job satisfaction, employee engagement, and overall workforce sentiment, but it also prompts the question “Why?” The way to bring about meaningful change in your organization is to uncover the factors that make your employees answer those questions as they do. While the surveys help gauge overall sentiment, it can be hard to diagnose which reasons are the most important in predicting and thus affecting promoter score.
Given that all employees are promoters, passives, or detractors, which workplace factors motivate them? Using predictive models, a company can uncover and research the factors that most affect employee engagement and sentiment and affect eNPS.
The predictive model is made possible by connecting a database of the promoter score results, including reported reasons for the score, with databases containing other metrics about the employee. Running those features (reasons for the score) through an anonymized model draws out the reasons that best predict the score an employee will give. By studying those reasons, managers can focus on the factors that really matter, as opposed to just grouping by the most common response. The model also helps highlight issues that employees care about and the topics most likely to make them promoters or detractors.
With Alteryx, you can:
- Load anonymized NPS survey responses and blend that data with employee demographic data
- Segment employees based on department to uncover department-level NPS scores
- Use regression modeling to discover what factors currently impact low scores, and what changes can most improve future scores