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  • The Compelling Employer is a groundbreaking research initiative examining the employment-offer preferences of arts employees across genres and locations. ABA is using conjoint analysis (also known as trade-off analysis) to give arts leaders a much clearer picture of what employees want in a job, and what they are willing to trade off in order to get it. The result of conjoint analysis gives employers a map for deploying resources to create the most compelling employment offer possible using available resources.

  • Conjoint analysis is a form of statistical analysis that analyzes how individuals value different components of product offers. Particularly, this form of analysis can only be done through special modeling software, a technique that cannot be easily or cheaply done through typical regression or driver analyses. Organizations that deploy conjoint analysis in order to understand staff preferences about their employment offer can answer a whole range of questions that are difficult or impossible to assess accurately using other approaches. Particularly, conjoint analysis elucidates true preferences of respondents, forcing a series of trade-offs that separates out the “must haves” from the “nice to haves” and illuminates what is most critical to have in a compelling job value proposition.

    Conjoint analysis generates two kinds of quantitative outputs that are extremely useful to anyone trying to allocate scarce resources in order to create the most perceived value for employees:

    1. Importance Scores measure the relative importance that individuals place on different elements of the employment offer, making it possible to force-rank attributes of the value proposition and assess how much more individuals value certain attributes more than others.

    2. Utility Scores measure the usefulness to an individual of different quantities of a given element of the employment offer.

    Harvard Business Review provides a helpful in-depth overview of the technique, which you can read here.

  • We will not be collecting any individually identifiable data. All data will be collected anonymously and then will be grouped together to ensure confidentiality.

 

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