The Core Drivers Diagnostict

Executive Summary

Scientific research has consistentlydemonstrated personality, defined as stable dispositions in how one thinks,feels, and behaves, to be a significant predictor of work-related outcomes. Itis now common practice for organizations to use personality assessment tools intheir talent management strategies, using such insights to shape how theyselect, develop, or promote employees, teams, and leaders. Personalityassessments are identified to be more scientifically valid in their predictionof job performance and critical work-outcomes over widely used methods such asinterviews, resumés, and education. Moreover, insights provided from thesetools are free from individual and group biases (Chamorro-Premuzic & Furnham, 2010).


While many organizations use personalityassessments in their talent management strategies, the most popular tools are confoundedby their length, ineffective use of technology, and inaccessible insights.Together, this creates an inadequate user experience where respondents find theprocess of taking the assessment cumbersome and often struggle to fullyunderstand their feedback report. In addition, these factors restrict anorganization’s ability to deploy personality assessments at scale. As a result,an organization-wide view of talent is often overlooked and undeveloped, resultingin leaders making ill-informed human capital decisions and leaving many withoutcritical feedback and awareness into their behavior. Overcoming theselimitations was the driving force behind the development of the Core DriversDiagnostic.


The Deeper Signals Core Drivers Diagnosticis a personality inventory based on the Five Factor Model — the mostscientifically validated and defensible model of personality. The Core DriversDiagnostic consists of 90 items, where respondents choose an adjective from apair that best describes themselves and respond to short behavioral statements.Each scale of the Core Drivers Diagnostic comprises of five facets or “SubDrivers”, empowering coaches and leaders with deep and nuanced talent insights.The diagnostic is administered on a modern, secure, and security-compliant technologyplatform (“The Deeper Signals Platform”[1]).Upon completion respondents are presented with an interactive and intuitivereport that describes their results and provides personalized development plansthrough a “Digital Coach”.


The Core Drivers Diagnostic was developedusing over 50,000 working adults, psychometrictechniques, and machine learning methods. This report describes thediagnostic’s psychometric properties. Specifically, the scales’ reliability,factor structure and intercorrelations, alongside construct (convergent &discriminant), concurrent, and criterion validity. Scores on the Core Drivers Diagnosticcorrelate with many popular psychometric constructs and inventories, including TheBig Five, Dark Triad, NEO PI-R, and the Hogan Personality Inventory, inaddition to employee engagement, counterproductive work behaviors and managerratings of job performance. The diagnostic was also tested for adverse impact,of which there is none. Moreover, the diagnostic does not discriminate betweenprotected groups.


The Core Drivers Diagnostic was designedfor working adults, in individual contributor, management, and leadershiproles. The tool can be used to inform talent management decisions, coaching,team development, learning and development, training, people analytics, and tosupport organizational change.


Assessment Characteristics

This chapter describes the keycharacteristics of the Core Drivers Diagnostic, specifically how the assessmentcan be used, intended audiences and an overview of the report insights. Thischapter has been created to help practitioners and stakeholders evaluate the assessmentand assess it suitability within their organizations.


Assessment Scope

The Core Drivers Diagnostic contains sixscales that are based on the Five Factor model of personality, the mostscientifically supported personality model (Chamorro-Premuzic & Furnham, 2010). While the next chapter describes the scales in more detail, thebelow provides an overview of the six dimensions:


●     Agreeableness: The tendency to be candid or considerate.

●     Conscientious: The tendency to be flexible or organized.

●     Drive: The tendency to be laid back or driven.

●     Extraversion: The tendency to be reserved or outgoing.

●     Openness: The tendency to be pragmatic or curious.

●     Emotional Stability: Thetendency to be passionate or stable.

In addition to the six dimension, 30 facetsor “Sub-Drivers” constitute each scale (five per dimension). This allows forgreater nuance and understanding around an individual’s dispositions. Tocomplete the diagnostic, users indicate the extent to which 30 behavioralstatements and 60 force-choice adjectives best describe themselves.


The Core Drivers Diagnostic sets itselfapart from other talent assessments with its short format which allows users tocomplete the diagnostic in less than ten minutes. In addition, the unique,conversational language improves accessibility and provides an engaging userexperience. More importantly, this unique experience is delivered withoutcompromising the scientific robustness of the tool. The Core Drivers Diagnosticis scientifically reliable, valid, and free of bias. It meets all industrystandards and predicts critical work behaviors and outcomes.


Users can access and complete theassessment on the Deeper Signals platform. This self-service platform featuresa modern user interface and is designed for mobile devices, while providing asafe, secure, and private online experience.


Compared to other commercial assessments,the Core Drivers can be deployed at scale, enabling organizations to supporttheir leaders and employees with deep, meaningful insights quickly andeffortlessly. Further, the assessment is powered by a robust analytics suitethat enables HR leaders to identify talent trends at the team andorganizational level.

Using the Core Drivers Diagnostic, organizationshave the unique opportunity to empower leaders, build strong teams, fuel innovation,and drive large-scale change through self-awareness.

[1] A full technical paper that describes the platform’sarchitecture and security is available upon request.

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