Hogan Method

Hogan Assessments

The Hogan Personality Inventory (HPI) describes normal, or bright-side personality – qualities that describe how we relate to others when we are at our best. Whether your goal is to find the right hire or develop stronger leaders, assessing normal personality gives you valuable insight into how people work, how they lead, and how successful they will be.

The Hogan Development Survey (HDS) describes the dark side of personality – qualities that emerge in times of increased strain and can disrupt relationships, damage reputations, and derail peoples’ chances of success. By assessing dark-side personality, you can recognize and mitigate performance risks before they become a problem.

When the pressure’s on, the line between strength and weakness isn’t always clear — drive becomes ruthless ambition, attention to detail becomes micromanaging. The dark side of personality derails careers and companies, but it doesn’t have to. Organizations around the world rely on the HDS to identify derailers that disrupt or interfere with effective performance.

The Motives, Values, Preferences Inventory (MVPI) describes personality from the inside – the core goals, values, drivers, and interests that determine what we desire and strive to attain. By assessing values, you can understand what motivates candidates to succeed, and in what type of position, job, and environment they will be the most productive. The MVPI consists of 10 primary scales, which are further divided into five subscales or item themes. The MVPI item themes provide additional interpretive power by categorizing individuals’ responses to the questions that compose each MVPI scale.

The Hogan Business Reasoning Inventory (HBRI) describes reasoning style – the ability to evaluate sets of data, make decisions, solve problems, and avoid repeating past mistakes. By assessing reasoning style, you can identify candidates’ problem-solving style, understand their capacity, and identify areas for development.

How You Think

The Hogan Business Reasoning Inventory (HBRI) describes reasoning style – the ability to evaluate sets of data, make decisions, solve problems, and avoid repeating past mistakes. By assessing reasoning style, you can identify candidates’ problem-solving style, understand their capacity, and identify areas for development.

The first measure of reasoning ability designed to predict real-world performance, the HBRI evaluates two kinds of problems solving:

Qualitative Reasoning

Qualitative reasoning involves working with data visualization, logic, and verbal information to solve problems.

Quantitative Reasoning

Quantitative reasoning involves working with mathematical and spatial information to solve problems.

More than IQ. Judgment is about making good decisions.

It’s clear that some people have better judgment than others. But what sets them apart? Although most people would say intelligence, that doesn’t account for the abundance of very smart people who continually make very bad decisions.

The first to combine cognitive ability, bright- and dark-side personality, and values, the Hogan Judgment assessment consists of two brief measures related to verbal and numerical reasoning, three independent scales that assess non-cognitive attributes that influence how an individual approaches decisions, and an assessment of post-decision reactions, including responses to negative feedback.

Information Processing

• Verbal Information vs. Numerical Information

Decision-Making Approaches

• Threat Avoidance vs. Reward Seeking
• Defensive vs. Cool-Headed
• Tactical Thinking vs. Strategic Thinking

Reactions to Feedback

• Denial vs. Acceptance
• Data-Driven Decisions vs. Intuitive Decisions
• Superficial Engagement vs. Genuine Engagement

Good judgment involves being willing to acknowledge and fix bad decisions, and learn from experience. Armed with this powerful knowledge, participants can improve their decision-making and judgment.

The Hogan Judgment Model represents a new and comprehensive approach to assessing judgment and decision-making styles. Unlike previous approaches, our model includes a critical component most models miss: how a leader reacts to feedback about his or her failed decisions. This means the decision-making process does not finish once a decision has been made – it is only completed after the leader evaluates the outcome, especially when the goal was not achieved. The underlying rationale is that to improve one’s judgment, one needs to learn from experience and receive negative feedback about one’s performance.

The goal of this model is not to categorize individuals as good or bad decision-makers because such categorizations hold no value for professional development. Everyone makes some good and some bad decisions. Instead, the goal of the model and accompanying report is to equip individuals with a greater understanding of their strengths and challenges in the pre- and post-decision processes, how well their typical decision-making tendencies fit specific roles and job requirements, and how to overcome specific biases that may impair judgment.