By Matt Harrington, BCBA · Behaviorist Book Club · Research-backed answers for behavior analysts
A staff preference assessment is a structured procedure adapted from behavior-analytic methodology to identify which workplace conditions and consequences an employee values most. Unlike a general satisfaction survey, which asks about current levels of happiness or contentment, a preference assessment identifies the specific stimuli — schedule flexibility, professional development opportunities, recognition formats, incentive types — that are most likely to function as reinforcers for a given individual. The format typically uses paired comparison or ranking methods to produce a preference hierarchy rather than a single composite score. This hierarchy can then be used to design individualized reinforcement systems tied to measurable performance targets, closing the loop between assessment and contingency design in a way that general satisfaction surveys rarely accomplish.
Begin by identifying the behaviors that most directly predict client outcomes and organizational quality. For RBTs, these typically include procedural fidelity on active treatment protocols, accuracy and timeliness of data collection, completion rates for session notes, and supervisor ratings on observable skills during behavioral skills training. For BCBAs, relevant metrics include fidelity probe completion, supervisee skill acquisition rates, assessment turnaround times, and client progress ratios. Each metric should be defined in observable, measurable terms with explicit criteria for what constitutes acceptable, competent, and exemplary performance. Review these criteria with staff before implementation, collect baseline data, and revise definitions if early data reveals that the metric is not capturing what you intended. Transparency and collaborative definition reduce the likelihood that staff experience the system as punitive or arbitrary.
This concern draws on cognitive evaluation theory and the overjustification hypothesis from social psychology, which suggest that adding extrinsic rewards to intrinsically motivated behavior can undermine motivation. The behavior-analytic perspective challenges this framing: the distinction between intrinsic and extrinsic motivation does not map cleanly onto operant principles, and the research base on OBM shows consistent positive effects of contingent reinforcement on workplace performance. The risks are more practical than theoretical: poorly designed systems that deliver reinforcement non-contingently, set unachievable response requirements, or use coercive contingencies can damage morale and undermine trust. The safeguard is careful system design — ensure that targets are achievable, that reinforcers are valued, and that the system is presented as a tool for recognition rather than surveillance.
Performance profiles that vary across dimensions are common and should be addressed through individualized feedback and goal-setting rather than a single organizational benchmark. A staff member who demonstrates strong procedural fidelity but struggles with session note timeliness needs a different intervention than one who completes documentation reliably but whose fidelity data is declining. Use the preference assessment data to identify consequences that are likely to be effective for that individual, then establish a specific, time-bound goal for the area needing improvement with a clear reinforcement contingency attached. Avoid the common error of averaging across metrics to produce a single performance score, which can mask clinically important variation and leads to undifferentiated feedback that is too vague to change behavior.
Corrective feedback is an essential component of any performance management system and should not be displaced by a focus on reinforcement. Effective corrective feedback in OBM follows several principles: it is delivered soon after the behavior occurs, it specifies the observed behavior and the desired alternative, it is delivered privately when possible, and it is followed by an opportunity to practice the corrected behavior. Leaders who rely exclusively on positive reinforcement without addressing performance deficits are failing a basic supervisory obligation. BACB Ethics Code 4.07 requires honest and accurate feedback. A balanced feedback culture delivers both recognition for performance that meets criteria and specific, constructive correction when it does not.
Identify the leading indicators that predict caseload quality and staff sustainability before a crisis emerges. Useful metrics include average sessions per week per RBT, supervisor-to-supervisee contact hours, days elapsed between client assessment and plan implementation, and turnover rates by role and tenure. Set threshold values for each metric that represent acceptable ranges, and build a review cadence — monthly or quarterly — at which you examine whether metrics are within range. When a metric falls outside its threshold, treat that as a signal to investigate root causes before making changes. Data-driven staffing decisions also require tracking outcomes after policy changes to evaluate whether the intervention produced the expected effect, using the same logic you would apply to any behavior change program.
Monetary incentives are legitimate and often highly effective reinforcers for staff behavior. The relevant considerations are practical and ethical rather than principled objections to money as a reinforcer. Practically, monetary bonuses or salary adjustments are among the most logistically complex reinforcers to deliver contingently and quickly, since most organizations have payroll cycles that introduce delays between behavior and consequence. These delays reduce the reinforcement value relative to more immediate consequences. Ethically, monetary incentive systems must be transparent, equitable, and must not create pressure that compromises clinical judgment or encourages staff to inflate performance data. Ideally, monetary and non-monetary reinforcers are used in combination, with non-monetary consequences providing the more frequent, immediate reinforcement and monetary incentives marking significant milestone achievement.
Resistance to performance measurement systems typically reflects past experiences with surveillance, punitive evaluation, or arbitrary criteria. Introduce the system by emphasizing the benefit to staff: clear expectations reduce ambiguity and protect employees from arbitrary judgment, and preference-based reinforcement means that good performance leads to consequences that matter to the individual. Involve staff in defining performance metrics to increase buy-in and improve the ecological validity of the measures. Establish a trial period with an explicit review point at which you will examine whether the system is working as intended and make adjustments based on staff feedback and data. Frame the system as a tool for recognizing performance, not catching problems, and ensure that early uses of the system are predominantly reinforcement-focused to build a positive history with the procedure.
The BACB requires BCBAs providing supervised fieldwork to deliver structured, documented supervision that includes direct observation, performance feedback, and skill-building activities. An OBM-based leadership model is directly compatible with these requirements and strengthens supervisory practice in several ways. Preference assessments with supervisees can increase the likelihood that supervisees find the supervision experience reinforcing, reducing the escape and avoidance behaviors that can undermine supervisory relationships. Metrics-based feedback provides the documentation trail that BACB requirements expect. And the habit of making data-based decisions transfers to supervisory case review, supporting more rigorous and defensible clinical decision-making at the supervisee level.
The most common implementation failure is operationalizing targets without connecting them to consequences — collecting data on staff performance but never establishing explicit contingencies that use that data. A second common error is implementing a uniform reinforcement system without accounting for individual preference variation, resulting in a system that functions as a reinforcer for some employees and is neutral or aversive for others. Third, leaders frequently set performance targets without establishing baselines, making it impossible to evaluate whether the system is producing change or to calibrate targets appropriately for staff at different skill levels. Finally, many systems fail because data is reviewed too infrequently — quarterly reviews cannot provide the timely feedback that behavior change requires. Monthly or bi-weekly data reviews tied to individual feedback sessions produce substantially better outcomes.
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All behavior-analytic intervention is individualized. The information on this page is for educational purposes and does not constitute clinical advice. Treatment decisions should be informed by the best available published research, individualized assessment, and obtained with the informed consent of the client or their legal guardian. Behavior analysts are responsible for practicing within the boundaries of their competence and adhering to the BACB Ethics Code for Behavior Analysts.