1. Objective data Subjective data Contextual data Productivity measures, absenteeism, tardiness, turnover, absenteeism OCBs (assisting others, loyalty, extra work/effort, volunteering), emotional labor, counterproductive behaviors (late arrivals, sabotage, gossiping) Performance ratings (e.g., supervisor, co- workers, self, subordinates, clients Criterion Domain

2. Objective Appraisal Data 1) Production Data (e.g., sales volume, units produced) When observation occurs (timing), and how data is collected Fairness and relevancy issue Potential limited variability Limitations regarding supervisory personnel 2) Personnel Data Absenteeism (excused versus unexcused) Tardiness Accidents (fault issue)

3. Years on job 1 2 3 4 5 6 7 8 Best predictor of performance Verbal Ability Aptitude Test scores Best predictor of performance Specific work methods Co-worker relations Dynamic Criteria (cont.) Use of Objective Data

4. Criteria Dimensionality Decision-makingCommunication Static --- Individual performance varies by performance criteria

5. Criteria Dimensionality (cont.) Individual --- Employees excel at different aspects of job performance Employee # 1Employee # 2 Production Client support & satisfaction Role prescriptions, organizational impact

6. Criteria Challenges Criterion unreliability --- Intrinsic (individual variations in performance) Extrinsic (equipment functioning, weather, supply chain, geographic region, information access) Recommended to always combine data across time and situations

7. Dynamic Criteria Productivity (Sales) by Year 2001 2002 2003 2004 2005 2006 2007 Individual variation in performance is often great across time More consistency is achieved by using an incentive system and when output is measured over a significant number of occurrences (and over a wide variety of measures) Use of Objective Data

8. Criteria Challenges (cont.) Observation --- Variation due to methods used, who observes Performance Dimensions --- Uni-dimensional vs. multidimensional criteria (Over-reliance on supervisor ratings of performance; 879/1506)

9. Objective dataSubjective data r =.39 Relevance --- Generally considered the most important issue Criteria Issues * Adequacy of production data for managerial personnel

10. Criteria Issues (cont.) Dimensionality --- Does the criteria differentiate between employees? Low variability (e.g., production line speed, process limitations) Contamination --- a)Error b) Biases (e.g., rating scales, group membership, knowledge of predictor scores, self-fulfilling prophecy)

11. To Combine or Not to Combine Criteria? Global criteria 3.0 GPA Separate, multiple criteria AACCAACC Is there a single, underlying dimension that “allows” combining separate criteria? Purposes of the data (e.g., a) for personnel decisions or b) feedback, understanding psychological and behavioral processes