Advancing selection in an SME: Is best practice methodology applicable?

Effective selection tools are important for identifying high caliber employees in SMEs, yet few SMEs use tools created using ‘best practice’ methodology. Selection literature tends to focus on large organizations and is conceptual rather than empirical; which may make it difficult for SMEs to use a best practice approach. This article addresses this by providing an empirical account of the design and validation of two selection tools in a medium-sized recruitment consultancy using a best practice selection methodology. Two work sample tests were developed using critical incident technique interviews, and validated using a concurrent design with existing recruitment consultants who were ‘high’ or ‘low’ performers according to sales output. Results indicated that the tools significantly differentiated between high and low performers, and there was a significant correlation between test performance and individual sales output. Findings are discussed in relation to implications for research and practice in SMEs and selection

Genetic parameters and evaluation of rear legs (rear view) for Brown Swiss and Guernseys

Genetic parameters were estimated for rear legs (rear view; RLRV) and 15 current linear type traits of Brown Swiss and Guernsey dairy cattle. The Brown Swiss Cattle Breeders' Association of the USA and the American Guernsey Association began scoring RLRV in 2004. For Brown Swiss, 8,502 records were available for 7,676 cows in 417 herds; Guernsey data included 5,437 records for 4,749 cows in 229 herds. Nine unknown-parent groups were defined for each breed, each with 2 birth years. The model included fixed effects for the interaction of herd, appraisal date, and parity; appraisal age within parity; and lactation stage within parity and random effects for animal, permanent environment, and residual error. The multitrait analysis for RLRV and the 15 linear type traits used canonical transformation, multiple diagonalization, and a decelerated expectation-maximization REML algorithm. For Brown Swiss, heritability was 0.102 for RLRV and ranged from 0.099 for rear legs (side view) to 0.453 for stature. For Guernseys, heritability ranged from 0.078 for RLRV to 0.428 for stature. For Brown Swiss, the highest genetic correlation with RLRV was 0.71 for rear udder width; the most negative correlation was -0.19 with rump angle. For Guernseys, the highest genetic correlations with RLRV were 0.43 for rear udder width and 0.42 for body depth; the most negative correlation was -0.46 with rear legs (side view). With heritability near 0.10, RLRV should be useful in selection for improved locomotion. Release of genetic evaluations for RLRV began in May 2006 for Brown Swiss and Guernseys