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measure their own performance on KPIs to that of respondents within the same demographic , based on industry , type of customer served , type of picking operation , and other factors . “ This will help to answer questions like where should we make improvements , and what specific activities should we be looking at ” in order to make those improvements , Tillman explains .
The research team also takes a deep dive into the findings to uncover trends and explore whether they have an impact on warehouse performance . They sometimes turn up surprises . For example , this year , five of the top 10 performance metrics respondents said they use most often were related to labor . Just two years ago , four of those ( contract employees as a percentage of total workforce ; overtime hours as a percentage of total hours ; part-time workforce to total workforce ; and percentage of employees who are cross-trained ) were ranked at the bottom of respondents ’ lists .
Another surprise : Adoption rates for some efficiency-enhancing technologies has not grown as much as expected . For example , only 65 percent of respondents are currently using a warehouse management system ( WMS ), a long-established technology that ’ s generally considered to be a “ must have .” Moreover , there was no statistically significant difference in performance between companies with and without a WMS . In the team ’ s estimation , this probably reflects current users ’ failure to fully utilize the software ’ s capabilities ,
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