Combining simple motion measurement, lean analysis technique and historical data review for countering negative labor cost variance: A case study. (30th June 2021)

• Record Type: Journal Article
• Authors: Adeyemi, Bami; Ogbeyemi, Akinola; Zhang, Wenjun
• Is Part Of: International journal of engineering business management. Volume 13(2021)
• Publication Date: 2021-06-30
• Subjects: Production planning and control -- production cost -- lean manufacturing -- labor cost variance -- value stream mapping -- non-value-added activity (NVA); Engineering -- Periodicals; Industrial management -- Periodicals; Engineering; Industrial management; Periodicals; 620.0068
• DOI: 10.1177/18479790211023617
• Languages: English
• ISSNs: 1847-9790

Abstract

Negative labor cost variance (NLCV) is an important problem in many manufacturing companies today. NLCV refers to the situation that expected or standard costs are less than actual labor costs in production. Management of NLCV, including the identification of causes for NLCV and the elimination or significant reduction of NLCV, is the topic discussed in this paper. The question studied in this paper is thus: what is an effective methodology in the environment of strong privacy protection to identify causes for NLCV and to significantly reduce it ? The study presented in this paper proposed a methodology by combining a simple motion measurement (stopwatch), lean analysis techniques, and historical data review to study the NLCV problem. A case study was taken on a particular company called ABC to test the effectiveness of this methodology. Specifically, the result of the study revealed that (1) the employees in ABC waited for one reason or the other for almost 5 h (idle time) in a 16-h daily operation period (2 shifts running at 8 h each), which accounts for 32% of the total productive time, and (2) the elimination of the waiting time or idle time over the years concerned could account for 83% of all identified wastes in ABC. Through this case study, the effectiveness of the proposed methodology was demonstrated and the applicability of the proposed methodology was also implied.