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To:	John Gliese, Production Department Manager
From:	Vincient M. Cleamons, Senior Controller
cc:	William T. Harmon, Chief Executive Officer
Date:	February 7, 2020
Re:	Massage Chairs (Product #MC09954A) Manufacturing Variance Analysis for January 2020

Calculations for a variance analysis in manufacturing 500 massage chairs (#MC09954A) during January 2020 are shown in the attached spreadsheet. This analysis shows a comparison of the benchmark expenditures (standard costs) with the actual costs involved in manufacturing the chairs. The constituents of manufacturing costs include labor and materials (refer to Table 1).

Table 1

Manufacturing Data for 500 Massage Chairs During January 2020

Items Actual Manufacturing Data Standard Manufacturing Data

Metal Tubing 3000 meters 3000 meters

Leather 1050 square meters 1000 square meters

Padding 1600 kilograms 1500 kilograms

Labor Hours 1750 2000

Labor Wages $27,265.00 $30,000.00

Cost per Chaira $54.54. $60.00

Note. Manufacturing materials, labor hours, labor wages, and cost per chair are illustrated in the table. aIncludes labor wages and the costs of materials (metal tubing, leather, and padding).

The information in Table 1 and the data for the variance analysis in the attached spreadsheet helps management ascertain the alignment of actual manufacturing expenditures for 500 massage chairs to the benchmarks (standard costs) established by the company. The variances for material usage were unfavorable. This unfavorable variance indicated that more materials were used to manufacture the massage chairs than the quantities specified in the benchmarks. However, the benchmark requires four hours of labor at $15.00 per hours to produce one massage chair. Consequently, the benchmark requirements produce 0.25 massage chairs per hour at $15.00 per hour ($60.00 to produce one chair). Therefore, to produce 500 massage chairs at benchmark standards, it would take 2,000 labor hours total. In contrast, the actual labor to produce 500 massage chairs for January was only 1750 hours (cost savings of $2,730). The 1750 labor hours resulted in a favorable variance because the actual total labor hours expended were below the benchmark. Therefore, the company may want to make changes in the wage rate to counterbalance the time productivity benefit, while also evaluating the material variances (i.e., material usage).

Though Body Comfort cannot control the fluctuations in material costs, the research of Miao, Du, Jiao, and Zhang (2017) and Whitehouse (2019) presented algorithms for controlling material costs in manufacturing operations. I suggest the company consider the respective research studies in developing cost-reduction measures. Please let me know how I can further assist management is these endeavors.

References

Miao, C., Du, G., Jiao, R. J., & Zhang, T. (2017). Coordinated optimization of platform-driven

product line planning by bilevel programming. International Journal of Production Research, 55(13), 3808-3831. doi:10.1080/00207543.2017.1294770

Whitehouse, S. (2019, April). 6 ways to control process manufacturing costs. WinMan ERP.

Retrieved from http://www.winman.com/blog/6-ways-to-control-process-manufacturing-costs

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