eComp.com manufactures personal digital assistants (PDAs). Because these very small computers compete with laptops that have more functions and flexibility, understanding and using cost behavior is very critical to eComp.com’s profitability. eComp.com’s controller, Kelly Hudson, has kept meticulous files on various cost categories and possible cost drivers for most of the important functions and activities of eComp.com. Because most of the manufacturing at eComp.com is automated, labor cost is relatively fixed. Other support costs comprise most of eComp.com’s costs. Partial data that Hudson has collected over the past 25 weeks on one of these support costs, logistics operations (materials purchasing, receiving, warehousing, and shipping), follow:

1. Plot logistics costs, Y, versus number of orders, X. What cost behavior is evident? What do you think happened in week 14?

2. What is your recommendation to Kelly Hudson regarding the relevance of the past 25 weeks of logistics costs and number of orders for measuring logistics cost behavior?

3. Hudson remarks that one of the improvements that eComp.com has made in the past several months was to negotiate JIT deliveries from its suppliers. This was made possible by substituting an automated ordering system for the previous manual (labor-intensive) system. Although fixed costs increased, the variable cost of placing an order was expected to drop greatly. Do the data support this expectation?

Do you believe that the change to the automated ordering system was justified? Why or why not?

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Logistics Costs, Y Number of Orders, X Week $23,907 1,357 2 18,265 1,077 3 24,208 1,383 4 23,578 1,486 5 22,211 1,292 22,862 1,425 7 23,303 1,306 8 24,507 1,373 9 17,878 1,031 10 18,306 1,020 11 20,807 1,097 12 19,707 1,069 13 23,020 1,444 14 20,407 733 15 20,370 413 16 20,678 633 17 21,145 711 18 20,775 228 19 20,532 488 20 20,659 655 21 20,430 722 22 20,713 373 23 20,256 391 24 21,196 734 25 20,406 256