Mile High Cycles

When Mile High Cycles produced 10,800 cycles, there was a total “unfavorable,” or negative, variance between its actual and projected costs. In all costs besides the “Frame: Labor,” there were unfavorable variances – each of which can be attributed to the price variances*. The efficiency variances were mostly “favorable"– since fewer units were used than planned. The highest price variance is for “Final Assembly: Parts,” due to the actual cost per unit, $367, being higher than the projected cost per unit, $350. Furthermore, management did not account for the “Rework Parts” costs for “Frames” and “Final Assembly,” causing additional unfavorable variances. These variances caused the unit cost of 10,800 units, $1,108.31, to be higher than that of 10,000 units, $1,089.50. For a complete detailed variance analysis, please see Exhibit 1.

I have several key recommendations to management for its next budget cycle. Most notably, I recommend the purchasing team research all the ways by which materials and labor prices would increase when there is a change in production. Additionally, since any variance, even favorable, should be investigated, the production team should research the efficiency variances to see why there was a discrepancy. Moreover, management should improve its processes, so that “Rework Parts” costs can be decreased, or eliminated; if they cannot, they should be included in the Master Budget. Using these suggestions, management should create not only a Master Budget, but also Flexible Budgets for different levels of production, as the flexible budgets would illustrate each production level’s materials costs – the cause of the high price variance (See Exhibit 2 for an example). Further, management should use this information to negotiate a stable, but low, price from its suppliers – or look to purchase materials elsewhere – so that there is not such a large price, and therefore, total variance, when production increases. Or, if management cannot receive a stable price from a supplier, it can use this information to decide whether to increase its selling price – assuming that demand for cycles is still high. [pic 1]