Problem Solution: Burns Auto Corporation

Problem Solution: Burns Auto Corporation

Burns Auto Corporation (BAC) is owned by Thomas Burns. Burns wants to adopt a new way of doing business when it comes to managing inventories and forecasting future sales. Burns is being motivated to make changes to current policy and procedures due to manufacturers mandating a “turn and earn” approach to managing inventories. These mandates are forcing BAC to re-look the current policies and procedures to re-align its organization. Burns must find and implement one of four alternative solutions to current procedures in forecasting and inventory control management to formulate a final solution. The final solution needs to satisfy the needs of all of the stakeholders of BAC. The purpose of this paper is to define the problem that BAC is encountering, identify the issues and opportunities, and then develop a set of goals from the potential alternatives that develop a final solution. There are many possible solutions to Burns Auto’s problem. Burns needs to analyze the pros, cons, and the risks associated with the possible solutions before choosing the best solution. Once a solution is chosen, Burns must develop an implementation plan for the solution. This plan must be evaluated and justified before being acted upon.

Situation Background (Step 1)

Burns Auto Corporation (BAC) is comprised of 25 new car dealerships. Dealerships range from Boise to Albuquerque to northern and southern California. BAC has been successful throughout its 12-year history and sales in all markets have recently increased due to a strengthening economy (Phoenix2, 2006).

Historically, BAC has maintained $300M in inventory with a carrying cost of $9M per year. Because inventories have fluctuated over the past two years, the daily average inventory has risen to $360M. Because of this increase, carrying costs rose 20% to $10.8M per year. Increasing costs prompted the corporation to reassess the sales forecasting and inventory management methodology. The reevaluation is especially timely considering the recently mandated “turn and earn” supply policy, which all manufacturers will implement in eight months. Under the new policy, each dealership receives new cars only at the rate at which it sells cars (Phoenix2, 2006).

BAC is currently considering two models to estimate inventory. In both scenarios, corporate managers calculate estimates for the entire organization. The first is Richard Settle’s empirical method of using manufacturer-provided forecasts for each vehicle category. This approach based on GDP and historic monthly sales rates are tested by Settle’s intuition. Settle has years of experience and his method has worked very well until recently. Peter Reardon, a consultant with a proven record of accomplishment, who also has significant experience in the industry, developed the second method. Reardon’s method, a regression analysis model, considers several factors, including disposable income, the current interest rate, the price index, competition’s price index and sales promotions.

An alternative method, which Mary Peterson recently recommended, modifies the regression analysis model by allowing individual dealerships to tailor variables to local markets and promotion schedules (Phoenix2, 2006). The resulting monthly estimates reviewed by corporate managers and consolidated into an annual estimate report for the owner’s approval.

Issue Identification

In order to develop an adaptable inventory method for BAC four issues exist:

• Account for the impact of promotions on sales.

• Define all of the factors that determine demand.

• Proactively estimate the impact of the “turn and earn” policy on inventory levels.

• Determine the appropriate organizational level for initial estimate generation.

All parties cited promotions as a significant contributor to month-to-month variance in sales. Complete the initiation of these promotions at the local level in accordance with a long-standing policy. Reardon assigned a coefficient in his model to account for this variation. Settle stated that difficulty in determining promotions causes problems in the estimate process, uses intuition to adjust forecasts. To counter both of the means mentioned corporate level must gauge the variables to forecast the variance accurately for each of the remote sites. This would be easier and produce results that are more accurate if each dealer is locally responsible for providing this information back to corporate.

Promotions plus several other factors contributes to month-to-month sales variations. Both methods use some measure of income (GDP or disposable