Parts emporium case study, solutions and answers - Free Essay Example

Sample details Pages: 4 Words: 1316 Downloads: 2 Date added: 2017/06/26 Category Marketing Essay Type Analytical essay Did you like this example? Case Parts Emporium Methodology Briefing 3 Inventory Analysis 5 This Report has been prepared in response to the warehouse inventory situation as appraised to me by Joe Donnell. In assessing the situation, I have found that the installation of a computer model for ordering projection will alleviate out of stock as well as overstock situations. Additionally, the preceding will need to be augmented by physical hand counts on a periodic basis to ensure that the physical inventory matches the computer ordering system counts. Don’t waste time! Our writers will create an original "Parts emporium case study, solutions and answers" essay for you Create order In addressing the present situation, I took a count of parts EG151 and DB032 as a sample in order to assess an actual inventory. That analysis as well as the subsequent recommendations are based upon the preceding, which will also work for the remaining warehoused parts after a physical count is established to enable me to pattern a computer modeling system for each item. The foregoing physical count, and periodic count follow up is a necessary part of the system in order to ensure that the numbers match, and to address count differences to keep the inventories in line with ordering procedures. In conducting my analysis, it was determined that the depletion rates for the two parts followed a consistent pattern, thus far. That analysis was based upon the sales rate; therefore, in order to maintain an accurate ordering program, daily sales information on all parts will need to be forwarded to me for monitoring so that if depletion rates change, I can adjust the ordering program vari ables. The following represents the results of the inventory analysis, and subsequent recommendations. Methodology Briefing In analyzing the problem, I referred to methodologies and techniques from the following sources Dalleck and Fetter (1961) à ¢Ã¢â€š ¬Ã…“Decision Models for Inventory Managementà ¢Ã¢â€š ¬Ã‚ , Brauner et al (2001) à ¢Ã¢â€š ¬Ã…“Velocity Management: The Business Paradigm That Has Transformed U.S. Army Logisticsà ¢Ã¢â€š ¬Ã‚ , Epps (1995) à ¢Ã¢â€š ¬Ã…“Just-in-Tine Inventory Management: Implementation of a Successful Programà ¢Ã¢â€š ¬Ã‚ , and Debnam et al (1992) à ¢Ã¢â€š ¬Ã…“Inventory Analysis for Generation, Transmission and Distribution Cooperatives of the Rural Electric Systemà ¢Ã¢â€š ¬Ã‚ . The preceding has been included here to aid you in your analysis of the findings, and recommendations made herein. The situation here at Case Part Emporium entails a mixture of solutions, thus my referral to the preceding material. Dallack and Fett er (1961, p. 8) provided the basis for à ¢Ã¢â€š ¬Ã…“à ¢Ã¢â€š ¬Ã‚ ¦ inventory planning and control when stockkeeping involves: (1) planning and control on an item-by-item basis, (2) variable demand and/ or variable lead time, (3) either continuous review or review at fixed intervals and (4) unfulfilled demand either back ordered or lost. The decision variables of interest are the reorder point and the order quantity for each item in the set of stockkeeping unitsà ¢Ã¢â€š ¬Ã‚ . Please note, since I have not equated all of the parts, there might be some subject to variable demand, and lead times, thus my inclusion of this methodology. Brauner et al (2001. p. 17) was utilized as supply entails à ¢Ã¢â€š ¬Ã…“ getting the right thing to the right place at the right time à ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚  and the applicability of U.S. Army delivery systems is predicated upon ensuring delivery in unpredictable situations. This reference source aided in defining the process for the par ts utilised in this analysis as well as having a flexible program parameter to handle the potentially differing variables that most surely will crop up in other situations. Brauner et al (2001, p. 18) refer to the Velocity Management process as à ¢Ã¢â€š ¬Ã…“à ¢Ã¢â€š ¬Ã‚ ¦improvement methodology, aims at producing a clear picture of the order fulfilment process that is common to all participants and stakeholdersà ¢Ã¢â€š ¬Ã‚ . The foregoing will be illustrated through the Excel Spreadsheet attachment that shows the methodology utilized. Epps (1995) provided the foundation for minimized inventory under the concept of à ¢Ã¢â€š ¬Ã…“Just-in-Time Inventory Managementà ¢Ã¢â€š ¬Ã‚  which was pioneered by the Toyota Motors Company. The process is based upon a à ¢Ã¢â€š ¬Ã…“à ¢Ã¢â€š ¬Ã‚ ¦philosophy that seeks to do the process right the first time and to eliminate any non-value added activitiesà ¢Ã¢â€š ¬Ã‚ . And finally, Debnam et alà ¢Ã¢â€š ¬Ã¢â€ž ¢s article (1992) was sel ected, even though the field of application, electricity, does not seemingly have applicability here, but it referred to à ¢Ã¢â€š ¬Ã…“Each cooperative participant may be subject to unique conditions, yet is faced with the same fundamental problemthe means by which to evaluate inventory decisions and the cost-effectiveness of decisions made in regard to acquisition and retention of suppliesà ¢Ã¢â€š ¬Ã‚ . In the instance of our company, the word à ¢Ã¢â€š ¬Ã…“cooperativeà ¢Ã¢â€š ¬Ã‚  was replaced with unit parts, thus the applicability to our situation. Inventory Analysis In analyzing the inventory for items EG151 and DB032, I broke down the process into a synthesis chart that enabled me to construct the computer Excel model that is attached. Said chart represented the following key variables: Chart 1 à ¢Ã¢â€š ¬Ã¢â‚¬Å" Case Parts Emporium Inventory Synthesis Variable EG151 DB032 Customer Price $12.99 $8.89 Gross Margin 32% 48% Order Price $4.13 $4.27 Order Charge $20 $10 Flat Fee Delivery $21.40 $21.40 Delivery Time Frame 2 weeks 3 weeks Lot Size 150 1,000 Estimated Depletion Rate 17 per day 54 per week The preceding were broken down into an Excel Model that utilized à ¢Ã¢â€š ¬Ã‹Å"Hypotheticalà ¢Ã¢â€š ¬Ã¢â€ž ¢ as well as à ¢Ã¢â€š ¬Ã‹Å"Actualà ¢Ã¢â€š ¬Ã¢â€ž ¢ inventory situations to provide a picture of the methodology, and to construct the Ordering point scenarios. As shown on the attached Excel Spreadsheets the ordering time frame delay for the EG151 was calculated as six days, with the depletion rate of ordered lots of 150 units taking 9 days. This meant that under the present rate of depletion, orders for replenishment had to be placed far enough in advance to ensure new parts delivery before an out of stock situation. In running the model, I utilized the depletion rate to calculate the order points, which are indicated by à ¢Ã¢â€š ¬Ã‹Å"Filledà ¢Ã¢â€š ¬Ã¢â€ž ¢ followed by a number that signifies the day (in the case of part DB032 a weekly time frame was utilized as a result of the larger lot size). As shown on the Excel model, the in stock depletion runs down to an estima ted 32 units on hand before the new inventory arrives, thus maintaining sufficient supplies. Chart 2- Excel Model Examples In the instance of part DB032, the larger lot size necessitated utilizing a weekly format. In the instance of inventory depletion, the on hand count dropped to an average of 80 units before the replenishment supply arrives. The other program parameters are thus the same and can be utilised in your review. Conclusion and Recommendations In analyzing the parts utilized in this examination I took into account the variable concerning the flat fee delivery charge of $21.40, and suggest that we should not include this in a new pricing scheme as such penalizes those customers who pick up their orders and will thus notice the price increase. Adding in the flat fee delivery charges across the board thus was not computed in any of the variables for that reason. I did not utilize the in-house ordering administrative charges in the models, as that is an accounting function that has already been included in the pricing. In addition, I examined the lot sizes and would al so like to suggest if we might convince the Bendox Corporation to provide us with a lot size of 500 units, as this reduced ordering unit would be more consistent with our utilisation rate. In any event, I prepared Excel Spreadsheet models for both variables in a à ¢Ã¢â€š ¬Ã‹Å"Hypotheticalà ¢Ã¢â€š ¬Ã¢â€ž ¢ as well as à ¢Ã¢â€š ¬Ã‹Å"Actualà ¢Ã¢â€š ¬Ã¢â€ž ¢ usage mode. As out of stock does not represent a desirable business situation for us, I would appreciate your comments on the prepared material. If positive, I will immediately proceed to conduct an analysis of all parts, and the variables associated with them in order to construct similar computer models for analysis, and recommendation. Brauner, M., Dumond, J., Eden, R., Folkson, J., Girardini, K., Keyser, D., Peltz, E., Pint, E., Wang, M. (2001) Velocity Management: The Business Paradigm That Has Transformed U.S. Army Logistics. Rand, Santa Monica, CA, United States Dalleck, W., Fetter, R. (1961) Decision Models for I nventory Management. Richard D. Irwin, Inc., Homewood, IL, United States Debnam, D., Hall, B., Lovas, T., Miller, T. (1992) Inventory Analysis for Generation, Transmission and Distribution Cooperatives of the Rural Electric System. Vol. 33. Management Quarterly Epps, R. (1995) Just-in-Tine Inventory Management: Implementation of a Successful Program. Vol. 17. Review of Business