Case Study: The Realco Breadmaster Two Years Ago Johnny Chan

Case Studythe Realco Breadmastertwo Years Ago Johnny Changs Company

Develop a master production schedule for the breadmaker. What do the projected ending inventory and available-to-promise numbers look like? Has Realco overpromised? In your view, should Realco update either the forecast or the production numbers? Comment on Jack’s approach to order promising. What are the advantages? The disadvantages? How would formal master scheduling improve this process? What organizational changes would be required? Following up on Question 2, which do you think is worse, refusing a customer’s order upfront because you don’t have the units available or accepting the order and then failing to deliver? What are the implications for master scheduling? Suppose Realco produces 20,000 breadmakers every week, rather than 40,000 every other week. According to the master schedule record, what impact would this have on average inventory levels?

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The case study of Realco Breadmaster presents a compelling scenario that underscores fundamental principles of supply chain management, production scheduling, and forecasting accuracy. Johnny Chang’s company, after achieving sales success with its breadmaker product, faces issues related to inventory management, production planning, and customer promise reliability. Addressing these concerns requires a rigorous analysis of the master production schedule, inventory levels, and order promising strategies.

Developing a Master Production Schedule and Assessing Inventory and Promise Numbers

The foundational step is constructing an effective master production schedule (MPS). Based on the data provided, Realco has been producing 40,000 units every other week, with inventory at week’s end at 7,000 units. This aligns with a demand forecast of approximately 20,000 units per week, suggesting the production is planned to meet current customer demand. The existing cycle indicates a relatively stable schedule, but the high inventory levels could imply overproduction or sluggish sales, which might signal overpromising or misalignment between forecast and actual demand.

In calculating ending inventory, one would typically account for the beginning inventory, add scheduled production, and subtract customer orders. With a weekly demand of 20,000 units, a biweekly cycle of 40,000 units aligns with the forecast. However, the ending inventory of 7,000 units after a production run might suggest overstocking or a lag in sales, meaning the company could be overestimating demand. The available-to-promise (ATP) quantity, which indicates the units available for new orders, depends critically on the current inventory and future scheduled shipments. If the projected inventory exceeds future demand, then Realco could be overpromising, raising the risk of failing to meet customer expectations.

Should Realco Update Forecast or Production Numbers?

Given the static nature of the forecast and production levels over the past year, it is prudent for Realco to revisit its demand forecasts and production planning. The stagnant forecast may not accurately reflect recent market dynamics, especially considering the product's success and potential changes in consumer preferences or seasonal variations. Updating the forecast based on current sales data and adjusting production levels accordingly would enable more precise inventory management and reliable order fulfillment. If demand forecasts increase, scaling up production or increasing inventory buffers might be necessary; if they decrease, reducing production would prevent excess stock and reduce holding costs.

Analysis of Jack’s Approach to Order Promising

Jack Jones’s approach involves promising delivery within three weeks, based on experience that nearly all orders can be filled within two weeks, providing a cushion. This method offers advantages such as setting realistic expectations, accommodating variability in production and shipping, and maintaining customer satisfaction. However, disadvantages include the risk of overpromising if actual lead times extend beyond the cushion, potentially damaging customer trust. It also relies heavily on historical data, which might not account for fluctuations in demand or unforeseen delays.

Implementing formal master scheduling would significantly enhance this process by providing real-time visibility into inventory levels, production schedules, and capacity constraints. It would enable more accurate order promising by aligning commitments closely with actual capacity and inventory availability. Organizational changes required could include establishing dedicated planning teams, integrating enterprise resource planning (ERP) systems, and fostering cross-department communication to ensure data accuracy and responsiveness.

Refusing vs. Accepting Orders: Which Is Worse?

Choosing between refusing an order upfront due to stock shortages or accepting and then failing to deliver presents distinct challenges. Refusing orders upfront might lead to lost sales and potential customer dissatisfaction, but it allows the company to maintain credibility and avoid promising unfulfillable commitments. Conversely, accepting orders without sufficient stock risks penalty costs, customer dissatisfaction, and reputational damage if delivery fails. The core implication for master scheduling is to establish robust processes for assessing capacity and inventory before confirming delivery timelines, thereby minimizing the risk of overpromising.

Impact of Weekly Production vs. Biweekly Production on Inventory Levels

Producing 20,000 units weekly instead of 40,000 units every other week affects inventory levels distinctly. Weekly production creates a steadier flow, potentially reducing fluctuations in inventory, minimizing excess stock, and enabling more responsive adjustments to demand variations. This approach enhances inventory turnover rates and can lower holding costs. However, it might increase operational complexity and costs due to more frequent changeovers and scheduling requirements. Based on the master schedule record, cumulative average inventory levels should decrease due to more consistent production, better aligning with weekly demand and reducing excess stock.

In conclusion, effective supply chain management depends on accurate forecasting, agile scheduling, and realistic order promising. Realco’s current practices suggest potential overpromising and inventory buildup, underscoring the need for robust master scheduling and forecasting updates. Transitioning to weekly production, employing advanced planning tools, and refining customer communication strategies can significantly improve operational efficiency and customer satisfaction. Organizations must continually adapt their planning and scheduling practices to meet dynamic market conditions and ensure long-term success.

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