Supply Chain Management Plan

Full Answer Section

     

2. Forecasting: A Case Study with Espresso Beans:

2.1 Data and Model: Assuming access to historical monthly data on advertising spend (x) and espresso bean consumption (y) in pounds, we can utilize a simple linear regression model: y = a + bx, where:

• y = Predicted pounds of espresso beans
• x = Advertising expenditure in dollars
• a = Intercept (y-axis value when x = 0)
• b = Slope coefficient (representing change in y for every unit change in x)

2.2 Interpretation and Forecast: Upon analysis of the fitted regression line and R-squared values, we can draw relevant conclusions:

• Strength of Correlation: A high R-squared signifies a strong positive correlation, indicating advertising drives higher bean consumption. For instance, a 0.8 R-squared implies 80% of espresso bean usage variation is explained by advertising.
• Predictive Capacity: The slope coefficient (b) tells us how much espresso bean demand increases for each additional dollar spent on advertising. By plugging in the desired advertising budget for month 7 ($1,350), we can predict the corresponding espresso bean requirement.

2.3 Insights for Wild Dog Coffee Company:

• Average Daily Demand: By dividing the forecasted monthly bean consumption by the number of open days, we can estimate the average daily demand.
• Advertising Efficiency: Analyzing the model can tell us if increasing advertising is cost-effective in terms of additional bean sales.
• Strategic Decision Making: Armed with these insights, Wild Dog can fine-tune their advertising budget allocation and optimize promotional efforts for maximum return on investment.

3. Inventory Management Strategies:

Two common inventory management systems for Wild Dog Coffee to consider are: 3.1 Fixed Reorder Quantity (FROQ):

• Pros: Simple to implement, minimizes ordering costs by placing larger orders at predetermined intervals.
• Cons: Requires accurate demand forecasting, risks stockouts if demand spikes or forecasts are inaccurate.

3.2 Continuous Review (ROP):

• Pros: Maintains a desired inventory level by ordering new stock when it reaches a predetermined reorder point (ROP). Adapts to fluctuating demand.
• Cons: Requires frequent monitoring, might lead to more frequent orders with higher transaction costs.

3.3 Recommendations for Wild Dog:

• Due to limited storage space and capital constraints, ROP with a buffer stock might be preferable. This balances responsiveness to demand fluctuations with inventory cost optimization.
• Regularly re-evaluating the ROP based on updated demand forecasts is crucial for maintaining efficient inventory levels.
• Implementing safety stock procedures to mitigate the risk of stockouts during unexpected demand surges.

4. Scheduling and Capacity Planning:

• Analyze hourly, daily, and weekly demand patterns to optimize staff scheduling and resource allocation.
• Identify peak and off-peak periods to ensure adequate staff availability during busy times.
• Cross-train employees to ensure flexibility and coverage during unexpected demand changes.
• Monitor equipment capacity and plan potential maintenance or upgrades to avoid disruptions during high-demand periods.

5. Conclusion and Recommendations:

This demand management plan provides a framework for Wild Dog Coffee to optimize operations and prepare for their second location. By employing accurate forecasting, efficient inventory management, and flexible scheduling, Wild Dog can ensure product availability, minimize costs, and deliver a consistently delightful customer experience. It is crucial to constantly adapt and refine these strategies based on actual demand data and market changes to maintain a competitive edge in the evolving coffee landscape.  

Sample Solution

   

This plan outlines a comprehensive approach to demand management for Wild Dog Coffee Company, including forecasting, inventory control, and scheduling strategies. The aim is to optimize resources, minimize operational costs, and ensure customer satisfaction in preparation for the expansion to a second location.

1. Assessing the Impact of Advertising:

Based on the provided information, it is essential to analyze the historical data relating to advertising expenditures and espresso bean consumption. This analysis can be conducted using a simple linear regression model to explore the correlation between these variables. By interpreting the slope and R-squared values, we can determine the strength and direction of the relationship.