MBA FPX 5016 Assessment 2 Demand Management Plan

MBA FPX 5016 Assessment 2 Demand Management Plan

Lydia Languedoc

Capella University

School of Nursing and Health Sciences

MBA-FPX5016 A2

December 16, 2025

Demand Management Plan

Demand management plan combines the planning of forecasting, inventory control and scheduling of resources to ensure the optimization of the operational efficiency. This is a systematic process that provides sufficient supply level and reduces the carrying costs at the highest possible customer satisfaction. Jasiński. (2024) argues that using effective demand management, production capacity is adjusted based on market needs and requirements with the help of data. Strategic planning helps businesses to predict the changes, minimize the wastes, and sustain the competitive edge.

Advertising Impact Assessment

Statistical result depicts a high level of positive correlation between advertising expenditure and consumption of espresso beans at Wild Dog. Linear regression modeling shows that advertisement dollars predict 95.14% of the monthly usage of the beans. The regression equation is y = 0.7885x + 188.22 which shows that every dollar of advertising produces 0.79 pounds. According to research by Zhang et al. (2025), marketing investments are proving to have viable effect on consumer demand patterns. This strong correlation (r = 0.9754, p < 0.001) proves that advertising is an effective way of bringing customers. The 6-month of historic data offer statistically significant support of further investment of marketing to grow.

The amount of advertising (between $1,000 and $1,500 every month) is associated with the consumption of beans (between 987 and 1,412 pounds). The high R-squared value implies that advertising is one of the predictors that are useful in demand forecasting. Each increment of 100 in advertising budget translates to about 79 more pounds of the bean intakes per month. Jasiński. (2024) highlight that the measurable advertising outcomes allow making the decisions on the contributions to resources and operations planning superiorly. This predictive ability facilitates proper inventory planning and decisions on staffing depending on the budget allocations on marketing. The management is capable of making changes in the amount of money spent on advertising with the assurance of the measurable effect on the operational resource needs.

Demand Forecasting Model

The forecasting model involves simple linear regression to forecast the requirement of espresso beans on the investment made on advertisement. Month 7, which will have advertising budget of 1,350, the model will predict that 1,252.76 pounds of beans will be required. This forecast is within the range of historical data, and this means that there are reasonable and realistic predictions regarding demand of operations. According to Khashei et al. (2021), regression models with R 2 values of more than 0.90 give the most reliable forecast. The high statistical validity of the model (R 2 = 0.9514 ) gives a good grip in terms of accuracy and reliability of the forecasts. Residual analysis helps in ensuring that the assumptions of the models are satisfied, thus the errors are randomly distributed about the regression line.

Wild Dog Coffee Company is open 14 hours in a day and average numbers of 420 cup of espresso beverages per day. Every drink has to be prepared with 1.5 ounces of beans so that it is 630 ounces or 39.38 pounds per day. The 30.33 days monthly operations (364 days per year) will consume around 1193 pounds in the baseline conditions. Month 7 forecast is 41.30 pounds per day, which is an increment of 4.9 percent as compared to baseline. According to Tadayonrad and Ndiaye. (2023), stockouts are avoided by accurate demand translation between forecasts and operational demands. This slight growth is strategic to a grow-up but can be operated at the present infrastructure capacity.

• Predictive Strength and Model Interpretation

Advertising to demand model is very predictive and explains 95.14% of variation in the usage of beans. This is a very high R-squared value that is way above the 70% mark that can be regarded as acceptable when using business forecasting. The low p-value (0.0009) of the model shows that the results are statistically significant and are not probable because of probability. The fact that the standard error is 0.0891 is the confirmation that the prediction is accurate and that the forecasts are usually correct within the range of ±177 pounds a month. Casas. (2023) suggest the continuous validation of the model by the use of constant data collection and refinement. Advertisement and demand data tracking should be further pursued by the management in order to optimize accuracy of the model in the long term.

Inventory Management Analysis

The EOQ model is an order quantity that optimizes the system based on ordering costs and holding costs. The EOQ of the Wild Dog Coffee Company is 863 pounds rounded off to 875 pounds. This will be equivalent to 35 packages of 25-pound packages, which will be ordered in 19.20 packages one year every year. EOQ total annual inventory costs amount to under $776.79, which is a combination of ordering costs (383.04) and holding costs (393.75). According to Haekal. (2023), EOQ methodology reduces the overall inventory cost whilst ensuring the service levels. The reorder point is determined at 331 pounds with eight point one pounds of safety stock cover. The total cost is reduced through this model and it has guaranteed that the supply of beans is continuous during the seven days of lead time.

The periodic review system uses weekly inventory evaluation having order-up-to level of 657.55 pounds (675 actual). The specified strategy will involve making orders after seven days no matter the current inventory relative position. The protection interval is 14 days (review period and lead time), which requires an increase in safety stock levels. The annual expenses are 1195.84 of which 1040.25 on the cost of ordering and 155.59 on the cost of holding inventory. As per Žic et al. (2024), periodic review systems are more administratively simple, although they are characterized by increased inventory costs. The average order quantities are about 323 pounds per week, which gives an operational convenience in terms of regularity and predictability. Nevertheless, this is not the most cost-effective method of operations because it is more expensive than EOQ.

• Comparative Analysis and Model Selection

EOQ model has the clear cost advantage saving the amount of 419.05 in comparison to periodic review systems every year. The smaller ordering frequency of EOQ (19 compared to 52 annually) save a significant amount of transaction allied to the increased inventory. The 875 pound order quantity gives a supply of about 19 days of supply at the current consumption rates. EOQ is in line with the cash flow limitations of Wild Dog as it orders in large amounts at strategic times. According to Raju. (2022), small businesses can enjoy the benefits of the EOQ models because of capital constraints. The 19-day is however more than the two week fresh window and requires close FIFO movement of inventory. Management is forced to strike a compromise between cost reduction and maintaining the level of the product quality with a strict management of inventory turnover.

• Safety Stock and Service Level Considerations

The two models are inclusive of 95% service level protection, which will ensure that there is an adequate stock volume during lead time phases. The EOQ safety stock of 8 pounds will cushion against fluctuation in demand with a minimum carrying cost. The standard deviation of 1.84 pounds/day demand suggests relatively consistent, predictable consumption of the food which sustains lower safety. The risk of stockout is also low since the lead time equals seven days and safety stock buffer protects. Saldanha et al. (2022) advise that the balance of service level and inventory investment trade-off should be made in safety stock calculations. The trend is expected to change with a monthly demand of about 1,400 pounds the needs to be monitored keenly to make adjustments to the model.

Staffing And Scheduling Analysis

The present staffing arrangement has a total of seven employees that consist of four baristas and three non-baristas working in shifts. The staffing of Baristas comprises one full-time employee, 40 hours, and three employees of part-time employing total hours. Other non-barista employees include 1 full-time staff at 40 hour and two part-time staff at work. The total number of labor hours is 176 per week with a weekly payroll expenditure of 2350.00 including benefits. The annual expenditure on staffing amounts to 122,200 which is a considerable fixed operation cost that needs to be optimized prior to growth. Amengual and Distelhorst. (2025) also focus on locating labor coverage holes, such that operational breakdowns in locations are destined by expansion. Existing model has definitive 20-hour gap in coverage over 196 total hours of complete operations.

In Scenario 2, strategic staffing can be improved by adding one full-time barista and one non-barista part-time. This set up has eight staff members, two full-time and two part-time baristas and full-time. The overall coverage is 206 hours per week which offers 10 hours coverage surplus over the operational requirements. The total cost is increased to 2764.00 per week and the annual expenditure to 143728.00, which is an increment of 21528.00 per year. Two new hires have one-time hiring cost of $1,000 that gives the company an immediate capacity to grow. According to Papademetriou et al. (2023), strategic investments in staffing give a pay back in the form of better quality and reliability of services. With increased coverage, there is no conflict in schedules, less reliance on overtime and also, there is better work to life balance of the employees.

• Comparative Staffing Analysis

The cost of scenario 1 is lower but it has poor coverage that exposes it to operational vulnerability on a daily basis. The shortage of 20 hours per week necessitates the use of overtime, burnout of the employees, and even the possibility of deteriorating service quality. The increased cost structure in scenario 2 offers reliability in its operations, flexibility in its scheduling and expansionability. The extra labor hours that are bought at the cost of the increase in the weekly cost of 414 dollars are 30 labor hours or 13.80 per hour. This is lower than the usual overtime rates, and having more personnel is cheaper than overtime. Tadayonrad and Ndiaye. (2023) affirm that the appropriate level of staffing has a direct relationship with customer satisfaction and the performance of operations. Better coverage allows providing better customer service at peak times and provides buffer in case of absenteeism.

Recommendations

The Economic order Quantity model that should be adopted by Wild Dog Coffee Company in the procurement of espresso beans is the Economic order quantity. The EOQ model provides 419 yearly savings with 95 percent service level coverage being satisfactory. When the inventory goes up to 331 pounds then orders 875 pounds (35 packages) should be made. The management should put up stringent FIFO rotation controls to see that the beans are consumed when in their freshness. Li and Yu. (2023) highlight that FIFO programs ensure that there is no deterioration of quality in perishable inventory management systems. Close-out stock outs will be avoided through weekly auditing of inventory to ensure compliance with reorder points. Such a system is cost effective and maintains the quality of products that are vital in retaining customers.

It is highly recommended to use Scenario 2 optimized staffing model in spite of the increased costs due to the consideration of operational excellence. The 21,528 yearly investment will eradicate coverage deficits, decrease the possibility of burnout, and offer expansion-ready capacity. By incorporation of one full-time barista and one part time non-barista, the company will achieve flexibility in scheduling that is fundamental to growth. This set up facilitates the opening of the second location by setting up effective staffing ratios and processes. According to Tadayonrad and Ndiaye. (2023), standardized labor models allow achieving successful multi-location replication and scaling strategies. At the current point, Scenario 2 must be applied by the management, performance indicators will be monitored, and then repeated. Directly, enhanced coverage will create better customer experience, employee satisfaction and back up operations in face of unexpected demand spikes.

Conclusion

Comprehensive demand management analysis confirms Wild Dog Coffee Company possesses strong operational foundation for expansion. Advertising demonstrates robust 95% predictive power for demand forecasting, enabling confident resource planning and allocation. The EOQ inventory model provides cost-optimal bean procurement while maintaining product quality and availability standards. Optimized staffing (Scenario 2) addresses current coverage deficits and creates scalable template for operations. Implementing these recommendations establishes systematic demand management practices essential for successful multi-location operations and growth.