Wild Dog Coffee Company: Operations Management Report

Introduction

The present report aims at analyzing operations of the current location of Wild Dog Coffee Company to refine the demand management strategy for a new location. First, the report assesses the impact of advertising on demand using a linear regression model. Second, the report evaluates two approaches to inventory management to define an optimal strategy for the new coffee shop. Finally, scheduling management is assessed to select the most appropriate composition of full-time and part-time employees. The report is concluded with recommendations based on the results of the analysis.

Demand Forecasting

The present section provides a forecast of demand using the expenditures on advertisements. Data for the past six months is analyzed to create a simple linear regression model, where the demand is the dependent variable and the advertising budget is the independent variable. The created model is interpreted to explain how it can be used in practice.

Forecasting Method Selection

Almost every decision made in the modern business world is impossible without forecasting. The accuracy of forecasting is affected by the selected forecasting method. There are numerous forecasting methods, including constant growth (straight-line model), simple moving average (SMA), exponential moving average (EMA), weighted moving average (WMA), simple linear regression, multiple linear regression, neural network (NN), and many others (Krajewski et al., 2019). Thus, a person needs to be aware of the possible approaches to forecasting to analyze every option for appropriateness critically. Additionally, an analyzer often needs to balance between complexity and potential accuracy when selecting a forecasting model.

Since Wild Dog Coffee Company is a relatively small business, the utilization of complicated forecasting methods may be inappropriate, as it may overcomplicate the process. Thus, three forecasting methods were considered for the analysis, including straight line, SMA, and linear regression model. The constant growth model was rejected, as the collected data on the demand for coffee beans was not linear. The owners of the company believe that the advertising budget affected sales significantly, which made the linear regression analysis the most appropriate approach to forecasting. Linear regression is a commonly used forecasting method when only one predictor is identified (Lahart, 2015). Thus, it was decided to use a simple regression model for predicting demand.

Effect of Advertising on Sales

The demand forecast by assessing the effect of advertising budget on sales. Data for the past six months was used to conduct the analysis. The utilized data is provided in Table 1 below.

Table 1. Sales and advertising data

The analysis revealed that advertising budget was a significant predictor of the demand with a probability of p<0.001. This implies that the use of the advertising dollars as a predictor of the demand for beans was appropriate. The coefficient of determination was very high (R² = 95.14%), which demonstrates that the advertising budget had a very high impact on demand for coffee beans. The regression analysis results are provided in Appendix A. The regression equation created by the analysis was the following:

Where:

• y – Pounds of beans used for a month
• x – Monthly advertising budget in dollars

While the model appears optimistic, as the coffee shop can make potentially high investments in advertising to boost sales, there are certain limitations to the reliability of the model. In particular, the model was created using a relatively small amount of data in the range between $1,000 and $1,500 on investments in advertisements. Thus, the forecasts will be most reliable for investments in this range, while forecasts significantly higher or lower investments may be unreliable.

Model Interpretation

The regression model provided in Section 2.2 can be used to forecast the demand for coffee beans using the estimated advertising budget. For instance, if the board of directors decides to invest $1,350 next month. The demand may be calculated the following way:

Thus, the forecasted demand will be approximately 1,253 lb. of coffee beans per month. Considering that there are 30 days in a month, the company will need approximately 41.8 pounds of coffee beans per day, which corresponds to 501.6 ounces. Since the coffee shop needs approximately 1.5 ounces of beans to make one cup of coffee, the coffee shop will need to serve approximately 334 cups of coffee per day. Since the company works 14 hours a day, it will need to serve 24 cups an hour on average. However, the hourly demand may differ considerably depending on the time of the day.

The coefficient of determination demonstrates that the model has a very large effect size. It indicates that 95.14% of the changes in the demand for coffee beans can be predicted by the amount spent on advertising. Moreover, the coefficient shows that a $1 increase in the advertising budget is expected to increase the demand by 0.79 pounds of beans, which is six additional cups of coffee served a month. Thus, advertising dollars have a large impact on the demand for coffee beans, and the advertising budget has an outstanding predictive ability of the demand for coffee.

Inventory Management Analysis

The present section provides the most appropriate inventory management strategy using the information gathered from the inventory management analysis. First, the section discusses the most advantageous approach to inventory management by assessing the benefits and drawbacks of periodic and continuous review systems. Second, the section discusses the optimal order quantity and reorder level that are expected to minimize the total holding costs. Finally, the section provides an estimation of the annual holding cost for the selected inventory management strategy. The results of the analysis are used to provide recommendations in Section 5 of the present report.

Approaches to Inventory Management

There are two general approaches to inventory management used by different types of organizations. These approaches are the periodic review system and the constant review system. The periodic review system supposes that there is a fixed interval between the reorders. In this system, the inventory position is reviewed periodically rather than constantly (Krajewski et al., 2019). In this system, the reorder period is fixed, while the order size changes depending on the forecasted demand. When an organization uses this inventory management method, an order is always made at the end of the review period (Krajewski et al., 2019). This method is convenient, as the management team does not need to monitor inventory between periods, which saves resources. Additionally, the periodic review period is advantageous when several types of goods are ordered from the same supplier, as different items may run out at different times. The periodic review method can help to optimize the total order costs.

While this method may be appropriate for large firms that can afford to keep large inventories, it is inappropriate for the Wild Dog Coffee Company. The organization orders only one type of beans from one supplier. Additionally, the company does not have the money to store large amounts of inventory, and unnecessary expenditures for taxes, insurance, and shrinkage are also unbearable for the company. Deterioration shrinkage is a major concern, as coffee beans lose their freshness two weeks after delivery. Thus, a continuous inventory review system is more appropriate for the Wild Dog Coffee Company.

The continuous inventory review approach is associated with significant costs associated with constant monitoring. The method is appropriate for small companies, as there are few items to monitor. Continuous inventory review system supposes that the time between the orders changes while the order size remains unchanged. The method helps to keep the inventory costs down, as the company can make an order using the economic order quantity (EOQ) approach and inventory control quantities.

Calculating Order Quantity and Re-Oder Level

The conducted research revealed that the current demand for espresso beans is approaching 1,400 pounds per month, which is 16,800 pounds per year and 46.15 pounds per day (considering that the business is open 364 days a year. The daily demand for the beans is unstable, with a standard deviation of 1.84 pounds. The espresso beans are shipped in 25-pound packages at a price of $9 per pound. The lead time of the order is constant at seven days on any day of the week. The shipping is free on orders over $250, while the shipping cost on orders below $250 is $19.95 per order, regardless of weight, which is the only reordering cost. In case the coffee shop runs out of beans, the business will need to be closed until a new order is delivered.

First, it is crucial to calculate the economic order quality, which is the optimal lot size. EOQ is calculated using the following formula:

Where:

• S = setup costs per order;
• D = demand rate or quantity sold per year;
• H = holding costs per unit per annum.

Based on the information mentioned above, the EOQ is

However, this amount is inappropriate for Wild Dog Coffee Company, as the order size is above the 25-pound threshold, which makes the order cost $0 since the shipping is free. Thus, the company is free to make orders of any quantities, which is sufficient to cover the lead time and possible variance in demand.

Next, it is crucial to determine the reorder point, which can be calculated using the following formula:

Where:

• U = maximum usage per day
• L = maximum lead time

This formula requires determining maximum usage per day, which is determined by the service level. Since the cost of having no beans is very high (closing business until the next batch arrives), the service level should be very high. It was assumed that the service level of 99.9% was appropriate for the company, which is approximately 3.3 standard deviations from the mean daily use. Thus, the maximum daily use will be:

Considering that it was appropriate for the company to have a safety stock of 100 pounds, which is enough to cover two days of operations, the reorder level is:

Since the lead time is a week and the amount needed to cover the lead period is 361.7 pounds, the order size should be 375 pounds or 15 packages.

In this scenario, the total holding cost can be calculated using the following formula:

Scheduling Management Analysis

The present section aims at assessing the most appropriate approach to scheduling management. Up until now, shifts in Wild Dog Coffee Company have been scheduled according to the employees’ will. While this has generally worked out well, the scheduling process needs to be tightened up to optimize the staffing model. Two strategies for scheduling are discussed in the present section, including the employee retention strategy and weekly cost minimization strategy. The benefits and drawbacks of each strategy are discussed from both financial and non-financial viewpoints.

Both scheduling scenarios discussed in the present section are based on the following assumptions.

• Baristas’ hourly wage is $14/hour;
• Full-time non-baristas employees are paid $12/hour;
• Part-time non-baristas are paid $9/hour;
• Full-time employees can work up to 40 hours a week with 10 hours of possible overtime;
• Part-time employees can work up to 20 hours a week with 6 hours of possible overtime;
• Full-time employees enjoy benefits of 15% of the wage, which are not paid for overtime hours;
• Overtime hours are paid at a 150% level;
• The coffee shop works 12 hours a day and needs at least one barista and one non-barista employee to operate;
• One hour for opening and one hour for closing should be allocated every day to one employee;
• Full-time employees are likely to resign if they are moved to part-time work;
• The cost of hiring another employee is $500 and $250 to terminate an employee.
• The shop currently hires four baristas, among which three are part-time, and three non-barista employees, among which two are part-time.

Employee Retentions Strategy

The first strategy considered for scheduling was based on the idea of employee retention. The primary goal of this strategy was to minimize the costs using the current workforce available for the Wild Dog Coffee Company. A spreadsheet for the employee retention scheduling strategy that includes the number of hours worked by each employee, the total number of hours worked per day, the total number of hours worked by week, and associated costs are provided in Appendix B.

Cost minimization was achieved by eliminating the hiring and employee termination costs and using the minimum amount of overtime. Additionally, all the overtime hours (a total of four hours) were given to the part-time non-barista employees, as they have the lowest hourly wage. The total weekly costs of the strategy are $2,418 per week without additional HR costs for hiring and contract termination.

While the maximum effort was given to cost minimization, some scheduling decisions remained suboptimal. First, all the closing and opening hours were given to baristas, as giving these hours to non-barista employees would mean paying for overtime work. Second, two barista hours remained unused, while the company had to pay 4 hours of overtime job to non-barista employees. Third, the company continued using the services of full-time employees, which are associated with higher costs. Thus, the major drawback of the scenario is financial inefficiency, which leads to increased costs.

While the strategy is associated with increased daily costs, it increases the retention rate of the company. Some of the crucial benefits of high retention rates include HR cost reduction, morale improvement, increased employee experience, recruitment, and training efficacy, increased productivity, and better customer experience (Holiday, 2021). Additionally, Increased retention is associated with improved customer experience, better workplace culture, increased revenue and improved employee satisfaction (Holiday, 2021). In other words, retaining employees now will help to decrease turnover in the future, which is expected to decrease HR costs in the long run. Singh (2019) states that human capital plays “an extremely crucial role in the sustainability and development of an organization” (p. 425). Thus, even though the strategy is associated with increased weekly costs, it may still be a strategically correct decision to follow this approach.

Minimum Weekly Cost Strategy

The second approach taken to scheduling is the cost minimization strategy. The primary goal of the strategy was to minimize daily costs without taking into account the one-time HR costs associated with hiring and terminating contracts. Additionally, non-financial benefits of retaining the workforce were not considered. A spreadsheet for the minimum weekly cost scheduling strategy that includes the number of hours worked by each employee, the total number of hours worked per day, the total number of hours worked by week, and associated costs is provided in Appendix C.

Cost minimization was achieved using several fundamental principles. First, no full-time employees were used. According to the company’s policy, all full-time employees receive benefits of 15% from the hourly wage. Thus, using only part-time workers is expected to reduce the costs by this amount. Additionally, part-time non-baristas are paid less than full-time non-barista employees. Second, the opening and closing hours were given to non-barista employees, as they are paid less than baristas. Third, four-overtime hours were still allocated to baristas, as it appeared more rational than hiring another part-time barista, which would be associated with another $500 of costs. The strategy requires four part-time baristas and five part-time non-barista employees. The total weekly costs associated with this strategy were estimated at $2,086. Additional HR costs for hiring new employees and terminating old contracts are demonstrated in Table 2 below.

Table 2. Additional HR costs associated with the minimum weekly cost strategy

Note: a full-time barista and a full-time non-barista are expected to resign. One part-time barista and three part-time non-baristas will need to be hired.

This strategy requires $332 less every week than the employee retention strategy. This implies that the additional costs associated with hiring new employees and contract terminations will be covered in eight weeks, which is financially advantageous. The strategy can save up to $14,764 ($332*52 weeks – $2500) a year.

While this scenario is associated with greater financial gains than the employee retention strategy, non-financial aspects of the matter need to be evaluated. In particular, it is crucial to notice that replacing employees means increased turnover rates, which can be harmful to the business. According to Hall (2019), high turnover may be associated with one-third of all HR costs. Turnover has direct and indirect costs that cannot always be quantified. The direct costs include hiring costs, termination costs, and training costs (Hall, 2019). Indirect costs include productivity losses, quality deterioration, damaged morale, and decreased customer satisfaction (Hall, 2019). It was estimated that employees need 8-12 weeks to start working at their full capacity (Hall, 2019). This implies that the quality and the efficiency of new employees are low for two or three months after hiring. Trainers and trainees are often pulled away from other work, which decreases their productivity (Hall, 2019). Decreased morale may also affect the corporate culture, employee experiences, and retention intentions (Holiday, 2021). Additionally, relying on part-time employees may decrease the loyalty of the staff, which also affects the retention rates. In summary, it is crucial to assess non-financial factors before selecting the most appropriate staffing strategy.

Recommendations

Forecasting recommendations

1. Use advertising dollars to forecast the demand. The analysis demonstrated that using advertising budget as a predictor is appropriate for forecasting demand for espresso beans. The regression model demonstrated goodness of fit of more than 95%, which demonstrated that the model is highly reliable.
2. Utilize the model provided in Section 2 with caution for advertising budgets significantly higher than $1,500. The model was created and tested using limited data. In particular, advertising budgets between $1,000 and $1,500 were present in the sample. Thus, the reliability of the model may drop when forecasting for significantly higher or lower advertising budgets.

Inventory management recommendations

1. Use continuous inventory review approach. Since the company does not need to monitor large amounts of inventory units (only one type of beans is used), the approach can be helpful for the company to reduce inventory-associated costs.
2. Reorder inventory when 18 packages are left. The calculations demonstrated that the company’s reorder level was 444 pounds, which is approximately 18 25-pound packages. Thus, whenever employees see that only 18 packages are left, they should place a new order.
3. The order size needs to be 15 packages. This amount is enough to cover a week of operations, which is the lead time.

Scheduling recommendations

1. Select the employee retention strategy rather than the minimum weekly cost strategy. Even though the second scenario is associated with larger financial gains, direct and indirect costs of turnover are expected to have a drastic negative impact on Wild Dog Coffee Company, such as productivity losses, quality deterioration, damaged morale, and decreased customer satisfaction.
2. Search for alternatives to the two scenarios discussed in the report. It is possible that a combination of the two approaches discussed in the present report can be used to optimize the scheduling strategy. Thus, further review may be needed to improve the current decision.

References

Bushnell, M. (2020). Should you hire full-time or part-time employees? Business.com. Web.

Hall, J. (2019). The cost of turnover can kill your business and make things less fun. Forbes. Web.

Holiday, M. (2021). 10 benefits of employee retention for businesses. Web.

Krajewski, L. J., Malhotra, M. K., & Pitzman, L. P. (2019). Operations management: Processes and supply chains (12th ed.). Pearson.

Lahart, J. (2015). America’s fixer-upper housing market. The Wall Street Journal. Web.

Singh, D. (2019). A literature review on employee retention with a focus on recent trends. International Journal of Scientific Research in Science and Technology, 6(1), 425-431.