MBA FPX 5016 Assessment 1 Process Improvement Plan

Student Name

Capella University

School of Nursing and Health Sciences

NHS-FPX5016

December 16, 2025

Process Improvement Plan

A process improvement plan is a methodical approach that helps to find out inefficiencies and introduce strategic improvements to the system to streamline operations. Such an organized system makes use of data analysis to review existing operations and come up with opportunities to improve in a systematic manner. The plan records the status quo of the processes, compares performance indicators and proposes practical remedies of organizational excellence (Gomaa, 2025). Best process improvement is directly proportional to increased customer satisfaction, lower operational cost and competitive advantage.

Process Flowchart Assessment

The espresso drink preparation flowchart is a systematic recording of eleven different working steps involved in the order taking up to the delivery to the customers. The given visualization creates several crucial control points such as quality checks, payment processing, and decision-making on the beverage composition (Vasudevan and Chengaiyan, 2024). The flowchart has decision nodes that differentiate milk-based and non-milk drinks, which provide flexibility in the processes. The major process tasks are bean grinding, extraction of espresso, steaming of milk and the last quality check measures.

Figure 1

Process flowchart

Espresso Beverage Preparation Process Procedure

Purpose of Procedure

The process sets up standard procedures in regards to the preparation of the espresso drinks in the locations of Wild Dog Coffee Company. The process documented allows quality consistency, efficiency of operations, and the best customer satisfaction at all service points. Standardization reduces differences in the quality of products and allows conducting successful training when recruiting new barista team members (Rogalewicz et al., 2023). The process facilitates the growth plan of the firm to develop operational excellence that is replicable in preparing beverages.

Performance Metrics

The effectiveness and efficiency of the process of preparing the espresso drinks are evaluated by three key performance indicators. Order delivery time monitors the hours in between the delivery of orders and the delivery to the customers. The optimal customer satisfaction is between two and three minutes delivery time on the target order delivery time. Consistency in beverage temperature guarantees that drinks are delivered at a temperature range of 150-165 degrees Fahrenheit. First time quality: measures the rates of beverages prepared with no rework or corrections (Taifa et al., 2021). The first-time quality rate is supposed to always be superior to 95 percent to keep the operations efficient and up to the standard.

Measurement Methods

The point-of-sale system records the order delivery time automatically by utilizing inbuilt timestamp functionality. Calibrated infrared thermometers are used to measure beverage temperature right before handoff, as a specification requirement (Scheucher et al., 2022). First-time quality rate is determined by dividing the number of successful orders by the number of orders and multiplying them by 100. These metrics are summarized in the form of daily performance reports to determine trends, patterns, and areas of continuous improvement.

Procedure Steps: Order Processing

The barista takes on the order and inputs the customer order into the point-of sale system with the right specifications. The processing and verification of payments is done and then beverage preparation is started to enable accuracy of the transactions. New espresso beans are weighed and grounded to the right level of fineness so that the quality of extraction is best (Vasudevan and Chengaiyan, 2024). The ground coffee is tamped to a steady pressure of about thirty pounds into the portafilter and spread evenly.

Procedure Steps: Beverage Preparation

The portafilter is placed in the espresso machine and twenty-five to thirty seconds of extraction time is provided. In the case of milk-based drinks, whole milk is steamed to the desired temperature with microfoam texture being produced. Depending on the recipe of the beverage, espresso is mixed with steamed milk or any other ingredients. Toppings, syrups or garnishes are optional and added depending on the customer preference and the normal recipes.

Procedure Steps: Quality Control and Delivery

A visual quality check is done to confirm that the beverage looks, measures the right amount of volume, and has the correct presentation before being handed over to the customer. Drinks that do not meet the quality standards are re-prepared instantly to ensure that the company does not lose its reputation of being the best. The final product is the beverage, which is passed to the customer and the correctness of orders is verified. POS system captures the time when the order is complete, which will be used to calculate the overall order delivery time (Scheucher et al., 2022).

Statistical Data Analysis for Process Changes

Process Centering Analysis

The process of making beverage shows that there is proper centering with a mean service time of 2.478 minutes. The acceptable range limits are 2.50 minutes at which the target specification midpoint is set. The process mean has only a deviation of 0.022 minutes compared to the target and, therefore, the overall centering performance is excellently high. This negligible variation indicates that the process is running close to the desired central value at a given time.

Process Capability Assessment at Three-Sigma

The process capability index (Cpk) is determined as 0.2699 which is much lower than the industry standard of 1.33. The potential capability (Cp) is 0.2823, which implies that the range of specifications is too small to vary. Cpu (0.2948) and Cpl (0.2699) are both significantly lower than reasonable capability values that need urgent remedies. The process is not conclusively capable at the three-sigma level and specially generates defects that are even beyond specifications regularly.

Statistical Control Chart Evaluation

Analysis of individual control chart does not show any data outside the upper (4.0694 minutes) and lower (0.8866 minutes) control limits. Nevertheless, the process shows eight successive observations at one side of the center line which contravene the rules of control. This trend signifies special cause variation that needs an investigation even though the points do not go beyond three-sigma control limits. This has led to the process being out of statistical control since the run patterns are not random.

Variation and Standard Deviation Analysis

The standard deviation of the known process of 0.5903 minutes is quite broad variation when compared to specification tolerance. The sample standard deviation is 0.5910 minutes, which is very close to the set standard process variability baseline. This great variability absorbs almost 60 percent of the range of specifications, constraining the process capability severely. Eliminating variation is a necessary requirement to attain decent process performance and customer satisfaction on a regular basis.

Specification Limits and Performance

There are lower and upper specification limits of 2.00 and 3.00 minutes respectively that provide one-minute tolerance. The specification range is seen to be insufficient considering the present variation of the process of about 0.59 minutes standard deviation. The specification range of 2-3 minutes is currently considered acceptable with most observations observed at rates of about 32 percent. This performance shows that there are major problems in terms of quality that need emergency process improvement interventions and remedial measures.

Process Improvement Urgency

The statistical analysis shows conclusively that the preparation of the beverages needs significant enhancement on a variety of quality levels. This lack of combination with insufficient capacity, statistical volatility, and too much variation endangers operational quality and contentment (Gomaa, 2025). Redesign of the process should aim at minimizing variation, eliminating special causes and possibly increasing specifications limits. This will require an immediate corrective measure to make sure that successful expansion to the second location is working.

Cause-and-Effect Analysis of Process Variances

The cause-and-effect diagram is a systematic process of identifying six key categories that cause beverage service time inconsistencies. Factors on manpower comprise variations in skills level, irregular training, employee exhaustion and learning curves of new employees. Causes associated with method include the lack of standardization of preparation procedures, ambiguous sequence of work, and ineffective workflow schemes on consistency. The machine variables include the age of espresso equipment, temperature variation, inconsistency of grinders, and insufficient preventive maintenance procedures (Kumah et al., 2024). Materials category deals with differences in coffee beans, milk temperature problems, inconsistencies in supply and stockout of inventory. The measurement issues involve the inaccuracy in time tracking, human error in measurement, and delays in recording the point- of- sale system. The management aspects include poor supervision, bad scheduling, lack of quality checks, and accountability.

Manpower and method categories can be analyzed, and it appears that they are the largest sources of service time variation. The variation of the level of skill among the baristas produces significant differences in the speed of preparation and quality of the drinks. The absence of standard processes allows every person to interpret the preparation steps in their own way, which is a direct cause of inconsistencies in time (Nahar et al., 2022). These problems are exacerbated by equipment related aspects such as temperature control problems and drift of grinder calibration over time. All these factors are interdependent, which makes the variances pattern complicated and needs a complex intervention approach that will deal with various groups.

Figure 2

Cause-and-Effect Diagram: Beverage Service Time Variation

Quality and Customer Service Improvement Recommendations

Reinforce visual work instructions as a part of comprehensive standardized operating procedures to decrease the variation by 40 percent that is associated with the method. Institute compulsory certification program for baristas who undergo test of competency in extraction of espressos, milk steaming and quality verification standards. Install mechanical dosing and grinding machines to reduce machine errors and enhance predictability of preparation time. Increase the range of specifications to 1.5-3.5 minutes and at the same time, decrease the variation in the process using the intentional training intervention (Nguyen et al., 2021). These enhancements focus on root causes as found in statistical analysis to improve capability and control. The introduction of real-time performance dashboards will also allow instituting corrective steps immediately in case of service time variances to the targets.

Immediate training standardization and procedure documentation should be prioritized before opening the second locations to ensure that the operations are standard. To eradicate the temperature and grinding variation in machines invest in preventive maintenance schedules and equipment upgrades. Introduce daily quality inspection and supervisor checking procedures as control measures to ensure accountability and discipline to the process (Lima et al., 2025). All these recommendations focus on the poor value of Cpk of 0.2699 which needs improvement to 1.33 minimum. Estimated cost of implementation of 15,000-25,000 will have high returns in terms of wastage minimization and satisfaction. Such success indicators are 95 percent first-time quality and the stable service times of 2.5 minutes on average.

Conclusion

The statistical analysis proves that the preparation process of beverages in Wild Dog Coffee Company needs to be vastly improved prior to the successful expansion. The lack of process capability, statistical instability, and too much variation endangers operational excellence and profitability. The recommended standardization, training and equipment improvement will be used to develop the basis of consistent and high quality service. These are the strategic interventions that make the second location follow in the footsteps of the first location without losing the competitive advantage and reputation.

Step-By-Step Instructions To Write MBA FPX 5016 Assessment 1 Process Improvement Plan

Instructions for MBA FPX 5016 Assessment 1 Process Improvement Plan will be added soon.

References for MBA FPX 5016 Assessment 1 Process Improvement Plan

  • You can use these references for your assessment.

Gomaa, A. H. (2025). Achieving operational excellence in manufacturing supply chains using lean six sigma: A case study approach. International Journal of Lean Six Sigma. https://doi.org/10.1108/ijlss-03-2024-0045

Kumah, A., Nwogu, C. N., Issah, A.-R., Obot, E., Kanamitie, D. T., Sifa, J. S., & Aidoo, L. A. (2024). Cause-and-effect (Fishbone) diagram: A tool for generating and organizing quality improvement ideas. Innovations Journals7(2), 85–87. https://doi.org/10.36401/JQSH-23-42

Lima, A. B. S. de, Becerra, C. E. T., Feitosa, A. D., Albuquerque, A. P. G. de, Melo, F. J. C. de, & Medeiros, D. D. de. (2025). Effective practices for implementing quality control circles aligned with ISO quality standards: Insights from employees and managers in the food industry. Standards5(1), e6. https://doi.org/10.3390/standards5010006

Nahar, N., Zhou, S., Lewis, G., & Kästner, C. (2022). Collaboration challenges in building ML-enabled systems. Proceedings of the 44th International Conference on Software Engineering. https://doi.org/10.1145/3510003.3510209

Nguyen, T., Quach, S., & Thaichon, P. (2021). The effect of AI quality on customer experience and brand relationship. Journal of Consumer Behaviour21(3). https://doi.org/10.1002/cb.1974

Rogalewicz, M., Kujawińska, A., & Feledziak, A. (2023). Ensuring the reliability and reduction of quality control costs by minimizing process variability. Eksploatacja I Niezawodność25(2). https://doi.org/10.17531/ein/162626

Scheucher, M., Hörandner, L., & Brandtner, P. (2022). Digitalization at the point-of-sale in grocery retail – State of the art of smart shelf technology and application scenarios. Procedia Computer Science196(1), 77–84. https://doi.org/10.1016/j.procs.2021.11.075

Taifa, I. W. R., Makundi, E. D., & Mwaluko, G. S. (2021). Production quality improvement for the soft drinks bottling industry through six sigma methodology. International Journal of Industrial and Systems Engineering39(4), e536. https://doi.org/10.1504/ijise.2021.120628

Vasudevan, S., & Chengaiyan, J. G. (2024). Ensuring beverage excellence: A quality control guide. Food Science and Engineering, 38–53. https://doi.org/10.37256/fse.6120255189

Do you need a tutor to help with this paper for you with in 24 hours.






    Privacy Policy & SMS Terms And Conditions







      Fill Form To Get Help!
      Please Fill The Following To Resume Reading





        Scroll to Top