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Process Improvement Plan

A process can be defined as a series of steps undertaken to achieve an outcome (Agarwal et al. , 2006). In terms of businesses, it can refer to business activities conducted to achieve an end goal like customer satisfaction. The thing about processes is that there will always be some inputs and some predetermined outputs. The inputs are passed through numerous variables in the process, and then result in the outcome. The variables involved in a process influence the result, speed, accuracy and quality of the outcome.

Process improvement is the method of identifying and analyzing a process, and then suggesting a better way for that process (Clark & Johnston, 2008). Many business concepts can be applied to daily life (Stevenson, 2008). As many of us have a specific process of doing some things, in this paper I’ll discuss a process that I conduct daily but would like to spend less time in doing so. I will utilize the flow chart design to analyze my process of getting ready for work, and then suggest a better one. In the process, I will discuss the effects of seasonal factors on it, and analyze the control limits.

I’ve used Microsoft excel to develop the

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flowchart. There are many different factors and variables that are influencing the process of going to work. The tasks involved in the process of going to work includes waking up, taking a shower, shaving, brushing the teeth, ironing the clothes, cooking breakfast, getting dressed, and finally leaving for work. The process is divided into specific tasks, and the time they take so as to properly measure them, and identify an area of improvement. For example, if I’m taking five minutes to brush my teeth, then it can be reduced to two minutes to save time.

To measure the process, I’ve used time (in minutes) as the metric. For the sake of simplicity, I’ve assumed that the process starts immediately when I wake up, and ends when I leave the house. Hence, the minutes I waste in bed snoozing a while will affect the speed of the process. Furthermore, unexpected things like burning the breakfast or slipping in the shower will also affect the speed and quality of the process. The change in the process was brought about by the process of elimination. I identified the items which were taking up much of my time, and were in fact unnecessary.

For example, instead of ironing the shirt in the morning, I did them in the night. Similarly, I would polish my shoes during the night. Another thing I did was eliminate breakfast altogether. I realized that a heavy dinner made up for the breakfast, and just a glass of juice would suffice. Another change brought about in the process was to shower and brush my teeth at the same time. The last change brought about in the process was to organize my clothes in the night, rather than deciding what to wear in the morning. The following chart shows the data collected before and after the change of the process.

Initial Process Changed Process Days Time Taken (min) Time Taken (min) Monday 58 45 Tuesday 54 35 Wednesday 60 30 Thursday 50 30 Friday 50 30 The chart shows that the process has clearly improved by implementing these measures. Statistically, the mean of the initial timing was 54. 4 minutes, while the mean for the changed and improved process was 34 minutes. The mean was calculated by adding up the minutes of each day and then dividing them with the number of days, which are five. The range of the process design was calculated to be 20. 4.

The range is calculated by determining the mean fro both the processes, and by subtracting the largest measurement from the smallest measurement. After calculating the mean and the range, a control chart can be made by determining the upper and lower limit. Both these measurements can be used to show the variation in the process. To calculate the confidence interval of the data, the standard deviation needs to be calculated. The standard deviation for the initial process is 4. 56, while the standard deviation for the changed process is 6. 52. The confidence interval is a useful tool for determining how reliable a process is.

The standard deviation shows that the changed process is much less reliable as there is more variation in the time than in the initial process. This greater variation may be explained by the fact that I haven’t gotten used to the new process yet. Perhaps, it might take me two more weeks to get used to the new changed process because of which there is why there is a large variation. Another explanation could be that the sample size is currently too small. I’ll have to collect more data to come to a definite conclusion that the new process is better.

It should be noted that some seasonal factors also influence the speed, accuracy and quality of the process. For example, day light savings would affect the performance of the process. Depending on the adjustments made, the sleep pattern of a person is influenced. A person is forced to wake up early if the time goes back an hour. This makes the person lethargic initially as he’s unable to get his full sleep. In a few days, however, the body does get used to the new timings. In conclusion, statistical analysis can be used to identify and analyze the parts that can be eliminated or merged with others to improve the process.

The process improvement plan was a success as I’ve been able to save 15 minutes of my time by improving the process by which I used to get ready to go to work. References Agarwal, N. K. , Aquilano, N. J. , Chase, R. B. , & Jacobs, F. R. (2006). Operations Management for Competitive Advantage (11th ed. ). New York, NY: The Mcgraw-Hill. Clark, G. , & Johnston, R. (2008). Service Operations Management (3 ed. ). Alexandria, VA: Prentice Hall. Stevenson, W. J. (2008). Operations Management (10 ed. ). New York: McGraw-Hill.

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