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To be able to attain maximum potential from a process there must be an effective monitoring and evaluation process that supervises the performance of the business process. A statistical process control comes in handy to perform this task so that the process maximizes the outputs (Aquilano, 2005). The measurable attributes characterize the Statistical Process Control where they may vary either naturally/common or assignably/special. The management must make sure that it tracks all the measurable attributes either natural or special to be able to avoid any bottlenecks or non-bottlenecks in the process but ensure a capacity constrained resource. Managers must also ensure that they are in control of the process so that any variations from the norm are identified and corrected in time.

The key steps involved in the statistical process control include identifying and getting familiar with the defined process, then identifying the measurable attributes in the defined process, defining the natural variation of the attributes (Goldratt, & Cox, 1992). Tracking variations in the process follows characterization which ensures that the management is in control, when in control then tracking must continue, but if not in control the assignable cause must be identified and removed to return the process back to the norm (Srikanth, & Umble, 1997).

The process in week one was the Hunan Express Delivery Process map which involves customers making food orders from phones until the food is delivered and payments are made. The bottlenecks identified in the order placement process seemed to turn the process into a bottleneck thus needed a statistical process control. The problems in the process included its slow mode and not meeting customers' expectations, repetitive information exchange from extensive and unnecessary phone communication and frequent incorrect orders that were caused by poor handwriting, inconsistent format, inconsistent order placement, incorrect delivery fee with respect to distance, and inaccurate radius method. The bottleneck was in the order placement from the time of answering a customer's phone call to thanking the customer and hanging up the phone.

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The problems of the delivery process were in the order placement section where there was inefficiency in that process that needed to be streamlined to make the process efficient. The total delivery time is calculated by adding the order placement time to preparing time and then to delivery time. I.e. Total deliver time= Order Placement Time + Prepare Time + Delivery Time

In this case the order placement has so many variations that translate to a higher total delivery time hence impacting on the profits negatively. The order placement time has its highest time to be 7.70 and it's lowest to be 1.32. This means that there is a very high variation in the process which must be checked. The orders taken in less time are delivered in a short time. The average total time in delivery is 24.07 and the average order placement time is 4.114 which must be reduced to ensure higher output. The average preparation and delivery time is 8.892 and 11.067 respectively. Reduction in the order placement time will reduce errors in the preparing and delivery hence reduces the time and this will contribute to reduced total delivery time.

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For a process improvement plan to happen; the set up time, processing time, queuing time, waiting time, and idle time must be effectively utilized effectively without any delays. The main variations that the problem has should be checked through setting limits to control them. This will be possible if management first conducts a capacity resource profile or apply the knowledge of the process, or even an actual participation in the order placement so as to establish the limits of time required (Aquilano, 2005). Supervisors and the workers will also help identify the variations and the correct periods of time required to take a single order in the efficient way.

Since the average order placement time is 4.114, this means setting limits with this time will be effective. The lower time limits should be set at the least time established when taking orders i.e. 1.32 while the higher time limits allowed for taking orders effectively will be 4.11.

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Figure 1; Showing how order placement varied

Setting upper limits for order placement will help reduce the total delivery time and hence better the output produced. Every minute reduced in order placement will be added for other production processes that translate to more output.

The business can work on the bottlenecks by establishing a customer profile that will have a database of the regular customers; this will eliminate questions like the phone number and address for the given customer if they are not yet changed. Customers will be allowed to change their profiles if need be to ensure they are served to satisfaction.

Codes for the orders need to be established to eliminate handwriting errors; the codes should denote specific food types or combination of foods that will be easily identified in the processing. The management should also set zones for delivery i.e. specific radius surrounding should be grouped into one zone that will ensure time is saved during delivery in zone identification. Staff training will be a seasonal factor in the process in view of the fact that they should be adequately trained to handle the order placement process effectively without creating bottlenecks.

Confidence intervals set for the control will allow for process improvement in that it will establish an expected error that the process can accommodate and evade bottlenecks (Aquilano, 2005). A 0.1 confidence interval is best since the data provided is specific and may be subject to varying. With an effective statistical process control the process improvement plan is guaranteed.

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