Customer dissatisfaction

There are important economic consequences of a process being out of control for example, product waste and customer dissatisfaction. Hence, statistical process control does provide a way to continuously monitor process performance and improve product quahty. A typic process may go out of control due to several reasons, including... 

In addition to the direct operating quality costs, the indirect quality costs and their effect on the total cost curve must be considered. Indirect quality costs can be divided into three categories customer-incurred quality costs, customer-dissatisfaction quality costs, and loss-of-reputation costs. These... 

There are a variety of reasons for managing inventory, including the need to keep costs at a minimum and to have a sufficient supply of producfs for good customer service. Too much inventory results in loss of profifs because producfs remain on fhe shelf and do nof generate cash flow. Too liffle inventory can resulf in customer dissatisfaction and employee frustia-tion because needed producfs are not available. 

Customer dissatisfaction is one of the hardest costs to determine, but the most easily observable. Customers expect that products typically held by a pharmacy are readily available for purchase during normal business hours. Stockouts often produce frustrabon and dissatisfaction among customers, but, if infrequent, may be forgiven. However, frequent stockouts can result in a loss of business. In hospitals, frequent stockouts of commonly used products can result in a decline in the quality of patient care, create frustration among the medical and nursing staffs, and promote dissension between the pharmacy and other staffs. 

Even when it s not a life-or-death situation, variation leads to customer dissatisfaction and the inability to reliably meet performance and perception expectations (see Technique 30). As you near the completion of your innovative solution design, you can use MSA to identify and correct measurement system error, resulting in a higher quality, more reliable design. To be successful with MSA, you will need some experience with statistics. 

Scenario In the DVD-by-mail example from the Cause Effect Diagram (Technique 53), we looked for the root causes (inputs) contributing to customer dissatisfaction. We can also use a Cause Effect Matrix to discover... 

Too little attention is usually paid to this important area of packaging. If the transit packaging is poorly designed then the product will not reach the market in usable condition. This automatically puts up costs and leads to intense customer dissatisfaction. There are several types and structures of boards for casing. 

Type C deficiency results from customers making compromises between their real requirements and existing SKUs (stock keeping units), that is, what is available on the shelf or in the catalogue. Although these compromises are usually not explicit and are difficult to capture, they lead to customer dissatisfaction, reduce wiUingness to make future purchases, and erode the competitiveness of a company. 

A Fortune 500 insurance company decided to reengineer its death claims process in order to reduce cycle time, cost, and customer dissatisfaction. Initially, a design team was formed and customer and process data were analyzed. Two important discoveries were made in this phase that would have significant bearing on the final solutions that were developed. First, a mismatch was discovered between the actual cycle time of the claim process and the cycle time deemed acceptable to the customer. Second, because of the inability of the company to provide customer data visibility to aU units of the company, many opportunities—totaling hundreds of millions of dollars—were not being captured by the company. 

Uncertainty breeds inventory. Managers involved in transportation often have to make planning decisions, like routing, that directly affect the movement of raw materials or finished goods. These decisions often affect other components in the supply chain network, in which case the transportation management team cannot afford to make an incorrect decision. Consequently, any mistakes not only jeopardize other elements within the system but also lead to customer dissatisfaction created by the delay in the delivery times (Quirm 1998). 

The expression "plastic age" which is frequently used to describe the present era, has a connotation of continuous and wasteful acquisition of new objects. There is a popular belief that manufacturers are consciously building obsolescence into their products, and deliberately promoting customer dissatisfaction with existing products by introducing needless innovations [27, 30]. The issue of life extension is receiving increased attention. But can the demand for new products and the quantity of discarded products be decreased by extending the lifespan of a product ITKe "built-in" durability provided by the manufacturer is not a guarantee for a certain calculated life products can be retired from service for several other reasons than normal wear and tear, such as [31, 32] ... 

Deming proceeded to destroy every important notion of management I had been taught. He showed me that the important things I had learned in business school were wrong. Not only were they wrong, but they led to inferior results, poor quality, and customer dissatisfaction [p. xi]. 

Baker and Scudder, 1990). In a JIT enviromnent, both earliness and tardiness must be discouraged, since jobs finished early increase inventory cost while late jobs lead to customers dissatisfaction and loss of business goodwill. Thus an ideal schedule is one in which all jobs finish within the assigned due dates. The objectives of early/tardy (E/T) scheduhng could be interpreted in different ways, for example minimizing total absolute deviation from due dates, job-dependent earhness and tardiness penalties, non-linear penalties, and so forth (see Baker and Scudder, 1990 for a comprehensive survey). 

To this aim we will apply the function called Tauchi s Function Loss (1989) that suggests that the non-performance from target values produces quality losses financially due to customer dissatisfaction as a quadratic or parabolic curve. This estimation could be employed to include the losses of Failure as ... 

Tsikriktsis, N., Heineke, J. (2004). The impact of process variation on customer dissatisfaction Evidence from the U.S. domestic airline industry. Decision Sciences, 35(1), 129-142. 

Failure wiU result in customer dissatisfaction and aimoyance and/or slight deterioration of part or system performance. 

Failure wiU result in high degree of customer dissatisfaction and cause nonfunctionality of the system. 

Failure will result in major customer dissatisfaction and cause non-system operation or non-compliance with government regulations. 

Because a process that is out of control can have important economic consequences, such as product waste and customer dissatisfaction, it is important to keep track of the state of the process. Statistical process control provides a convenient method to continuously monitor process performance and product quality. However, it differs from automatic process control (such as feedback control) in that it serves as an indicator that the process is not operating within normal parameters. SPC does not automatically provide a controller setting that will bring the process back to its desired operating point or target. 

Quality-assurance procedures on manufactured products nearly always require confirmation that active levels are within specification, because an out-of-specification product may result in needlessly high production costs, customer dissatisfaction or even legal action. Sometimes it may be necessary to confirm that the composition complies with the demands of legislation, and it seems likely that this need will increase with the passage of time. And when things go wrong with a production process, trouble-shooters will not get very far unless they can call upon first-class analytical support. 

FAULT CAUSES GREAT DETERIORATION OF SYSTEM /PRODUCT PERFORMANCE. INCLUDING IZ B NON FUNCTIONING/ INOPERABLE. HIGH CUSTOMER DISSATISFACTION. EVEN MAY CALL EOR... 

As established by the predecessor military standards, process indicators are not intended to be reworked or even dispositioned, and they can be included in product delivery without correction of the product. They are, however, not desirable and indicate the relative success of the process and materials if the process or materials could lead to defect conditions, the process may need to be adjusted or corrected for future production. Process indicators should be monitored as part of the process control system. Should the number of process indicators indicate abnormal variation in the process or identify an undesirable trend, the process should be analyzed. This analysis may result in action to reduce the variation and improve yields before there is a defect trend that may require rework or scrap or, worst of all, result in customer dissatisfaction. 

In our production environments there are four different levels of quality (see Chart 8.13). Unfortunately, we find that most of U.S. industry falls into one of the first two levels, where inspection and quality certification occur with the customer or at some other point at the end of the production process. This is unfortunate for many reasons. With level one and two, we often find that an extensive amount of unnecessary effort has been used to produce parts, and this effort could have been saved if the error had been caught earlier in the process. In addition, catching the problem late often means that the cost of rework is much higher. This failure to catch the problem earlier may also cause extensive customer dissatisfaction or frustration. 

Handovers may lead to cut calls, which in turn can lead to customer dissatisfaction. Knowing the probability of escapes from cells is therefore one of the key aspects of wireless network management. Our aim in this work is to show very simply how to compute this probability of escape, which depends on the geometry of the cell, for several regular polygons, which as can be used for a two-dimensional covering. 

Pakdil F., Ozkok O., Dengiz B., Kara I., Selvi N. Kargi A. 2009. A systematic approach to reduce human and systemrelated errors causing customer dissatisfaction in a production environment, Total Quality Management Business Excellence, 20 1, 129137, DOI 10.1080/14783360802351728. 

---