【校稿任务】第二十二 Statistics Roundtable Complaint Department
本帖最后由 小编H 于 2011-9-1 13:10 编辑
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本文由yzz翻译:**
**Complaint Department
Statistical engineering expands sphere of influence
投诉部 统计工程的延伸**
by Lynne B. Hare
George: How are you doing, John?
John: I can’t complain.
George: Sounds like a complaint to me.
琳尼b .黑尔
乔治:你好吗,约翰?
约翰:我不能抱怨。
乔治:听起来像是抱怨我。
Perhaps you know what goes on in most corporate complaint departments. Given euphemistic names such as "consumer affairs" and "consumer response," their business is still the same. In most of them, telephone operators enjoy the happy task of answering phone calls from often-irate customers who are upset with what they’re getting for their money. Complaints come in from other sources as well—mostly letters or emails. With the publishing of 800-numbers on packages, websites and other sources of consumer interface, most complaints are received by phone.
也许你知道在大多数公司投诉部门的情况。它们被委婉地称为“客户事务部”和“客户处理部”,实际上工作仍是一样的。大多数接线员经常微笑接听那些愤怒客户打来的电话，他们为花冤枉钱而伤心不已。同样，投诉信息还来自于信件或电子邮件。尽管有800电子表格程序、网站和其他顾客反馈方式,电话还是主要投诉方式。
Trained as models of sympathy, operators make inquiries regarding the nature of the complaint. The first step is to douse the flames by apologizing. The real source of the irritation could be high heat and humidity, but they apologize anyway. Then the operators gather relevant information such as UPC, item size, color, SKU and the nature of the complaint, such as package damage or disappointing product performance.
经过培训，接待者询问一般情况并进行安慰。首先通过道歉熄灭客户抱怨的怒火。可能顾客怒火难熄,不管怎样还是道歉。然后收集与UPC、项目大小、颜色、包装和抱怨的实质的相关信息,比如包装损坏或产品性能令人失望等。
Operators cannot be expected to be technical experts in all product-related matters, so to carry out the consumer interface, they are often prompted by computer screens that guide inquiry while logging relevant data. Successful sessions end in soothed customer nerves and valuable corporate information, assuming the data are used properly. Doubtless, at day’s end, the operators are not in the mood to listen to their children’s complaints about homework.
接待者不是产品相关所有事宜的技术专家,所以面对顾客时,他们经常根据电脑屏幕提示进行询问并记录相关数据。成功的会面最终消除了客户的疑虑,收集了对公司有用的重要信息。毫无疑问,黎明时是没有心情听孩子们抱怨作业的。
Accumulated complaint data are used in various ways, depending on the corporation and the unit within it. Marketing staff want to know about product negatives, while manufacturing staff want to isolate quality problems so they can be reduced or eliminated.
公司不同，部门不同，利用所收集的投诉数据的的方式也不同。销售人员想了解产品的缺陷,然而生产人员则关注质量问题, 希望减少质量问题，甚至杜绝。
Some organizations publish internal tabulations arranged by product, manufacturing facility and type of complaint. Such tabulations can cause brain cramps. For most of us, eyes glaze over after the second page. When questioned about one such report’s use, a senior vice president was heard to confess that he circled the large numbers and threw the report in the waste basket. You just thought of a way to save a step, didn’t you?
一些公司按生产产品,生产设施和投诉类型建立内部表格。这样的表格将使思维受限。对我们大多数人来说,眼睛看到第二页后就表现的有些迟钝。听说一个高级副总裁当被问到怎样使用这样一个报告时,承认他把大量报告团成团扔在废纸篓里。你会有一个办法改变这个情况,不是吗?
Putting data to work
把数据用到工作中
How can data of this nature best be put to corporate advantage? A first concern should be data quality control. Are the data reasonably representative of the complaining population to which inference is being made? If not, any effort to make sense out of them is doomed.
怎样才能让这些原始数据更好地发挥作用?首先考虑的应该是数据质量的控制。能够判定数据真正体现抱怨的真实情况吗?如果不能,那么任何努力都是徒劳的。
Not realizing the sweeping implications of its actions, one organization that was short of operators arranged for its telephone system to hang up on potential complainers after the 10th ring. Such practice renders summary statistics useless for the purposes of assessing consumer dissatisfaction, to say nothing about what it does to blister an already aggravated customer.
一个组织,不了解这种做法的重大的作用,就是十年以后，也很少安排通过电话系统，了解潜在的抱怨。用这种不切实际的总结统计方法评估消费者的不满是无用的,对一个非常已经不满的顾客，没有有任何作用。
After issues of data representation are resolved, you also might examine how the data are categorized and if the categories are mutually exclusive. Operators should be in synchrony with category definitions and bounds which, in turn, should include things likely to go wrong with the product and process, and should extend to be specific to differing product characteristics from one SKU to another.
数据表达问题解决以后,如果数据是相互独立的,你还可以对数据并进行分类。操作者应同时定义数据范围和界限,依次包括容易出错的产品和过程,还可以扩大到一个又一个仓储地的不同产品特性。
That stage being set provides more fertile ground for the sensible application of statistical thinking and methods directed toward greater customer satisfaction and productivity improvements.
这个阶段提供更丰富的资源，以便合理应用数理统计的思想和方法,使更多的客户满意，改进生产效率。
Make no mistake; the messages from consumers come much too late after the fact to exert a major role in the quality and productivity improvement processes. Certainly they are important, but other quality control techniques that are closer to the process are much sharper tools. Still, the data cannot and should not be ignored: They are often placed under the nose of the CEO, and that might be all the inspiration you need to take them seriously.
不要犯的错误; 已有消费者信息的过分滞后反馈，对质量和生产效率的提高有很大影响。这些当然都很重要,但是其他的质量控制技术更贴近过程，是更加锐利的武器。尽管如此,数据是不能忽视的:他们经常被送到CEO眼皮底下,而那可能是所有的精髓,你需要认真研究它们。
Consumer complaint data sets can be enormous and highly varied. There is enough work in their care and feeding to occupy the time and talents of at least one statistician, but there are not—nor will there ever be—enough statisticians to go around, given all the other expectations placed on them.
消费者投诉数据繁多且多变。这至少需要一个统计学家足够的关注和时间,他们承担着所有的期望，再多的统计也不显得多余。
Enter statistical engineering
进入统计工程
What to do? The principles of statistical engineering1 come to the rescue. Statisticians can and should work with those who own the problem to establish systems for complaint handling. A team might be composed of the head of the consumer complaint department, someone with strong programming skills, stakeholders from departments dependent on complaint reporting and, of course, a statistician.
怎么办呢?统计工程能解决这个问题。 统计学家们能够并且应该就存在问题建立投诉问题处理系统。一个团队可能包括：典型投诉的顾客,编程高手,相关信访部门,当然,还包括一个统计学家。
Together, they plan the generation of informative reports tailored to fit organizational needs. Typical among these needs are:
总之,他们为满足组织的需要做出信息报告。这些典型的需要有:
• The need to detect important changes and trends.
•需要找出重要的变革和发展趋势。
• The need to recognize improvement when it occurs.
需要确认所发生的改进。
• The need to avoid inundation by tables of data containing no important information.
需要避免数据表泛滥，包含任何重要信息。
Given these needs, an exception report—a document that alerts users of important events and doesn’t bother them otherwise—would seem appropriate. A report of this nature might be generated by tracking complaints over time, modeling them to learn of their baseline variability and informing users whenever complaint numbers wander beyond the bounds of expectation.
鉴于这些需要,一个特殊报告（一个提醒用户的重要情况但又不带来麻烦的文件）是很适用的。自始至终跟踪投诉，将形成一份报告,建立模型以了解他们变动的底线，及顾客抱怨超出了预想的数量范围。
Those well versed in tools common to statistical quality control might be tempted to draw C-charts to track complaints. Put simply, the center line is the average number of complaints, , per reporting period (usually months), while the upper and lower limits are
那些熟悉掌握常见的统计质量控制工具的人可能试图用C-图跟踪投诉。简言之,中线是平均投诉量，申报期 (通常是月),是上下限,
We don’t say this very much in polite company, but the assumption here is that complaints are Poisson distributed, which in turn assumes that:
我们不要说这个公司很正规,这里假定投诉符合泊松分布,相反:
• The probability of a complaint is proportional to the length of the reporting period.
•投诉机率与投诉报告间隔时间成正比。
• The probability of multiple complaints occurring at the same time is negligible.
•同一时间多人都抱怨的机率可以忽略不计。
• The probability of a complaint is consistent from interval to interval.
投诉的时间间隔是一致的。
• The probability of a complaint in one time period is independent of the probability of a complaint in another time period.
•每个时期的投诉机率是相对独立的。
Right off the bat, you can see the first assumption is not likely to be true because product exposure to the market changes from month to month. One month, sales might be high; the next, low. An effective solution is to substitute the C-chart with a U-chart to track complaints per million customer units sold.
凭心而论,你能发现第一假设可能不正确,因为产品根据市场变化逐月暴露问题。第一个月,销售可能高;第二个月,销售可能低。一个有效的解决办法是用U-图替代C-图来跟踪客户每百万销售单元的投诉。
The U-chart (Figure 1) sets as its center line the average number of complaints over a reasonably long reporting period, such as 24 or 36 months, divided by the average monthly sales for that same period. Then, control limits vary depending on the sales for the month in question. They are calculated as , in which ni is the number of millions of customer units sold during the ith month.
这U-图(图1)中心线是在一个相当长统计周期的平均投诉数,如24或36个月(3年),除以每月同期平均销售数。然后,控制极限取决于月度销售。他们计算出,第一个月百万销售单元的投诉数。
The U-chart is an improvement over the C-chart for this application, but it is not without its problems. First, it is almost certainly true that the denominator—the sales data—represents shipments from a distribution center or a manufacturing facility. Unless the sales tracking system is up to date, perhaps representing cash- register sales, it does not actually reflect a given month’s sales.
这个U-图是在C-图基础上改进的一个应用,但是它并非无可挑剔。首先,几乎可以肯定的是 销售数据代表着从配送中心或制造方发货数量。 除非销售跟踪系统是最新的,销售回款记录可能并不是所指月销售的实际反映。
To overcome the problem of the lag between product distribution measured this way and actual consumption, some complaint tracking routines are written to lag and smooth the sales series. That manipulation may help stabilize the complaint rate series, but it also may cause problems with the assumption of independence (point No. 4 mentioned earlier
针对销售的延迟和正常发货提出了一些投诉跟踪流程,以解决销售分配和实际销量之间滞后这个问题。这样做可稳定抱怨率,同时还可使问题相对独立(前面第四点提到的)
There are other charting and modeling techniques that might be considered to overcome violations of underlying assumptions. Among these are the use of exponentially weighted moving average control charts and cumulative sum charts. Modeling could be generalized to autoregressive integrated moving average (ARIMA) models, seasonally adjusted as needed. For example, you might need seasonality for barbecue sauce and allergy medication complaints.
可能还有不违反基本假设的其他图形和模型。其中包括利用指数加权的均值移动控制图和金额累积图。模型可以根据周期性调整的需要，延伸到单值回归移动平均(ARIMA)模型。例如,你可能需要烤肉酱和抗过敏药物的周期性投诉。
The downside of ARIMA modeling is that the number of observations required for precise coefficient estimates is large—at least 100. Many complaint applications do not have that much history captured, and when they do, the history is not stable because of numerous market changes.
ARIMA模型的缺点的数量要求准确，需要数量估计至少有100。许多抱怨没有那么多的历史应用数据,当他们分析时,历史数据因为市场的大量变化而不稳定。
Trial run
试运行
Regardless of the charting method used, there is always a need for trial runs before a formal system is put in place. The trial runs should record what proportion of the charts trigger out-of-control messages. If there are too few, the system probably won’t provide information on important consumer issues. Too many, and the complaint department will be perceived as crying wolf. A healthy balance must be established so charts trigger action on the most important consumer issues. Control limit action rules can be adjusted to alter control chart vigilance.
无论使用什么方法的图表,正式运行前一定要试运行。试运行应该记录图表非受控信息。如果非受控信息太少,系统可能不会提供消费者的重要信息。非受控信息太多,投诉部门将被认为是瞎起哄。必须建立一个健全合理的对最重要的客户问题的反应机制。也可以通过调整行动控制界限来改变控制图中的警示。
There also will be a temptation to examine control charts at higher levels in the reporting hierarchy. For example, you might be interested in all complaints relating to a particular manufacturing facility. 也会有一种情况,使检查控制图报告的层次较高。例如,你可能会对与某一特定生产设施有关的所有的投诉感兴趣。
Users should be cautioned that such charts lack the power to detect differences that might be important to the organization because low complaint numbers will average out high numbers. The most informative and valid charts will be at the low levels of the data hierarchy because the assumption of a single Poisson mean is more likely to hold there.
用户应该注意，因为投诉数量少，平均数据高,这种图表检测不出可能对组织很重要的差异点。因为单项假设用泊松分布分析更适合，信息量大,且有效的图表数据等级将很低。
In complaint handling, as in most other potential statistical applications areas, organizational considerations extend far beyond statistics. Yet much of the underpinning technology is statistical. 在投诉的处理,还有很多其它潜在的统计应用领域，组织应做远远超出统计长远打算。但是大部分支持技术是统计。
Successful complaint handling systems depend on team efforts supported by the statistician. There is strong synergy to statistical engineering enterprises of this kind. Neither the statisticians nor the other team members can develop successful systems alone. But working together, they can create powerful management tools.
成功的投诉的处理系统依赖于统计员团队的工作支持。统计工程企业需要很强的协作精神。不管统计学家们还是其他团队，都不能独自成功开发系统。但共同努力,可以创建功能强大的管理工具。
Note
1。关于统计工程的更多内容,见“缩短差距” Roger W. Hoerl 和 Ronald D. Snee, Quality Progress、质量进步,2010年5月,页-。52-53。
Lynne B. Hare is a statistical consultant. He holds a doctorate in statistics from Rutgers University in New Brunswick, NJ. He is past chairman of the ASQ Statistics Division and a fellow of ASQ and the American Statistical Association.
琳尼b .黑尔是统计学顾问,泽西市新不伦瑞克区路特格大学的博士,曾是ASQ统计研究所原主席及美国ASQ统计协会成员。
请对以下文章有校对兴趣的组员留下你的预计完成时间，并发短信息联系小编H或者邮箱mailto:xbH@6sq.net**，以便小编登记校对者信息以及文章最终完成时的奖惩工作。
本文由yzz翻译:**
**Complaint Department
Statistical engineering expands sphere of influence
投诉部 统计工程的延伸**
by Lynne B. Hare
George: How are you doing, John?
John: I can’t complain.
George: Sounds like a complaint to me.
琳尼b .黑尔
乔治:你好吗,约翰?
约翰:我不能抱怨。
乔治:听起来像是抱怨我。
Perhaps you know what goes on in most corporate complaint departments. Given euphemistic names such as "consumer affairs" and "consumer response," their business is still the same. In most of them, telephone operators enjoy the happy task of answering phone calls from often-irate customers who are upset with what they’re getting for their money. Complaints come in from other sources as well—mostly letters or emails. With the publishing of 800-numbers on packages, websites and other sources of consumer interface, most complaints are received by phone.
也许你知道在大多数公司投诉部门的情况。它们被委婉地称为“客户事务部”和“客户处理部”,实际上工作仍是一样的。大多数接线员经常微笑接听那些愤怒客户打来的电话，他们为花冤枉钱而伤心不已。同样，投诉信息还来自于信件或电子邮件。尽管有800电子表格程序、网站和其他顾客反馈方式,电话还是主要投诉方式。
Trained as models of sympathy, operators make inquiries regarding the nature of the complaint. The first step is to douse the flames by apologizing. The real source of the irritation could be high heat and humidity, but they apologize anyway. Then the operators gather relevant information such as UPC, item size, color, SKU and the nature of the complaint, such as package damage or disappointing product performance.
经过培训，接待者询问一般情况并进行安慰。首先通过道歉熄灭客户抱怨的怒火。可能顾客怒火难熄,不管怎样还是道歉。然后收集与UPC、项目大小、颜色、包装和抱怨的实质的相关信息,比如包装损坏或产品性能令人失望等。
Operators cannot be expected to be technical experts in all product-related matters, so to carry out the consumer interface, they are often prompted by computer screens that guide inquiry while logging relevant data. Successful sessions end in soothed customer nerves and valuable corporate information, assuming the data are used properly. Doubtless, at day’s end, the operators are not in the mood to listen to their children’s complaints about homework.
接待者不是产品相关所有事宜的技术专家,所以面对顾客时,他们经常根据电脑屏幕提示进行询问并记录相关数据。成功的会面最终消除了客户的疑虑,收集了对公司有用的重要信息。毫无疑问,黎明时是没有心情听孩子们抱怨作业的。
Accumulated complaint data are used in various ways, depending on the corporation and the unit within it. Marketing staff want to know about product negatives, while manufacturing staff want to isolate quality problems so they can be reduced or eliminated.
公司不同，部门不同，利用所收集的投诉数据的的方式也不同。销售人员想了解产品的缺陷,然而生产人员则关注质量问题, 希望减少质量问题，甚至杜绝。
Some organizations publish internal tabulations arranged by product, manufacturing facility and type of complaint. Such tabulations can cause brain cramps. For most of us, eyes glaze over after the second page. When questioned about one such report’s use, a senior vice president was heard to confess that he circled the large numbers and threw the report in the waste basket. You just thought of a way to save a step, didn’t you?
一些公司按生产产品,生产设施和投诉类型建立内部表格。这样的表格将使思维受限。对我们大多数人来说,眼睛看到第二页后就表现的有些迟钝。听说一个高级副总裁当被问到怎样使用这样一个报告时,承认他把大量报告团成团扔在废纸篓里。你会有一个办法改变这个情况,不是吗?
Putting data to work
把数据用到工作中
How can data of this nature best be put to corporate advantage? A first concern should be data quality control. Are the data reasonably representative of the complaining population to which inference is being made? If not, any effort to make sense out of them is doomed.
怎样才能让这些原始数据更好地发挥作用?首先考虑的应该是数据质量的控制。能够判定数据真正体现抱怨的真实情况吗?如果不能,那么任何努力都是徒劳的。
Not realizing the sweeping implications of its actions, one organization that was short of operators arranged for its telephone system to hang up on potential complainers after the 10th ring. Such practice renders summary statistics useless for the purposes of assessing consumer dissatisfaction, to say nothing about what it does to blister an already aggravated customer.
一个组织,不了解这种做法的重大的作用,就是十年以后，也很少安排通过电话系统，了解潜在的抱怨。用这种不切实际的总结统计方法评估消费者的不满是无用的,对一个非常已经不满的顾客，没有有任何作用。
After issues of data representation are resolved, you also might examine how the data are categorized and if the categories are mutually exclusive. Operators should be in synchrony with category definitions and bounds which, in turn, should include things likely to go wrong with the product and process, and should extend to be specific to differing product characteristics from one SKU to another.
数据表达问题解决以后,如果数据是相互独立的,你还可以对数据并进行分类。操作者应同时定义数据范围和界限,依次包括容易出错的产品和过程,还可以扩大到一个又一个仓储地的不同产品特性。
That stage being set provides more fertile ground for the sensible application of statistical thinking and methods directed toward greater customer satisfaction and productivity improvements.
这个阶段提供更丰富的资源，以便合理应用数理统计的思想和方法,使更多的客户满意，改进生产效率。
Make no mistake; the messages from consumers come much too late after the fact to exert a major role in the quality and productivity improvement processes. Certainly they are important, but other quality control techniques that are closer to the process are much sharper tools. Still, the data cannot and should not be ignored: They are often placed under the nose of the CEO, and that might be all the inspiration you need to take them seriously.
不要犯的错误; 已有消费者信息的过分滞后反馈，对质量和生产效率的提高有很大影响。这些当然都很重要,但是其他的质量控制技术更贴近过程，是更加锐利的武器。尽管如此,数据是不能忽视的:他们经常被送到CEO眼皮底下,而那可能是所有的精髓,你需要认真研究它们。
Consumer complaint data sets can be enormous and highly varied. There is enough work in their care and feeding to occupy the time and talents of at least one statistician, but there are not—nor will there ever be—enough statisticians to go around, given all the other expectations placed on them.
消费者投诉数据繁多且多变。这至少需要一个统计学家足够的关注和时间,他们承担着所有的期望，再多的统计也不显得多余。
Enter statistical engineering
进入统计工程
What to do? The principles of statistical engineering1 come to the rescue. Statisticians can and should work with those who own the problem to establish systems for complaint handling. A team might be composed of the head of the consumer complaint department, someone with strong programming skills, stakeholders from departments dependent on complaint reporting and, of course, a statistician.
怎么办呢?统计工程能解决这个问题。 统计学家们能够并且应该就存在问题建立投诉问题处理系统。一个团队可能包括：典型投诉的顾客,编程高手,相关信访部门,当然,还包括一个统计学家。
Together, they plan the generation of informative reports tailored to fit organizational needs. Typical among these needs are:
总之,他们为满足组织的需要做出信息报告。这些典型的需要有:
• The need to detect important changes and trends.
•需要找出重要的变革和发展趋势。
• The need to recognize improvement when it occurs.
需要确认所发生的改进。
• The need to avoid inundation by tables of data containing no important information.
需要避免数据表泛滥，包含任何重要信息。
Given these needs, an exception report—a document that alerts users of important events and doesn’t bother them otherwise—would seem appropriate. A report of this nature might be generated by tracking complaints over time, modeling them to learn of their baseline variability and informing users whenever complaint numbers wander beyond the bounds of expectation.
鉴于这些需要,一个特殊报告（一个提醒用户的重要情况但又不带来麻烦的文件）是很适用的。自始至终跟踪投诉，将形成一份报告,建立模型以了解他们变动的底线，及顾客抱怨超出了预想的数量范围。
Those well versed in tools common to statistical quality control might be tempted to draw C-charts to track complaints. Put simply, the center line is the average number of complaints, , per reporting period (usually months), while the upper and lower limits are
那些熟悉掌握常见的统计质量控制工具的人可能试图用C-图跟踪投诉。简言之,中线是平均投诉量，申报期 (通常是月),是上下限,
We don’t say this very much in polite company, but the assumption here is that complaints are Poisson distributed, which in turn assumes that:
我们不要说这个公司很正规,这里假定投诉符合泊松分布,相反:
• The probability of a complaint is proportional to the length of the reporting period.
•投诉机率与投诉报告间隔时间成正比。
• The probability of multiple complaints occurring at the same time is negligible.
•同一时间多人都抱怨的机率可以忽略不计。
• The probability of a complaint is consistent from interval to interval.
投诉的时间间隔是一致的。
• The probability of a complaint in one time period is independent of the probability of a complaint in another time period.
•每个时期的投诉机率是相对独立的。
Right off the bat, you can see the first assumption is not likely to be true because product exposure to the market changes from month to month. One month, sales might be high; the next, low. An effective solution is to substitute the C-chart with a U-chart to track complaints per million customer units sold.
凭心而论,你能发现第一假设可能不正确,因为产品根据市场变化逐月暴露问题。第一个月,销售可能高;第二个月,销售可能低。一个有效的解决办法是用U-图替代C-图来跟踪客户每百万销售单元的投诉。
The U-chart (Figure 1) sets as its center line the average number of complaints over a reasonably long reporting period, such as 24 or 36 months, divided by the average monthly sales for that same period. Then, control limits vary depending on the sales for the month in question. They are calculated as , in which ni is the number of millions of customer units sold during the ith month.
这U-图(图1)中心线是在一个相当长统计周期的平均投诉数,如24或36个月(3年),除以每月同期平均销售数。然后,控制极限取决于月度销售。他们计算出,第一个月百万销售单元的投诉数。
The U-chart is an improvement over the C-chart for this application, but it is not without its problems. First, it is almost certainly true that the denominator—the sales data—represents shipments from a distribution center or a manufacturing facility. Unless the sales tracking system is up to date, perhaps representing cash- register sales, it does not actually reflect a given month’s sales.
这个U-图是在C-图基础上改进的一个应用,但是它并非无可挑剔。首先,几乎可以肯定的是 销售数据代表着从配送中心或制造方发货数量。 除非销售跟踪系统是最新的,销售回款记录可能并不是所指月销售的实际反映。
To overcome the problem of the lag between product distribution measured this way and actual consumption, some complaint tracking routines are written to lag and smooth the sales series. That manipulation may help stabilize the complaint rate series, but it also may cause problems with the assumption of independence (point No. 4 mentioned earlier
针对销售的延迟和正常发货提出了一些投诉跟踪流程,以解决销售分配和实际销量之间滞后这个问题。这样做可稳定抱怨率,同时还可使问题相对独立(前面第四点提到的)
There are other charting and modeling techniques that might be considered to overcome violations of underlying assumptions. Among these are the use of exponentially weighted moving average control charts and cumulative sum charts. Modeling could be generalized to autoregressive integrated moving average (ARIMA) models, seasonally adjusted as needed. For example, you might need seasonality for barbecue sauce and allergy medication complaints.
可能还有不违反基本假设的其他图形和模型。其中包括利用指数加权的均值移动控制图和金额累积图。模型可以根据周期性调整的需要，延伸到单值回归移动平均(ARIMA)模型。例如,你可能需要烤肉酱和抗过敏药物的周期性投诉。
The downside of ARIMA modeling is that the number of observations required for precise coefficient estimates is large—at least 100. Many complaint applications do not have that much history captured, and when they do, the history is not stable because of numerous market changes.
ARIMA模型的缺点的数量要求准确，需要数量估计至少有100。许多抱怨没有那么多的历史应用数据,当他们分析时,历史数据因为市场的大量变化而不稳定。
Trial run
试运行
Regardless of the charting method used, there is always a need for trial runs before a formal system is put in place. The trial runs should record what proportion of the charts trigger out-of-control messages. If there are too few, the system probably won’t provide information on important consumer issues. Too many, and the complaint department will be perceived as crying wolf. A healthy balance must be established so charts trigger action on the most important consumer issues. Control limit action rules can be adjusted to alter control chart vigilance.
无论使用什么方法的图表,正式运行前一定要试运行。试运行应该记录图表非受控信息。如果非受控信息太少,系统可能不会提供消费者的重要信息。非受控信息太多,投诉部门将被认为是瞎起哄。必须建立一个健全合理的对最重要的客户问题的反应机制。也可以通过调整行动控制界限来改变控制图中的警示。
There also will be a temptation to examine control charts at higher levels in the reporting hierarchy. For example, you might be interested in all complaints relating to a particular manufacturing facility. 也会有一种情况,使检查控制图报告的层次较高。例如,你可能会对与某一特定生产设施有关的所有的投诉感兴趣。
Users should be cautioned that such charts lack the power to detect differences that might be important to the organization because low complaint numbers will average out high numbers. The most informative and valid charts will be at the low levels of the data hierarchy because the assumption of a single Poisson mean is more likely to hold there.
用户应该注意，因为投诉数量少，平均数据高,这种图表检测不出可能对组织很重要的差异点。因为单项假设用泊松分布分析更适合，信息量大,且有效的图表数据等级将很低。
In complaint handling, as in most other potential statistical applications areas, organizational considerations extend far beyond statistics. Yet much of the underpinning technology is statistical. 在投诉的处理,还有很多其它潜在的统计应用领域，组织应做远远超出统计长远打算。但是大部分支持技术是统计。
Successful complaint handling systems depend on team efforts supported by the statistician. There is strong synergy to statistical engineering enterprises of this kind. Neither the statisticians nor the other team members can develop successful systems alone. But working together, they can create powerful management tools.
成功的投诉的处理系统依赖于统计员团队的工作支持。统计工程企业需要很强的协作精神。不管统计学家们还是其他团队，都不能独自成功开发系统。但共同努力,可以创建功能强大的管理工具。
Note
- For more about statistical engineering, see "Closing the Gap," by Roger W. Hoerl and Ronald D. Snee, Quality Progress, May 2010, pp. 52–53.
1。关于统计工程的更多内容,见“缩短差距” Roger W. Hoerl 和 Ronald D. Snee, Quality Progress、质量进步,2010年5月,页-。52-53。
Lynne B. Hare is a statistical consultant. He holds a doctorate in statistics from Rutgers University in New Brunswick, NJ. He is past chairman of the ASQ Statistics Division and a fellow of ASQ and the American Statistical Association.
琳尼b .黑尔是统计学顾问,泽西市新不伦瑞克区路特格大学的博士,曾是ASQ统计研究所原主席及美国ASQ统计协会成员。
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