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2.2 B. Voice of the Customer

Business Process Management

2.1 Voice of the Customer


B. Voice of the Customer

1. Identifying the Customer

The customers are the main focus of any organization. It is very important to streamline the demands of the customers. Six Sigma is a useful tool in assessing customer satisfaction. Customer satisfaction not only rests in the quality of the product but also in such services as the ordering procedure, delivery, mode of payment and after sales. It is very important to make changes keeping the customers’ demand in mind. 

The data collected from customer satisfaction surveys are useful in determining customer demands and the performance of the product. This also helps the people working on the Six Sigma project because they are able to categorize the customers’ according to their needs. They do not share the same viewpoint about the product and its cost as the manufacturer or the service provider. So, it becomes very important to mould the policies according to the organization goals as well as the customers’ demands. 

A customer views a product from the point of view of its usefulness, price and quality. A product or a service has no relevance for the customer is not of any use for the organization. Customer satisfaction is the biggest accomplishment for any organization and without it; the Six Sigma project cannot achieve its desired end. 

Some organizations categorize the customers on the basis of their needs and roles they play in the organization. One of these categories of customers is who put in their money for upcoming projects of the organization. They are very important because they bring great value by investing a major chunk of the money. Customers also can be categorized in the form of small traders and businessmen. There are customers who might be good for an organization in the long term. It is important to value these customers also. 

The customers should be pampered so much that they do not feel the need to go to the competitor. It is very important to pay heed to each customer’s needs and he/she should be made to feel that he is important and his/her opinion is valued. His problem should be resolved at the first go in the best possible manner. If the customers know that they are valuable for the organization they would certainly help improve business and increase sales. 

Therefore, it is very important to identify the customer and his needs because it is the customer who is and will remain the core element for an organization in the long run. 

2. Collecting Customer Data

In today’s competitive scenario, it has become imperative to keep the customers happy and, therefore retain them in the long term. It is just not enough to take internal decisions. It is very important to capture the customer’s voice and hear his concerns also. Continuous interaction with the customer will help in building better relationships with them. 

The customer satisfaction is measured on such metrics as quality of the product, how many calls they make after they buy the product and the feedback they give. The feedback that the customers provide is an important metric and can be critical in improving the quality. The feedback can be measured in the form of interviews, customer satisfaction surveys, customer complaints and focus groups. The customer feedback is very essential because it helps in determining the loopholes and improving the performance of the employees. 

Quality Call Monitoring

Quality call monitoring is an important way to hear the voice of the customer. For instance, in a contact centre if an agent’s call is monitored, it means that his/her performance is being measured and at the same time it will also help to determine the pros and cons of certain processes and the customer satisfaction can be easily evaluated.

Kano Model

Kano model is another quality measurement technique to measure client happiness. It can be said to be a useful tool in evaluating and prioritizing customer requirements. Not all requirements are equally important to all customers, and the attribute of a product will be ranked differently by different customers in their need chart. Therefore this model is used to rank requirements according to the importance of each segment’s needs, which differentiates between must haves and differential attributes. 

Applying Kano model in the workplace to learn customer requirements will change the Black Belt’s viewpoint towards customer satisfaction. The team will be able to know which values and services the customer covets for the most, and how to plan for operations in the Six Sigma program. 

Product attributes can be classified as:

Basic/Threshold attributes: Threshold attributes are those whichthe customer normally assumes to be present in the product. Their absence will cause dissatisfaction among customers. However, the customer will remain neutral even if these attributes are provided in a better way. For example, refrigerators come with freezers and door handles. A sleeker handle or a frost-free freezer will not cause any more satisfaction in the customer. 

Performance/Linear attributes: The presence of performance attributes are directly proportional to customer satisfaction. There are high levels of satisfaction if their performance is high and dissatisfaction if their performance is low. For example, the time spent waiting in line at the check-in counter of an airport terminal. This attribute is represented as a linear and symmetric line in the graph. A high level of execution of these linear attributes can add to product competitiveness. 

Exciters/Delighters: These are hidden attributes which delight the customer and lead to high levels of satisfaction if they are present, but do not cause any dissatisfaction if the product lacks this feature.These ‘delighters’ are the surprise elements in the product and companies can use this attribute to set their product apart from their competitors. In course of time, as expectations rise, today’s delighter’s become tomorrow’s basics. For example, a car with an inbuilt television can be today’s delighter, but can be a basic tomorrow. 

In order to survive cut-throat competition, and to lead in the market, companies need to be constantly innovative and research what is the current level of customer quality to meet customer expectations. A higher grade of execution of performance attributes and inclusion of one or more delighters/exciters will provide stiff competition to similar players. 

In the figure below, the entire basic attribute curve lies in the lower half of the chart, indicative of neutrality even with improved execution, and dissatisfaction with their absence. The exciters curve lies entirely in the upper part of the graph. The more the exciters, the higher is the level of satisfaction. The performance attributes are shown as a 45° line passing through the center of the graph.





Sample Survey

Definition

Definition Another voice of customer tool or method for gathering customer feedback, are sample surveys. 

A set of written questions that is sent to a group of selected customers to obtain answers that will enable corporate decision making is called a sample survey. Data are collected from a sample of a universal population to reach a conclusion about the inherent features of the whole population. 

It is an important tool to determine which requirements are most important to the customer. 

The organization might interact with its customers to access the customer sensitivity to the company’s product, measure the quality of service or determine if the current level of quality is at par with the company’s identified goals. The organization might want to judge why employee behavior or morale is changing, what the customer’s buying experience is, or what the responses for a new product are. 

According to Thomas Pyzdek, ‘Sample surveys are usually used to answer descriptive questions (“How do things look?”) and normative questions (“How well do things compare with our requirements?”).’ 

It is not humanly and logistically possible to count everything that happens in a process. Sample surveys enable the process leader to collect the no-nonsense responses of the customer, analyze, and reach a conclusion from them. Sampling saves time and money and gives reliable data to analyze a problem. 

Determining what to measure: The first thing that needs to be decided in a sample survey is what to measure, or the population to be studied. . For example, a five star chain may want to measure the quality of food served in its 24 hour restaurant. The customer care division for a telecom brand may want to assess how the billing system can be made less erroneous. After this a sampling frame has to be set up. 

Determining the Margin of Error: The desired margin of error and confidence level has to be determined. (The concept of margin of error is elaborated below)

Selecting the sample size: The process team will decide on the sample that needs to be selected from the population. A sample is a subset of a universal population, like the number of night time customers out of the total customers in the round-the clock restaurant of a five star chain. 

The samples maybe randomly collected, which ensures that it is unbiased, and in which each element or respondent has an equal chance of occurrence. The sample may also be a representative sample which is a sample with an exact reflection of a larger population. To truly represent a population, the sampler and analyzer of data must take into consideration the variables like a diverse and changing population. 

Selecting a Sampling Method: The next step is to select the sampling method (For more information on Sampling Methods, see Chapter 5- Six Sigma, Measure) Sampling methods are simple random sampling, stratified sampling, clustered sampling, and systematic sampling etc. 

Make the sampling plan: The subsequent step is to document the sampling plan; this involves when and how to construct the survey. 

Selecting a Sampling Method: The next step is to select the sampling method (For more information on Sampling Methods, see Chapter 5- Six Sigma, Measure) Sampling methods are simple random sampling, stratified sampling, clustered sampling, and systematic sampling etc.

Survey Construction

1. The first important step in constructing a successful survey is to develop the measure of the survey. Measures of responses can be taken in the form of:

  • Open-ended questions- Here the respondents frame their own answers without any limitations
  • Ranking Questions- The response choices are ranked according to some criterion, like importance.
  • Fill-in-the blank questions
  • Yes/No questions
  • Likert’s scale- This response type is used to determine the strength of a response. Likert stated that a scale of 1 to 5 is better than a range of 1 to 10 because people tend to ignore larger ranges and hardly use the entire range of choices, and instead opt for very low ranges, like 1,2 or very high ranges like 9 or 10
  • Semantic differentials-This response type measures respondent’s choices in two bipolar values. The values than may lie between the two possible options are not stated. The values are usually two contrasting adjectives. For e.g. Very Good and very Bad


2. After selecting the sample, the next thing to be done is to design the samples. Sample design is determining how many persons or elements (respondents) are to be included in the survey to ensure the success of the survey. 

3. The next step would be to develop the questionnaire. A questionnaire must truly reflect the situation facing the company and be aimed to fulfill the goal of the survey. 

4. After that, the questionnaire is tested on a small sample, also known as a pilot study. This is done to test the accuracy and clarity of questions. 

5. Now the final questionnaire will be produced. 

6. This would be followed by preparation of mailing material and dispatching the same to the sample population. 

7. The next obvious step would be to collect the filled up questionnaires, also known as data. 

8. Data collected has to be collated and reduced to enable analysis. 

9. The last step would be to analyze this data.

Tactics to develop questions :

Surveys should be designed with the proper professional expertise or survey experience. Question framers should meticulously study the respondent group and ensure that the area under discussion is understood by the respondents so that they give appropriate responses. 

The format of the questions should be in line with the focus of the survey. The questions should be relevant, concise, and clear and in a language the respondent understands. 

To get unbiased answers, the question itself should be unbiased. The answer choices should be clear and mutually exclusive so that it becomes easy to understand and choose from. 

The responses should also be quantified wherever possible.

Margin of Error:

When a survey is conducted, a sample is selected and the data gathered from the survey is generalized for the larger population. Margin of error is a tool used to determine how precise the collected data are, or how precisely the survey measures the true feelings of the whole population. 

For example, it is not logistically possible for an organization to measure the entire population, say of customers, on the satisfaction level of using a particular product. Rather, samples of customers are taken from the whole population of customers. Margin of error is used to gauge how precisely this sample is judged. 

A margin of error is calculated for one of the three confidence intervals- 99%, 95% or 90%. The most commonly used is the 95% confidence interval. The larger the margin of error, the lesser is the confidence interval. 

For example, in a pre poll survey, the larger the margin of error, the lesser is the level of confidence that the survey’s reported percentage will be close to the poll’s true percentage. 

The formula for calculating the margin of error is-




Where, p = Estimate of percentage of respondents answering a question 

n = Number of respondents that answered the question 

The formula involves three basic steps: 

1. The amount of variability in the sample denoted by p 
2. The standard degree of precision of a 95% confidence interval 
3. The sample size denoted by n
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