Common VOC Mistakes & How to Avoid Them
Voice of the Customer (VOC) is a critical component of Six Sigma, helping us establish measures that serve as a foundation for each of the DMAIC phases, says contributor Craig James. But beware the common mistakes of VOC. Here are 4 of them and what you can do to avoid them.
VOC is a process of gathering input from customers and translating customer input into key requirements, known as Critical-to-Quality (CTQ) characteristics. The framework below illustrates this process; I’ll be covering each of the steps in more detail, showing common mistakes made by Black Belts and how you can avoid these mistakes in your own projects.
Figure 1. VOC framework (click to enlarge)
Common mistake #1: Failure to identify all relevant customer groups
Identify your customers
This includes identifying internal groups who have insight into the bill-paying customer. This was illustrated in a Life Insurance retention project that gathered VOC from current and former policyholders; VOC missed a key component; namely, whether customers were given alternatives to help decrease premium payments. This was only identified much later in the project, through involvement of Call Center representatives during the Improve phase.
How to avoid: In addition to providing process flow information, the SIPOC (Suppliers, Input, Process, Output, and Customers – see below for diagram) can help you identify customer groups you might otherwise forget. In a SIPOC, the customer is defined as any person or group who receives the output from a process step. A good example comes from a project that identified Agents as a customer group for the Endorsement process, where bill-paying customers request changes to their insurance coverage. After analyzing external customer data, a sample of ‘best practice’ Agents were interviewed. This served as a key source of recommendations to implement across all Agencies.
Figure 2. SIPOC template (click to enlarge)
Common mistake #2: Not clarifying goals of the data collection step upfront
What do you want to know?
One common mistake is to focus too much on the outcome, and not enough on factors that may influence that outcome. This can result in VOC data that doesn’t provide enough detail around these input factors, which are often the keys to identifying potential improvements. This is illustrated in a project focused on reduction of employee calls to the company service desk. One of the themes identified through VOC was lack of information available to employees to resolve issues on their own. Because there was not enough detail on what types of information employees needed, it was necessary to conduct an additional round of data collection.
How to avoid: Using the fundamental Six Sigma equation, Y is a function of the Xs: can help you identify all the areas you’ll want to get detailed information on during the data collection step. Another suggestion is to work with internal teams (e.g., Marketing research group) who can provide consulting support and help you articulate your goals.
Common mistake #3: Using the wrong data collection method for the type of information you need
Choose your collection methods wisely
There are a variety of data collection methods to choose from, including: surveys, one-on-one interviews, focus groups, and user testing/observation. One of the most frequent mistakes at this stage is over-reliance on surveys; although interviews and focus groups are more labor-intensive than surveys, they are generally much more effective in gathering detailed qualitative information that can help lead to improvement.
How to avoid: Understand the pros and cons of each method, and consider the use of multiple data collection methods. Often, phone interviews and on-line focus groups can provide a good balance between need for efficiency and need for detailed VOC data. You should also use the goals identified in the previous step to help guide your choice of which method(s) to use.
Common Mistake #4: Not doing the work of translating customer statements to Critical-to-Quality characteristics (CTQs)
Mind your CTQs!
It’s imperative to operationalize customer CTQs, because this is what feeds into subsequent phases such as gathering baseline measures, identifying root causes, and developing Control Plan metrics. Many times, initial verbatim comments are not themselves specific or actionable enough. For example, suppose a customer says he/she wants "good customer service": what does this really mean? You need to either probe the customer on what he/she means, or translate this statement in some other way, such as brainstorming with your project team.
How to avoid: You can use a tool such as the CTQ tree to translate customer input into CTQs. In using a CTQ tree, you keep asking the question: "What does that mean?" until you reach the proper level. This approach can either be used directly during the VOC data collection, or after the fact as a team brainstorming tool. The example below shows how you can get from a generic statement ("Good customer service") to more specific CTQs.
Figure 3. CTQ Tree example (click to enlarge)
By looking at VOC as a process and by taking advantage of the tools available in the Six Sigma toolkit, you can gather the right information from the right people using the right method. This will lead to objective CTQ measures that will serve as critical input throughout the DMAIC phases, which in turn will allow you to achieve maximum results.