Translate Research to Action with a VOC Table
Ask any group of satisfaction researchers and consumers of satisfaction research about the largest problem facing the research industry, most likely, the lack of actionability (or usefulness of the research) will be the most common concern raised. All too often, research is conducted, reports produced and bound into professional looking binders which end up gathering dust on a shelf some place, or if you’re like me, providing excellent use as a door stop.
What is missing is a strategy to transition research into action, and bring the various stakeholders into the research process.
Managers and researchers alike are faced with the difficult task of determining where to make investments, and predicting the relative return on such investments. One such tool for transforming research into action is the Voice of the Customer (VOC) table.
A VOC Table is an excellent tool to match key satisfaction dimensions and attributes with business processes, and allow managers to make informed judgments regarding which business process will have the most return in terms of satisfaction improvement.
A VOC Table supports this transition from listing the key survey elements on the vertical axis, sorting each attribute by an importance rating. On the horizontal axis, a complete list of business functions is listed. At this point, the researcher and manager match business process/functions with key survey elements and make judgments regarding the extent to which the business function influences key survey element (in the enclosed example, a dark filled-in square represents a strong influence, an unfilled square represents a moderate influence, while a triangle represents a slight influence.) A numeric value is assigned to each influence (typically, a value of ‘four’ for a strong influence, ‘two’ for a medium influence, and ‘one’ for a weak influence). For each cell in the table, a value is calculated by multiplying the strength of the influence by the importance rating of the survey element. Finally, the cell values are summed for each column (business function) to determine which business functions have the most influence on customer satisfaction.
Consider the enclosed example of a VOC table. In this example, a retail mortgage-lending firm has conducted a wave of customer satisfaction research, and intends to link this research to process improvement initiatives using the attached VOC Table. The satisfaction attributes and their relative importance, as determined in the survey, are listed in the far left column. Specific business processes from loan origination to closing are listed across the top of the table. For each cell, where satisfaction attributes and business process intersect, the researchers have made a judgment of the strength of the business process’s influence on the satisfaction attribute. For example, the researchers have determined proper document collection to have a strong influence on the firm’s ability to perform services right the first time, and a weak relationship for willingness to provide service. For each cell, the strength of the influence is multiplied by the importance. The sum of the values of each cell in each column determines the relative importance of each business process in influencing overall customer satisfaction.
In the example, the loan quote process and clearance of underwriting exemptions are the two parts of the lending process, which have the greatest influence on customer satisfaction, followed closely by an explanation of the loan process. The other three aspects of the loan process of significance are document collection, application, and preliminary approval. The least important are document recording and credit and title report ordering. The managers of this hypothetical lending institution now know what parts of the lending process to focus on to improve customer satisfaction. Furthermore, in addition to knowing which specific events to focus on, they also know, generally speaking, which improvements in the loan origination process will yield more return in terms of customer satisfaction than improvement in processing, underwriting, and closing. As all the loan origination elements have comparatively strong influence on satisfaction.
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