Improving performance - particularly in those areas that are important to customers - has been a staple of continuous improvement programs for years.  Market research is routinely utilized to identify attributes that are important to the customer, measure current and competitive performance, and develop growth strategies based on the research findings.

This all seems very logical and simple, but as Albert Einstein said, “make everything as simple as possible but not simpler.”  In a recent survey, a film customer was asked the following: “How important are the adhesion properties of film in your manufacturing process?”  The answer came back 10 out of 10; extremely important!  This coupled with the fact that performance ratings were equal to competition (i.e. undifferentiated), led company management to conclude that improving the adhesion properties of their film would add value and provide a competitive advantage.  The strategy appeared to make sense, except for one minor detail. Even though film adhesion was critical and therefore very important within the customers’ process, once the minimum adhesion spec is reached, there is little to no value associated with improving adhesion.  The fact was improving film adhesion would not deliver any additional value.

So how can your research assure the importance measure of each attribute is an accurate measure of importance?  Don’t ask the importance of attributes, derive the importance. Importance can be derived by using a simple regression between each attribute and overall satisfaction or value. This allows a determination of attribute importance without actually asking for a series of additional importance ratings. PMG believes that this unstated or derived importance measure is more accurate than stated importance.

Derived importance is the correlation between the rating of any single performance attribute – such as on-time delivery or technical support – and an outcome such as overall customer satisfaction or overall value. If an attribute tends to move in sync with the outcome, there is a high correlation (Figure 1). However, if the attribute moves independently of the outcome, there is a low correlation (Figure 2).

                                Figure 1                                            Figure 2                

So, if customers tend to rate on-time delivery high when they are very satisfied and rate it low when they are dissatisfied, there is a high correlation between the two measures. This would suggest that on-time delivery is a strong driver of customer satisfaction, thus an important attribute.

To further illustrate the accuracy concerns of “stated importance” verses “derived importance,” we employed both methodologies in the same survey, allowing for a direct comparison of the data.  The graphic below (Figure 3) shows the average importance rating for each attribute on a 1 to 7 scale (1 being not important and 7 being very important). The first concern is there is little differentiation between the overall importance ratings of all of the attributes, making it impossible to identify the top 3 or 4 most important attributes. The reality is when asked to rate the importance of product and service attributes, respondents will almost always rate at the highest part of the scale.  Why? Because they do not want anything reduced or taken away.

Figure 3

As an example, if you were asked how important each of the following attributes are in choosing a new automobile, what would you say?

• Overall quality
• Safety ratings
• Resale value
• Warranty
• Overall comfort
• Fuel economy
• Maintenance cost

Wouldn’t you rate most, if not all, as very important (7)? This reality makes it nearly impossible to truly identify the precious few attributes that are driving satisfaction or value by simply asking the question.

However, using derived importance can create a much clearer picture of the critical attributes that are driving satisfaction and value.  The graphic showing the results when importance is derived below (Figure 4) shows much more separation in the values. Product strength and sales effectiveness are by far the leading drivers of satisfaction. Conversely, the entire category of deliveries and shipments is clearly not a driver of delivering satisfaction.  

Misreading the importance of critical attributes in delivering customer satisfaction is a simple mistake to make, but can have major strategic and competitive ramifications. Companies can align major parts of their organizations to improve areas that deliver little or no value to the customer. Most successful companies are not only operationally excellent, but also spend upfront the time and effort to assure they are heading in the proper direction.