Editor’s note: William M. Bailey is principal of WMB & Associates, an Apopka, Fla., statistical services firm.

Gap analysis is the term for a methodology used to help a business understand the relationship between what is important to its customers and the derived difference between business performance and customer expectations (the P-E gap). For example, a client might note that price is very important in their decision to purchase an item. However, when asked what else is important in that decision, the customer might also list another 20 items or attributes that are equally important. Thus, how does price actually rank in comparison to the entire set of decision criteria?

As with cause/effect models, such as regression and discriminant analysis, gap analysis attempts to understand relative positioning. The value in gap analysis is its simplicity and pictorial representation. However, gap analysis does not determine any statistical relationship between these items of importance. Gap analysis is based on the comparison between an attribute’s importance (mean rating) and the difference between the attribute’s (mean) performance and its (mean) expectation, called the P-E gap or the difference between performance and expectations.

This article is based on the author’s part in the addendum research to a study of the trends driving the demand for oligonucleotides (oligos) in the United States. Oligos are short sequences of single-stranded RNA or DNA which are often used as probes for detecting complementary DNA or RNA because they bind readily to their complements.

As described in the report (“The U.S. Market for Synthetic Oligonucleotides: Establishing Differentiation for Success,” published by BioInformatics LLC, Arlington, Va.), competition in the current oligos market is intense:

“Overall, the market for commercially available custom oligonucleotides has reached a certain level of maturity. Mature markets are those that have achieved a state of equilibrium marked by the absence of significant innovation. In such a situation, brand equity is difficult to establish and suppliers are challenged to differentiate themselves and/or their products in an effort to keep customers from switching to competitors. Customers in a mature market therefore enjoy significant leverage over their suppliers, and in an attempt to maintain market share suppliers often feel as if they have no choice but to compete on price with a resultant decline in profitability.”

The data collected for this project is based on a survey conducted by BioInformatics through its market research panel of scientific customers, the Science Advisory Board, which consists of life science and medical professionals from 62 countries who participate in surveys that address emerging technologies, test customer reactions to new product concepts, measure brand awareness and assess advertising effectiveness.

The goal of the addendum research was to use P-E gap analysis to determine key attributes in selecting a synthetic oligos supplier. While the actual results were segmented by brand, this illustration is viewed from an overall perspective. A secondary objective was related to brand equity - indexing based on derived importance - and is planned for a later article.

The gap table that forms the basis of this type of analysis displays the mean results for each measured attribute based on its importance (I) to the respondent, the respondent’s perception of performance (P) of each attribute and then what the respondent expects (E).

The gap map is another form of a quadrant map that pictorially represents the results with the P-E gap on the vertical axis and importance on the horizontal axis. The four quadrants are based on the intersection of the overall importance mean and the P-E gap (Figure 1).

A high (or positive-direction) P-E gap for an attribute is generally favorable and means that performance exceeds expectations (P > E). On the other hand, a low (or negative-direction) P-E gap shows performance as being below expectations (P < E).

While these are informative results, a much more revealing interpretation takes place when attribute importance is considered. Attributes that fall to the left of the vertical reference line are classified as those of lesser importance relative to those to the right of the line. This is not to say, however, that they are unimportant.

The P-E map used to represent the results of the gap analysis does not form its basis on pure quadrant theory but is an extension of an earlier theory that involved market acceptance models that describe “cash cows” and “dogs” to segment products based on their market attractiveness and competitive positioning. Here we relate attractiveness to importance while the P-E gap is a gauge of perceived market position. Such a display exposes attributes that have a high level of importance to the consumer, as defined by their mean rating, but have a low performance-to-expectation deviate (P-E gap).

Key supplier attributes

In the research, each respondent was asked to rate a series of attributes using a seven-point Likert scale ranging from a “low” rating to a “high” rating using the following questions:

“Previous studies have identified the following features as important to other life science researchers. When considering your Primary Supplier’s [noted in an earlier question] ability to provide oligos, how IMPORTANT to you are each of the following? (Choose only one for each.)”

“How we expect a company to perform may differ from how they actually perform. How high or low are your EXPECTATIONS for each of these features when purchasing oligos from your Primary Supplier? (Choose only one for each.)”

“As we mentioned in the previous question, how we expect a company to perform may differ from how they actually perform. How well is your Primary Supplier PERFORMING based on your experiences when purchasing oligos from this company? (Choose only one for each.)”

Table 1 displays the results of the P-E gap analysis and consists of the mean results for each measured attribute based on its importance to the respondent (I), the respondent’s perception of their primary supplier’s performance regarding that attribute (P) and then what the respondent expects of each attribute (E). The P-E column represents the difference, or gap, between performance and expectation. Thus, a positive P-E indicates that the attribute’s performance is higher than expected, and vice versa.

For example, based on the seven-point Likert scale, the mean response for the perceived importance of accuracy of shipment is 6.73; its mean expected value is 6.63 while it is performing at a mean rating of 6.41. Thus, the P-E gap is -0.22 (6.41-6.63), which finds that accuracy of shipment is underperforming.

Of particular note is “value for price paid.” The results show that the perceived performance of the price value being derived for the price being paid is lower than expected. That is, the price being paid is greater than the perceived value - again, underperforming.

Also noted in the table are the overall importance mean and P-E gap, which are used to determine the quadrants for interpretative purposes. The overall P-E gap of 0.01 suggests that, generally, performance is just about at par with expectation.

The gap map (Figure 2) is the pictorial representation of Table 1 with the P-E gap on the vertical axis and importance on the horizontal axis. The four quadrants are based on the intersection of the overall importance mean and the P-E gap, 5.76 and 0.01, respectively.

As seen, performance is lower than expected (a negative P-E gap) for the following attributes that have higher than average importance:

  • timeliness of delivery (-0.34)
  • quality-control procedures (-0.34)
  • quality guarantee (-0.33)
  • accuracy of shipment (-0.22)
  • value for price paid (-0.20).

Respondents are not getting what they expect from this set of above-average importance attributes.

On the other hand, performance is higher than expected (a positive P-E gap) for:

  • sales force (0.68)
  • customer service/support (0.28)
  • oligo design expertise (0.23)
  • same-day delivery (0.16).

But, compared to several other attributes, these are relatively unimportant.

The only supplier attribute that is both deemed as being important and meeting the P-E gap expectations is electronic ordering capabilities via the Web site.

Detailed picture

Gap analysis is but one tool that provides a means of evaluating brands or companies based on attributes that are deemed by customers as crucial to selecting a supplier. While performance alone is a significant criterion for selection, the addition of customer expectation and importance into the equation paints a more detailed picture for companies seeking to learn more about the many factors that customers take into consideration when making their purchase decisions.