Abstract
Until recently, methodologies allowing the identification of financial returns of improvements in quality have been unavailable. Therefore, the benefits of the investment in products or services quality have been questioned by many companies. In addition, it has been difficult or impossible, in most business contexts, to choose in an objective way between different types or levels of quality investment. We propose an integrated methodology for estimating the return of quality investments, allowing a cost–benefit analysis. The approach uses a chain of causality that assumes that quality investments potentially affect customer satisfaction and loyalty, which in turn influence customer behaviours, generating financial returns to the firm. An application for the mobile telecommunications industry is presented. We conclude that it is possible to estimate financial returns for different types and levels of quality investment, given sufficient knowledge of the critical paths in the value chain. By producing measures of profitability, it becomes possible to compare investments in quality with other competing investments, enabling a rational allocation of available resources, and allowing managers to approach the investment in quality as any other type of investment in a competitive environment.
Notes
This effect of technical quality on customer satisfaction is considered indirect, i.e. via perceived quality. However, according to Burton et al. Citation(2003) this technical quality or actual performance may also be a significant direct predictor of customer satisfaction. This potential direct effect is not considered in our model. Instead we have considered the possibility of direct effects from technical quality on revenues per customer.
This direct relationship between the improvements on technical or internal quality and improvements on revenues may also be justified by the so-called ‘quality is free’ argument (Crosby, Citation1979) or by the ‘hard dollar outcomes’ for the Six Sigma process (Fuller, Citation2000). According to these authors, improvements in technical or internal quality can increase productivity and lower internal costs and thus directly increase profitability.
These drivers were in fact explicitly included in our model. We represent these sets of variables by DS and DL, only for sake of simplicity.
By including the lagged market share as explanatory variable, the number of retained customers in each period plays an accelerating effect. An increase in the retention or acquisition rates will potentially increase market share that in turn will influence retention and acquisition rates at the next period.
One possible explanation for this empirical finding is the price policy followed by the operators. According to this policy, the price of a call is significantly lower if the customer calls inside the network of a same operator. Thus, the market share may be considered as a proxy for the price. Customers of operators with larger market shares tend to perceive lower prices than the customers of smaller operators.
Owing to unavailability of data, we have not explicitly considered in the modelling of revenue per customer that the improvement on satisfaction may allow the operator to impose higher prices. Moreover this topic needs further research since some authors (e.g. Reinarz & Kumar, 2002) contradict this idea.
The actual values for these improvements remain confidential.
In a recent paper, Keiningham et al. Citation(2005) present as main findings that customer revenue was found to correlate negatively with customer profitability for unprofitable customers and positively for profitable customers. So, ‘these findings clearly demonstrate the importance of understanding clients' profitability levels. Efforts aimed to improve client revenue through improved satisfaction and SOW have the potential actually to lower a firm's net income if not targeted to profitable clients’ p. 179.