Beneficios de ISO 45001

To answer the main research question, the value discipline typology of Treacy and Wiersema (1997) has been used to describe value propositions as a combination of three kinds of customer value. Inspired by the work of Micheels and Gow (2009), a value discipline scale has been created to measure which kind of customer value P&C-insurers intend to deliver and which kind of customer value is perceived and needed by clients. In total, nine elements of a value proposition were included in the value discipline scale of this research. These elements were based on previous literature and suggestions from the field (e.g. from clients, intermediaries, and consultants). For each element, three statements were developed. Each statement reflects one way to offer customer value in line with operational excellence, product leadership, or customer intimacy. Respondents had to distribute 100 points between the three statements per element.

The value discipline scale was distributed among six of the largest P&C-insurers in the Netherlands. Two insurers filled in the scale twice as they have two value propositions within the target segment of this research, i.e. a proposition for clients with 2-10 fte and a proposition for

clients with 10-50 fte. This resulted in eight different value propositions from P&C-insurers. The value discipline scale was also distributed among a sample of 171 respondents from clients with 2-50 fte. The scores of P&C-insurers and B2B-clients were used to test whether there are any differences between what is currently offered and what should be offered in the future. The future value proposition will be based on the needs of the clients. To get an indication of what is currently offered, the value proposition as intended and communicated by insurers and the value proposition as perceived by clients were analyzed. The differences (or ‘gaps’) give an indication what P&C- insurers should change to ensure that clients perceive a value proposition which is also aligned with their needs. There is an opportunity for P&C-insurers to become distinctive if they can offer a value proposition which covers the needs that are currently not fulfilled.

Potential gaps were identified by comparing the scores of P&C-insurers and B2B-clients on each statement of the value discipline scale. An independent samples t-test was used to test whether the means of P&C-insurers’ intention and B2B-clients’ needs are significantly different from each other (gap 2). The same test was used to check for significant differences between the means of P&C-insurers’ intention and B2B-clients’ perception (gap 3). Because the scores for clients’ perception and needs (gap 4) were obtained from the same sample of 171 respondents, a paired samples t-test was used to compare the average difference between an individual client’s score on perception and the score on his needs.

The quantitative results of the gap analysis were complemented with qualitative data from semi-structured interviews. The qualitative data was used for the purpose of explanation, unexpected results and illustration (Bryman, 2006, p. 106). The combined results of the quantitative and qualitative analysis will provide P&C-insurers with some future directions on how they can deliver a more distinctive value proposition towards B2B-clients.

For a correct interpretation of the conclusions and implications in the following paragraphs, a few limitations should be noticed. First, the gap analysis has been conducted on the level of separate elements. The analysis could have been simplified by taking the average score for all nine elements on operational excellence, product leadership, and customer intimacy. However, such data reduction was not possible due to the low levels of internal consistency reliability and convergent validity. This means that the scores of an individual client do not indicate a consistent preference for operational excellence, product leadership, or customer intimacy across the different elements in the value discipline scale of this research. Hence, it cannot be stated with certainty that the statements are all measuring the same value discipline as an underlying construct.

Furthermore, the heterogeneity in clients’ perceptions and needs is high (as reflected by the high standard deviations). Because the clients in this sample were diverse, it cannot be stated which kind of customer value is most important to all B2B-clients with 2-50 fte as firm size. To determine the optimal level of one kind of customer value, a further segmentation in clients will be necessary. For a reliable comparison of segments, the sample size will need to be larger than the 171 clients that were used for this research.

A larger sample size will also allow for a gap analysis of clients from the same insurer. The sample size of clients per insurer was too low to make any valid inferences with regard to the perception and needs of its own clients. As a result, this research could not test the differences between the clients of various insurers. Otherwise, we could have tested the assumption of Treacy and Wiersema (1997) that “different kinds of customers buy different kinds of value” (from different companies). More time and resources will be necessary to obtain larger subsamples of clients for

each insurer and to conduct an analysis per insurer. This research has provided a start for such a future research by first exploring the generic trends in the P&C-insurance market.

The cross-sectional measurement of the research data also presents a limitation, as B2B- clients were asked simultaneously for their perception and their needs. This makes it difficult to assess whether client’s expectations (or needs) are fulfilled by the P&C-insurer. A longitudinal study may be necessary in which the expectations of clients are measured on forehand, while the clients’ perception of the delivered service is measured afterwards.

However, although the quantitative data was limited by the cross-sectional design, the research data was also enriched by complementing it with qualitative data from semi-structured interviews and a frequency count of keywords. Additional insights were derived from these data as well. One of these findings is that there seems to be little attention for innovation among P&C- insurers. This was initially observed from a low frequency of the keyword ‘innovation’, and it was later confirmed by the interviewees from P&C-insurers. However, given the time constraints of this research, we may not have elaborated too much on the potentially limited attention for innovation and the underlying reasons. This may require a more in-depth analysis of qualitative interviews. Our interviews now mainly served a goal of explanation, unexpected results and illustration (Bryman, 2006, p. 106).

Similarly, the frequency count of keywords mainly served an informative and exploratory goal. Future research with a more extensive keyword dictionary might be needed, to verify whether the frequency count in this research missed some other important keywords. In addition, the analysis of communication has been restricted to written sources of text on the insurers’ web sites for time considerations. Other important sources of communication, such as the advisor, have not been included. It might be interesting to assess the influence of an advisor on client’s decision-making.