In the introduction project the companies first developed a CRM concept which specified work packages and the timetable for their introduction. As with classic project management, a targeted approach calls for a clear focus in respect of operational, analytical, and collaborative CRM activities, particularly in view of the broad nature of CRM. In general, the CRM projects were coordinated with existing e-business strategies, began with a focus on operational CRM (call centers, sales), and were only successively extended to include analytical and finally col- laborative functionalities. As part of a goal-oriented implementation, the subprojects comprised manageable timeframes of six months at the most. Since the first system modules were imple- mented in four to six months, initial results of the CRM project may become available after this period. However, the case studies showed that creating a filled and widely used customer data- base in the areas of marketing, sales, and service required a minimum of two years. Consequently, the expected benefits of the CRM system will emerge only in the medium term, which means that the support of top management was of great importance in all the case studies in order to over- come disappointments and setbacks. To achieve a high level of acceptance, CRM project teams were comprised of representatives from marketing and/or sales, IT, and top management. They involved subsequent users at an early stage in the requirements analysis as well as in the specifi- cation and pilot phases, since there were significant problems with adoption, particularly in the area of sales. Here again, for this change management the role of top management was of great importance (penalizing nonuse, use by management as motivator).
In order to secure a cross-functional view of customer data and processes, all companies imple- mented one central responsibility for their CRM activities. In all companies this resided with the marketing area, which possessed competencies in the creation of cross-organizational process, data, and system standards. The introduction of CRM had two major effects on the company’s organization. First, a structure based on business functions or products was replaced by one oriented toward customer segments. These organization units were given a wide scope of action, so that they could cater to the requirements of the segment for which they were responsible and then provide the connection with the internal departments. The latter were located either at a subsidiary level or as a second dimension in a matrix organization. Alongside these, central orga- nization units provided specific CRM tasks, for example, call center operation or customer seg- mentation. These areas act as service providers and bundle specific know-how, for example, on statistical methods in analytical CRM. Among the examples are Swisscom’s direct marketing center and the customer care center at Consors.
In order to identify services, all the case examples used customer life-cycle models which differentiate the processes in four to seven steps. These corresponded to established approaches from Ives and Learmonth (1984) or Vandermerwe (2000) and led to customer segment-specific services through different customer contact channels. At Heidelberg, the ‘service’ phase no longer consisted only of the services of field sales but now also included information and spare parts procurement via the online shop. Assignment to a life-cycle phase was performed on the basis of customer history and profile as well as sociodemographic and geographical criteria (Swisscom) and was closely linked with analytical CRM. The company addressed customers with a high cancellation probability (and high sales potential) with win-back campaigns which had a 15 to 20 percent likelihood of success due to more focused target groups. In the case of companies with a high level of process integration, this value was immediately incorporated in sales planning to ensure product availability after campaigns (Bertelsmann). The prerequisite is a cross-functional standardization of processes so that, for example, all CRM users have the same understanding of the terms ‘lead,’ ‘opportunity,’ or ‘quotation’ (Unisys), or that information from service manage- ment is incorporated in the quotation process (Heidelberg). If, for example, a service engineer
learns that a production manager is planning to buy a new machine, this information will be routed on to sales.
Consistent with our expectations, a central customer database for operational CRM, a data warehouse for analytical CRM, and the use of portal systems for collaborative CRM were the main elements of a CRM system architecture. Because no manufacturer covered all areas com- prehensively, heterogeneous “best-of-breed” architectures predominated, which have been real- ized on both a centralized and a decentralized basis. When it came to selecting the system for operational CRM, a variety of strategies can be observed: from the strategic decision (Unisys) and a short selection from a small number of providers (Consors) to an in-depth and time-inten- sive evaluation process (Swisscom). Considering that in all of the case studies, the decision was made in favor of a leading product on the market, the success factor may well lie in a systematic selection limited to market leaders. With 20 to 30 percent user-specific customizing, the compa- nies retained a large part of the standard functionality. Critical integration points existed to opera- tional applications, for example, to the human resources system for user data or to the CRM system for order forwarding, but also to systems belonging to analytical and collaborative CRM. Although often implemented only in a second step, both areas were already taken into account in the CRM design phase.
All except one of the case study companies have performed a benefit analysis. While the Balanced Scorecard is widely used at the strategic, qualitative level, different criteria were ob- served for measuring operational efficiency. The metrics cited by (Winer 2001, 102) “customer acquisition costs,” “conversion rates” (from lookers to buyers), “churn rates,” or “same customer sales rates” were applied in some cases (e.g., Swisscom). In addition, the companies used metrics for process efficiency, for example, call center productivity (number of telephone calls/employee, etc.) or the costs of mass mailing campaigns.
Assignment of Success Factors to Literature
Since the beginning of this benchmarking, various articles on success factors and metrics have been published. This shows, on the one hand, that there is interest in the subject, and on the other that the search for success factors is in the early stages. A first category of CSF publications are general studies on the success of e-commerce or Web presences. For example, Straub et al. (2002) summarize metrics that aim at measuring performance at the user interface, such as navigability, shopping convenience, ease of use, and the like. Usually, these articles do not provide insights into how the activities are organized during the project and operation. The second category con- tains studies more specific to CRM. For example, using the induction method, Wilson et al. (2002) discovered the need for project approval procedures, the need to leverage best practices, the im- portance of prototyping new processes, and the need to manage for the delivery of the intended benefits. Based on the work of Wells et al. (1999), Bose (2002) describes more specific critical issues that need to be addressed during the CRM development life cycle. The recommendations include conducting a complete business analysis, since CRM implies changes along customer interaction points, to ensure long-term commitment of senior level management, to consider a stagewise implementation of the CRM modules, and to carefully address ‘people problems’ dur- ing the implementation process. In a study of 96 organizations, Yu (2001) reports that corporate culture and process and technology improvement were the “best predictors of CRM success.” Table 5.3 summarizes the success factors stated in seven articles along with the respective re- search methods used and assigns them to the success factors identified in this article. This leads to the following comments:
- Most studies employ unstructured case study methodologies. In four articles, procedures and data sources are not specified. The remaining articles concentrate on case studies, and only the benchmarking study performed by Reinecke et al. (2002) from a marketing per- spective deduces success factors from a larger total population.
- In the majority of cases, it was possible to assign the benchmarking success factors to factors taken from the literature. Where no clear assignment was possible, the success factors are given in brackets. The five success factors which could not be assigned, with the exception of the twice-named features of the system architecture (flexibility and scalability), involved specific success factors (e.g., a customer profile extended to include nontransaction data). Overall, however, the success factors taken from the literature provide an initial confirma- tion of the benchmarking results.
• The success factors are concentrated on the introduction project, in particular the existence of a concept and the performance of the introduction in manageable project phases. At the same time, the users should be involved, and top management should give their full backing. The second most frequent success factors are those for customer orientation, in particular the iden- tification of services along entire customer processes and the creation of an organization struc- ture based on customer segments. Success factors for system architecture and operational efficiency are found less frequently, which indicates a lower relevance of these aspects.