Selection of cases

We decided to conduct multiple cases in order to augment the generalizability of the conclusions, also referred to as the external validity (Voss, Tsikriktsis, and Frohlich 2002; Meredith 1998).

In studying multiple cases an important issue is the case selection. Cases should be selected according to clearly specified criteria using replication logic. According to Yin, using replication logic means that the cases must be selected either to predict similar results (literal replication) or to produce contrasting results but for predictable reasons (theoretical replication) (Yin 1994 p.46). In our study replication logic is used: each case is selected carefully on the basis of variables assumed to influence the degree of formalization. Some of these variables are kept constant to predict similar results with respect to the structuring issues of the ordering process. Some other variables are left free to vary as they would naturally (Meredith 1998) to produce different results on the degree of formalization of the ordering process. In the remainder of this section the selection criteria are discussed.

The variables that influence the degree of formalization of the ordering process are demand characteristics and characteristics of the production system, discussed in Chapter 4. We assume that formalization of the ordering process will be especially difficult in manufacturing companies with a customer-specific demand that is hard-to- predict. To be able to deal with this uncertain, heterogeneous and customized demand the production system must have certain flexibility. We further assume that the specific combination of demand and production system influences the complexity of the ordering process and therewith the degree of formalization of the ordering process. Using replication logic we defined the main selection criteria on the basis of these variables.

The first selection criterion used was the size of the organization. On the basis of theoretical notions we assume that the larger the organization, the higher the degree of formalization is (e.g. Mintzberg 1979), and vice versa, the smaller the organization, the lower the degree of formalization in general respect. Being interested in organizations in which formalization is not a mere result of the size of that organization we selected small to medium sized organizations. The size of the selected companies was held

constant; we selected manufacturing companies with about 100 employees in total. The actual margin differed from 90 to 125 employees (see Table 5.1).

The second selection criterion was the degree of customization of demand. As discussed in Chapter 3, the ability to formalize is often associated with situations that are characterized by few uncertainties and in which activities are repetitive. In general, repetitive order-processing situations are associated with processing standard orders. We therefore assume that processing standard orders will be easier to formalize than processing customer-specific orders. Consequently, we expect that formalization of the ordering process will be fairly easy in manufacturing companies with a standardized demand. Formalization will be a more interesting issue in companies with a customer- specific demand. We also argued that customer specific demand is often associated with order-driven manufacturing in order to respond flexibly to changing customer wishes. Therefore, we selected companies that had mainly customer-specific demand with an order-driven production system (see Table 5.1).

The third selection criterion was the type of production system. We selected companies with a comparable production system in order to prevent that differences in the production process interfered with the degree of formalization. We selected production systems with a relatively high degree of capacity complexity and a moderate degree of material complexity: having some variety in routings, multiple operations with some ‘work-in-process’ between operations, moderate inventory of semi-finished products, single products or small batches (capacity complexity). The products are composed of different components that are partly produced in-house and partly purchased (material complexity). These production situations are mostly identified as job shop environments, although the final production unit may mostly resemble an assembly environment. We expect that these types of production systems are confronted with uncertainty in capacity availability and material availability, thus influencing the production possibilities (see Table 5.1).

The final selection criterion we used was the availability of an automated order processing system. In the previous chapter we described the availability of an order processing information system as a possible influencing variable (see Section 4.3.3). In this study we are interested in the influence of an automated system on order processing in general and formalization of the ordering process in particular. Therefore, we selected manufacturing companies that use information systems in various extents. During the selection we asked the companies if they were using an information system to support the administrative order processing and to control the order flow. We did not find a company not at all using automated information systems, but we were able to identify companies with clear differences in the extent of integration of the information system used (see Table 5.1).

On the basis of these selection criteria we first selected all manufacturing companies with about one hundred employees. From this selection we screened the companies on

the products and their production process. Then we approached the companies by phone and discussed the other relevant criteria. Only those companies that complied with the selection criteria were asked to participate in our research. After a first approval we visited the company for an introductory meeting, to further discuss the research and the relevant characteristics. Table 5.1 presents an overview of the characteristics per case.

Table 5.1 Characteristics of the cases selected Com

pany

Size Demand Production Information system

A 95

95% standard products with customer specific variations.

4 main product groups

Steel-based office furniture. 4 main operations. Mainly ATO.

Only administrative order processing B 124 2 PMC’s: 60-70% customized 30-40% standards Heat exchangers. 3 main operations. Standards Æ MTS Specials Æ MTO

Integrated, standard, but new information system

C 110

95% customer specific variations.

5% new design. 7 main systems.

Flue gas terminal and ventilation systems. 5 main operations. Mainly MTO Integrated, customized information system D 125 70% customer specific variations. 30% standard. 8 product groups

All kinds of stel-based products. 3 main operations. Mixture of MTS, ATO and MTO Mostly administrative order processing E 90 2 PMC’s: 80 % customized products (9 product groups) 20% standards + customer specific variations (4 product groups) Steel-based manufacturer of products for office and shop design.

4 main operations. Mixture of ATO, MTO and ETO

Integrated, standard, but ‘outdated’ information system