# 3.2.1c Location Selection: Cost-Benefit Analysis Using a Qualitative Method (Factor Rating)

### Intended learning outcomes: Identify cost-benefit analysis using a qualitative method.Explain the results of factor rating and the sensitivity analysis in this case.

Continuation from previous subsection (3.2.1b)

To evaluate alternative locations, a cost-benefit analysis is often performed. A simple, rather qualitative tool for this is factor rating, for example.

Factor rating [DaHe05, p. 382], is a decision method for evaluating several possible solutions to a problem that can be characterized using factors or features.

Figure 3.2.1.11 shows the results of a rough-cut factor rating in the form of a graphical summary of the criteria that were applied in the concrete case.

Fig. 3.2.1.11      Results of factor rating.

The overall rating can be determined qualitatively using the graphical representation in Figu­re 3.2.1.11 as an aid. First, starting from the rating of the individual criteria in Figures 3.2.1.4 to 3.2.1.10, simple graphical averaging, or interpolation, allows the determining of the positions in Figure 3.2.1.11. As the great majority of the values for location 2 are higher than the values for location 1 — also in both cases where better evaluations resulted for location 1, but were only insignificantly better than location 2 — the decision will be made that location 2 is the better location; in the case at hand, that was indeed the company’s decision.

Generally, however, it is necessary in the last step to quantify the ratings and to assign weights to both the individual criteria within a location factor and the location factors in relation to one another (reflecting their relative importance to the company) to be able to compare the alternative locations. Instead of estimating the ratings qualitatively (from minus to plus to double-plus), we can determine the degree to which a criterion is fulfilled, expressed, for example, as a percentage of maximum fulfillment of the criterion. Suppose

• n is the number of locations,
• mi is the number of criteria per location i, 1 i  n,
• Fi,j is the degree of fulfillment of the criterion (i,j) of location factor i, 1 j  mi, 1  i  n,
• Wi,j is the weight assigned to the criterion (i,j), 1 j  mi, 1  i  n,
• Wi is the weight assigned to the location factor i, 1 i

Figure 3.2.1.12 shows the formula for calculating the overall benefit B for each location and thus the ranking of the locations. For greater certainty in ranking the alternative locations, in addition to determining the overall benefit, a sensitivity analysis is also necessary.

Fig. 3.2.1.12      Factor rating with degrees of fulfillment and weightings.

A sensitivity analysis determines how much an expected outcome or result will change in response to a variation of the input variables.

For an identification of locations that are close in the overall score, it is important to vary both the degree of fulfillment and the weightings.

The quantification of ratings can also be set by considering costs and investments associated with the locations. This can, for example, concern the criteria under the location factor “internal company evaluation” (see Figure 3.2.1.8). In this case, to discount the benefits and costs over time, commonly used methods of investment analysis can be applied, such as the net present value technique, NPV (see Figure 19.2.5.3).

Likewise, for location selection for both distribution and service networks, location factors with catalogues of criteria are used.

• For distribution or service processes in direct contact with the customer or the object, the main factors are criteria such as access routes (pedestrians, cars, public transportation), population density, size of families, and annual family income. See the discussion in relation to Figure 3.1.3.2.
• For distribution or service processes in indirect contact with the customer or the object, there are often additional factors, such as the availability of lower-cost temporary personnel that can be flexibly (time) employed. As an example, airlines locate call centers in Cape Town or Dublin, due to the plentiful supply of well-trained, multilingual exchange students present in these places who can provide a low priced, qualified workforce for these part-time jobs.
• For distribution or service processes with no customer or object contact, in contrast, the location factors and criteria are in principle the same as those described above for production networks.

Assessment of the various options for the location selection can be carried out using qualitative methods such as those above for production networks. Sometimes quantitative methods are also used, such as linear programming.

## Course section 3.2: Subsections and their intended learning outcomes

• ##### 3.2 Location Selection and Location Configuration

Intended learning outcomes: Differentiate between location selection and location configuration. Explain location selection using qualitative methods and factor rating. Describe location selection and location configuration with linear programming.

• ##### 3.2.1 Location Selection: Systematic Reduction of Possible Locations / Partners

Intended learning outcomes: Disclose a procedure for systematic reduction of possible locations / partners. Present factors for location selection. Produce an overview on steps in location selection and evaluation of a concrete case, namely a joint venture partner in China.

• ##### 3.2.1b Location Selection: Factors Used for Identifying a Joint Venture Partner in China

Intended learning outcomes: Present in detail factors for location selection of a concrete case, namely a joint venture partner in China.

• ##### 3.2.1c Location Selection: Cost-Benefit Analysis Using a Qualitative Method (Factor Rating)

Intended learning outcomes: Identify cost-benefit analysis using a qualitative method. Explain the results of factor rating and the sensitivity analysis in this case.

• ##### 3.2.2 Location Selection and Location Configuration with Linear Programming

Intended learning outcomes: Produce an overview on linear programming (LP). For the design option of “in part decentralized production for the global market”, explain the use of mixed-integer linear programming (MILP).