Planta del pie para valorar el metatarso adductus (MA) Se realiza proyectando el eje de la planta del pie hacia delante con objeto de cuantificar la deformidad En el pie

This research suggested some constructive steps to analyse the SC information obtained from downstream partners. The construction of RDM is an ideal way of aggregating various types of SC information and their attributes for decision making. Three steps are suggested to construct RDM. While, steps 1 and 2 of RDM list all of the possible demand factors along with their characteristics, step 3 of RDM involves evaluating and interpreting the RDM. This approach can guide managers to decide either to stop information exchange or continue information exchange. Sometimes it is also suggesting the managers to revisit RDM for future collaborations. It is interesting to note that although these decisions are common for all of the companies, the purpose of the supply chain information is different for each of the case companies. However, RDM can be used as a common technique to decide on the level of information exchange in CPFR (research Question 2).

Some of the case companies use the selected SC information for replenishments while the others use the same type of information for forecasting. For example, the historical sales information is used by the Soft Drink Co. for forecasting and EPOS data is used for replenishment; however, the sales information is used mainly for the long-term planning in Packaging Co. but not for the short term-forecasting.

The products of all of the six cases companies studied can be classified under two main categories MTO and MTS. Demand forecasting of MTS products, such as Crude-oil Co. and Wholesale Co. are rather simple in comparison to the other MTS environments. Hence, MTS products can be further classified into ‗easy to forecast‘ and ‗difficult to forecast‘. It is important to note that the short term forecasting is more important for MTS products than MTO products. This is because in a MTO environment, orders are

145 received from customers and hence demand is known. For MTS products the demand forecast is important to avoid the bullwhip effect (Lee and Padmanabhan, 1997). Accurate demand forecasts can help reducing stock-out and excess inventory. Based on the levels of difficulty to forecast demand in MTS environments, different forecasting approaches could be applied.

From the analysis of cases, it is clear that soft drink products and textile products are difficult to forecast when sales promotions are offered by retailers. To forecast these products, different demand factors need to be identified. Identifying important demand factors is possible through the Reference Demand Model (RDM). The RDM can help forecasters to systematically list all possible types of SC information and also to identify potential SC information that can be received from downstream partners. The analysis of RDM will guide supply chain planners on what information has to be exchanged. More sophisticated forecast techniques such as multiple regression modelling can be used to better match the demand with explanatory factors. In summary, it is possible to say that ‗difficult to forecast MTS environments‘ can use both RDM and regression models to improve forecast accuracy and timely replenishment (see Table 7-3). Difficult to forecast MTS situation may arise in the following cases:

 Sales promotions (functional products)

 Products with short shelf life or life cycle (e.g. fashion driven products)

 After market spare parts

- Saturn (case of after-sales service by Cohen et al., 2000)

- EEM Co. for Maintenance Revamping and Overhauling (MRO)

Wholesale Co. and Crude-oil Co. are in a MTS environment but the demand is rather smooth. Hence, it should be easy for them to forecast the demand using standard forecasting techniques. However, supply chain collaboration with downstream partners

is essential to make end customers‘ demand visible and also to ensure timely replenishments.

Table 7-3 Suggested techniques

Currently, Wholesale Co. does not use any mathematical forecasting techniques, and the company places rather irregular replenishment orders to Soft Drink Co., and not benefitting from the quantity discounts offered (i.e. when orders are placed as full truck loads). Soft Drink Co. has better forecasting and inventory management capabilities. We also showed that simple forecasting techniques could be used to predict the demand and that (R ,Q) inventory models (with the order quantity adjusted to a full truck load) could be applied. Wholesale Co. would benefit from reduced inventory levels, while maintaining high service and at the same time earning the quantity discounts when it would engage in a closer collaboration with Soft Drink Co. That collaboration could involve making end customer demand visible, applying simple forecasting procedures and (R,Q) inventory policies (with possibly joint replenishments for the slower moving items) and perhaps even engaging in a VMI arrangement with Soft Drink Co.

Crude-oil Co. maintains a good collaborative relationship with downstream SC partners so as to make timely replenishments. Currently, the company exercises VMI and

Forecasts

Easy to Forecast Difficult to forecast

E nv iro nm e nts M T S Wholesale Co. Crude-oil Co.  Standard forecasting techniques

 Make end customer demand visible

 VMI

Soft Drink Co. Textile Co.  Reference Demand Model  Multiple regression Models  VMI MTO Packaging Co. EEM Co. N/A --- Type-1 SC Type-2 SC Type-3 SC

147 inventory pooling with some retail customers. This inventory pooling facility case can be extended to others to obtain full benefit of SC collaboration. Demand variability of MTS products at Wholesale Co. and Crude-oil Co. are low, and hence the demand for these two products can be determined by simple forecasting techniques. This forecasting technique can be for example, simple moving average, exponential smoothing or Holt-Winter‘s method.

Companies operating in a MTO environment such as Packaging Co. and EEM Co. do not make any short-term forecast using the SC information from downstream partners. Supply chain information from downstream partners may be used to make long term forecasts and material resource planning. The supply chain collaboration appropriate to each case company is discussed further in the next section.