External collaboration is considerably complicated, because interests of various organizations should be taken into account. For a long-term collaboration to succeed, there should be substantial benefits for both buyer and supplier. This needs trust and technology, as stated in a previous chapter. Trust for example also depends on the not (often) changing the supply specifications, i.e. the rescheduling of order dates or quantities (a cause discussed in this research). External collaboration can be discussed in many forms but the sharing of information is the most applicable in this situation. Information sharing with regard to demand and forecast towards suppliers can give several advantages for both parties. CO could share anticipated future demand of specific parts to corresponding suppliers. This information should be available real-time (for example on the web or intranet), or at least be updated together with the forecast of CO (weekly). This needs the suppliers to act on the received information in order to assure on- time deliveries, but on the other hand creates certainty and a direction for future sales. Because of the impact and the amount of work needed for shared (forecast) information, not all suppliers are suitable for this.
In several cases this method could be improved with the introduction of a frozen period in the forecast. Furthermore should there be a distinction in long- short- and mid-term forecasting (Wagner, 2005). As can be seen in Figure 5-1, the frozen period obliges the buyer to purchase, but also the buyer to deliver, the forecasted items on the agreed date.
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Figure 5-3: Shared forecast information
Items entering the short-term forecast also have a purchase guarantee, but can be rescheduled by CO. This, on the one hand is an advantage for suppliers, but on the other hand increases their risk of maintaining stock if dates are rescheduled. Finally, long-term forecast could indicate already sold machines (or parts) or anticipated demand, but with the fluctuating sales of CO this would be very difficult. The length of scope of these categories should differ per item or supplier, because an optimum has to be found with regard to delivery times and inventories. Updating the forecast could be done by applying a rolling forecast; every week, the forecast basically shifts a week in time. Sharing the forecast can be done for example using a portal; suppliers can log into the system of CO and download the newest version of the forecast, only with regard to their own products.
In practice, first has to be decided which items, and towards which suppliers to forecast. As discussed before, several items are already forecasted, in particular due to long delivery times (longer than FAS). This forecast is on machine-level, and should be maintained. But for each machine, the critical parts are known, and can be forecasted with them. Other criteria can be whether or not the item is suitable for keeping on stock (in particular costs and size play a role in this). Choosing suitable suppliers for this depends mostly on the criticality of the items, together with the height of CO’s turnover with these suppliers. Most important group should be
strategic suppliers and after that leverage suppliers (see the Kraljic Matrix, Figure 3-1). Furthermore, a fundamental decision has to be made on the length of the different periods
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(frozen period, short-term forecast and long-term forecast). For CO, a long frozen period will assure on-time delivery, but limits the flexibility of the organization. Therefore, a best practice has to be found. The delivery time of the part should in any case fall within the short-term forecast; the supplier can order the part and keep it on stock until it enters the frozen period, in which it can be sent CO. Also, agreements should be made with the suppliers about acting towards the forecast. They should download the forecast on regular periods in time (weekly, or when they are about to order specific parts).
In short, the following actions should be prepared in order to share forecasting information with suppliers:
Task Responsibility
Share forecasting information with suppliers
Decide which items to highlight from the current machine forecast (based on supplier delivery time, costs and size) and their suppliers (criticality and CO purchasing volume)
Purchasing, Planning
Make sure that there are benefits for both parties, and that the suppliers are aware of this
Purchasing, Suppliers
Agree on the lengths of the periods (frozen period, short-, and long-term forecast), based on delivery times, criticality and costs of stock and the way of sharing the information of the forecast
Purchasing, Suppliers
Weekly update the forecast, and assure availability towards suppliers for their specific items
Planning
Download or receive the forecast from CO, and process this when new items are ordered
Supplier
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5.3.Absence of Supplier Monitoring Techniques
In the current situation, problems or difficulties on both long- and short-term could remain unnoticed because suppliers and the supply chain are not monitored, and their performance is not measured. In order to observe, monitor and measure the supply chain (the suppliers in particular), several techniques can be used. This could prevent future, long-term developments and problems with regard to longer delivery times and higher variability, to occur unnoticed. First, a buyer itself could monitor their suppliers. From a survey of Hendrick et al. (1996), the most implemented activity was “Just-On-Time Goals and Measurement (Suppliers Meeting Scheduled Due Dates/Times for Purchased Materials).” (p. 7). Having clear agreements with suppliers regarding timely and consistent delivery and monitoring this, creates a longitudinal overview for the buyer of the supplier’s performance. Confronting, on top of this, the specific suppliers with their performance creates awareness. This technique is closely related to frequent on-time delivery measurement, and reporting procedures for suppliers (Hendrick et al., 1996): the buyer measures deliveries to monitor the long-term reliability and consistence of a supplier in order to detect flaws with specific suppliers or items. Gunasekaran et al. (2004) discuss several measures in order to evaluate delivery performance namely; on-time delivery (Stewart, 1995), on time order fill (Christopher, 1992), number of faultless invoices, and flexibility to meet the buyer’s needs (Novich, 1990). Suppliers themselves also could (be given the ability and freedom to) report delivery or availability difficulties in an as early stage as possible. This would assure a faster response of the buyer’s purchasing department on oncoming problems.
Talluri and Sarkis (2002) propose a model to monitor supplier performance with both multiple criteria and measures. In combination with providing feedback to suppliers, this method is improving supply chain performance. Furthermore, Brewer and Speh (2000) propose an extended balanced scorecard (BSC) and link this to supply chain performance measurement. As can be seen, many different forms of supplier and supply chain monitoring are known in literature. Handfield and Nichols (1999) propose three criteria in order to effectively measure supply chain performance, regardless the method used:
- Measuring the performance of the overall supply chain, rather than the individual members
- There should be one focus in the entire supply chain; improvement of customer service - Managers should be allowed to eliminate possible identified causes of problems.
Taking above criteria in account, performance measurement has multiple functions. From the case studies of Schmitz and Platts (2004), these functions appear. The most important are mentioned in Table 5-4.
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Category Function
Communication with