Strategy
Defining a strategy for the lean game, the first aspect of differentiation is choosing lean over agile right away. The factors contributing to such costs were the little variety in the output widgets, and the need for reducing costs and time. The philosophy behind lean systems is the minimization of waste including time (Bowersox et al., 2010). Nevertheless, the low volumes of the process, and the need for quick response outlined the necessity to integrate agility within the strategy (Christopher, 2005). Thus, the strategy of being lean and agile were selected, i.e. situation in which lead times are long and characteristics of the demand are unpredictable (Wang, 2010). Considering the nature of the variability in the widgets, which are the colour of the base and the tops, and an estimation of the demand in numbers, the strategy of postponement were selected, which holding strategic inventory in unfurnished form, completing the final configuration once the demand is known. Applying the latter to the case, raw materials will be purchased for each colour and held cooked at the first process of assembly. The main aim of the strategy is responsiveness, where the change of colour will be identified right away (Jain et al., 2008).
Forecasted components will have a lean supply chain, which in this case might be seen through such aspects as coloured circles, and standard size paint for the bases (Jacoby, 2009). The rest of the components will have an agile supply chain, once an order is placed. Variation between lean and agile supply chain strategies can be seen as a common approach in many companies, where a study of supply chain strategies among Chinese manufacturers, outlined in QI, BOYER, and ZHAO (2009) revealed that companies who do not follow a specific strategy either lean, agile, or lean/agile perform worse than their competitors. In that regard, a benchmark of performance might be required to establish the best practice to follow (Christopher, 2005). Such benchmark will reveal the typical lead times, the average cycle, and other characteristics that will provided a base against which the performance will be measured for improvements. It should be mentioned that for in selecting the agile/lean strategy or leagile strategy will depend on the where the decoupling point will be that is the point in which the order driven and forecast driven activities will meet (MASON-JONES et al., 2000). The identification of such point will be the basis of the improvement for the next round in the game. At the present time such point is selected to be at the first assembly stage.
Improvements
For the first improvement, it should be stated that the selection of leagile strategy was rather successful, although some modification might be required. One improvement can be seen through integrating some of the process in the supply chain. The latter accordingly, will lead to changing the layout of the supply chain as well. One example can be seen through joining similar processes which are adjacent to each other. The suggestion was to match assembly stages into a single supply chain link, which in this case will form a single hub, and which in real life will assumingly will not only reduce logistics and inventory costs, but also the time of the logistics between different processes. Such recommendation is more related to the agility part of the supply chain, specifically acknowledging that in the game the main recorded parameters are the time of the delivery, and thus, decreasing lead time can be seen as the main priority of the team (Rimienë and Bernatonytê, 2008). The changes increased the speed of the delivery, where the lead time decreased, although the lean supply chains remained dependent on the order, where the determination of the colour played a role in the length of the whole process.
It should be noted that some of the difference between various supply chain strategies are related to aspect which might not be apparent in the game, such as the cost of the inventory. Where an analysis of the leagile strategy for the HVAC industry revealed an increase in the manufacturing costs, compared to agile and lean strategies (Supply Chain Digest, 2006). In this case, the change was through an identification of bottle-necks in the whole supply chain. Considering that lean supply processes takes place after an order is place, the next6 change is in increasing the speed of the delivery of the raw materials and cutting the bases, for which more people should be assigned to that process. The relocation of people might be a simple process in this case, while in real life scenario, it might be assumed that such relocation will be associated with a learning curve, which in turn might affect the speed of the processes and the quality at the first stages of implementation (Scott et al., 2011). In this case, the speed of cutting processes increased, facilitating a faster switch to the next process, and in turn reducing the lead time in the chain. In that regard, both cases proved to be important for the team, which is integrating several processes and relocating human resources.
Forecasting and Ordering
The forecasting in the game in the first round was largely poor due to the absence of previous information of demands, which can be seen as the foundation for forecasting. Forecasting is a projection of what to be sold, based on previous demands of customers, or an approximation of demands in the market (Bowersox et al., 2010, Chinho and Yu-Te, 2006). In the absence of such information in the game, no forecast was made with the demand down the supply chain was initiated by the customers. After several turns, with no changes in demand, the forecasting was correlated with emptying the stock first before demand increased. In that regard, such behaviour can be seen typical in such cases is usually characterised as an extreme strategy called “panic”, in which the stock is emptied first before the end customer’s demand increases (Nienhaus et al., 2002).
Another important fact, which is also characteristic of the bullwhip effect, is the lack of knowledge between each members of the supply chain. Thus, when the demand increased, at the customers’ side, each subsequent stage in the chain correlated with consideration to the three days lead time. Thus, the most obvious critique to such effect in the game is the lead time, as it is apparent that if the lead time was fewer days, the “whip” will not be so obvious. Another mistake was the information exchange. The acknowledgment of the information of demand about the increase of demand at the customers level throughout the other levels, would have allowed a smoother adjustments to such correlations (Nienhaus et al., 2002, Lee et al., 1997).
The Importance of Bullwhip Effect
The importance of the bullwhip effect can be seen on several dimensions, the most important of which is that it does allow managers to optimise their supply chains, forcing the different stage from the upstream and the downstream supply chain be concerned about the efficiency of their distribution activities, and in turn securing cost reductions (Disney and Lambrecht, 2008). In that regard, although the bullwhip effect is generally negative, it allows companies to focus to focus on its causes and appropriate actions to mitigate the effect (Lin and Lin, 2006).
As stated in the previous paragraph, the bullwhip effect enforces overall concern of the stakeholders at various stages of the supply chain, through a form of cooperation. The latter can be explained through that the strategies to eliminate the bullwhip effect largely imply some form of cooperation, specifically information exchange in form point-of-sale data (Lin and Lin, 2006). As one of the reasons for the bullwhip effect is errors in forecasting, and the corresponding amplifications of such error due to the lag in the chain, improving both is important for the participants of the chain (Manyem and Santos, 1999). The improvement of the forecasting techniques used is dependent on the lag in operations, i.e. the replenishment response time, which in turn lead to the overall purpose of optimising supply chain management (Bowersox et al., 2010). In that regard, the latter can be seen trough the goal of organisations to improve the effectivness of their operations through the supply chain, and decreasing the lead time. One of the consequences of such optimisation is optimising forecast of demand, reducing response time, and accordingly, eliminate the bullwhip effect.
Reference List
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