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SCM has been a major component of competitive strategy to enhance organizational productivity and profitability. The design and operation of an effective supply chain has been widely recognised as being of important to business performance (Wikner et al., 1991). Authors Wikner et al., (1991); Mason-Jones & Towill (1999) have proposed different approaches, strategies and models to enhance the performance of the supply chain management. The proposed approaches, strategies and models have been tested by their respective authors through different simulation models in order to check the validity and applicability to the real world.
In this research study, we are discussing two research studies, in which their respective author's have proposed different strategies to improve and enhance the performance of the whole supply chain.
Smoothing supply chain
In order to improve and enhance the supply chain performance the Wikner et al., (1991) suggested two approaches
Integration in the supply chain
Smoothing the supply chain dynamics
Integration in Supply Chain
In this part of the research study Wikner et al., (1991) suggested, in order to enhance the performance of the supply chain, integration of all the echelon approach should be used, rather than focusing on individual echelon. Since integration cannot be achieved instantly, therefore an integration plan should be adopted.
Wikner et al., (1991) supports the approach put forward by the Stephens (1989). Stephens (1989) proposed that top down design methodology should be used in integrating the supply chain. Stephens (1989) put forward four stages through which integration can be achieved. When combining the stages, there should be subsequent improvement in the SCM. The description and characteristics of five stages are summaries as follows.
Stage One. Stage one also known as base line. The company planning is short term and is more towards reactive to crisis in order to get quick fix. The stage one companies puts the responsibilities of different activities on different independent departments.
The stage one companies has the following characteristics
Staged inventories caused by failure to integrate and synchronise activities
Independent and often incompatible control systems and procedures covering sales, manufacturing, planning, material control, purchasing, etc.
Organizational boundaries are not defined properly; purchasing might control the incoming material flow to raw material stocks without regard to manufacturing requirements.
Stage Two. In second stage of integration company develop factory function integration. Company normally apply time-phased planning to the materials and manufacturing management areas using Material Required Planning (MRP) or Manufacturing Resource Planning (MRP II) techniques.
The characteristics of stage second integration are as follows
Emphasis on cost reduction rather than performance improvement.
Discrete business functions, each of which is buffered by inventory
Elements of internal trade-off between, for example, purchase discount and the level of inventory investments, high plant utilisation and batch sizing
Customer services tends to be reactive, in other words who shouts loudest gets the goods
Stage Three. This stage involves all local integration of all those aspects of the supply chain which are directly under the control of the organization. Organizations in this stage normally use DRP systems, integrated via well managed master schedule to an MRP II system for material management. Where possible for organization, they opt to just in time (JIT) manufacturing strategy.
The characteristics of stage third integration are as follows
Full system visibility from distribution through out the purchasing.
Medium term planning. The focus on tactical rather than strategic issues.
An emphasis on efficiency rather than effectiveness.
Reacting to customer demand rather than managing the customer
Extensive use of electronic data interchanges to support the customer link and facilitate at a faster response.
Stage Four. The fourth stage of integration is achieved when there is full integration through out the supply chain by extending the scope of management outside the company to embrace suppliers and customers. Organization is integrated with all the suppliers of the supply chain.
The Characteristics of stage fourth integration are as follows
Embodies a change of focus. From product oriented to customer oriented through penetrating deep into customer organization to understand their products, culture, market and organization
Focus of organization is changed from oneself to mutual supplier cooperation to benefit all stakeholders.
Smoothing the supply chain dynamics
In the second part of this research study, Wikner et al., (1991) used the detailed mathematical analysis; model simplification and optimisation via SMART algorithm in order to improve the dynamics of the supply chain.
Wikner et al., (1991) proposed five strategies to smooth the supply chain dynamics, they also stated that they are not comprehensive but have found these strategies in various industrial studies. The five strategies are as follows
Turning the existing decision rules.
In this Wikner et al., (1991) have used the basic Forrester decision rules and modified them in order to determine any possible improvement in the supply chain dynamics. For ease of analysis Wikner et al., (1991) have fine tune the Forrester model. For ease of analysis, time to smooth order and the time to adjust inventory are taken as equal and termed them as double time constant.
The double time constant, represents the parameters within each echelon which is directly influenced by the management decision making procedure. Three setting were used by Wikner et al., (1991), which are pessimistic, nominal and fast using the SMART technique for deterministic performance. The new model behaved slightly better than the setting suggested by the Forrester and the demand amplification was reduced slightly.
Reducing System Delays
Reducing time delays through out the system element by element. This can be done by substitute machine process for manual clerical operation in order to speed up the process and enhance productivity. Here Wikner et al., (1991) try to automate the supply chain processes so that rapid information flow through out the organization takes place.
Automation helps in the reduction of the demand amplification and significant improvement was seen. But Wikner et al., (1991) also argued that since it requires major over haul in the organizational system. Reducing system delays can be effected by the major cost of implementing the new system.
Removing the Distributor From the Supply Chain
The benefit of removing an echelon from the supply chain was analyzed. In this Wikner et al., (1991) analyzed the benefits of moving from three echelons to two echelons, in which retailer orders directly to factory/ warehouse. The removal of distributor from the supply chain helps in the reduction/removal of the amplification caused by the pipeline and inventory accumulation at that echelon.
The results obtain from the removal of the distributor are encouraging and gives the indication that demand amplification at the factory is greatly removed. Here authors support the argument put forward by Forrester that after the removal of an echelon normal distribution functions such as sales, service, and training assistance to retailers will be removed and the only function remain would be ordering and stocking goods. Therefore in order to control the echelon, organization should purchase it or start its own distribution network.
Improving the Echelon Decision Rules
Any deviation in the market demand is absorbed by the inventory; this is helpful when the demand amplification is sort term, since the inventory works as a shock absorber to smooth the system. The authors replace the pipeline delay variable by its average value at each echelon. The result shows that the system behaves much better and the demand amplification was reduced. Considering the improvement in the reduction of the demand amplification and the recourses put in order to implement this strategy are economical this particular strategy has high chances of being accepted by the industry.
Integrating the Information Flow
There are three different approaches to integrate the information flow through out the supply chain.
The first approach is based on the assumption that one echelon can be regarded as a linear filter with a transfer function known to the higher echelons
By using this knowledge concerning the lower echelons the higher echelons can cancel out the distortion of the order rate caused by lower echelons. The cancellation does work and a great improvement in the system behavior can be achieved.
The second approach is based on the use of the cancellation discussed above but instead of using knowledge of the actual (or assumed) control laws of the lower echelons; these are estimated using available information from lower echelon.
The third approach states that instead of using the exact knowledge of the control laws at lower echelons as in the first approach or using an estimation procedure as in the second approach. Organization will now focus on the individual states (flow of information) and see if it is possible to reduce the effect of the derivative terms.
Since the overshoot of demand amplification is amplified in the upper echelon. In order to control this problem, we divide the orders into two fundamental types. Actual increase in sale and the extra unit orders for the safety stock/cover orders.
By doing so higher echelon levels now receive orders of two forms. The real order related to customer demand and the order that maintain cover/help build safety stock. If implemented the total stock in the system will be somewhat controlled and the demand amplification can be controlled.
Choosing the Best Solution
The best solutions from the derived strategies are summarized in table 1 taken from the study of Wikner et al., (1991)
Table the best solution
Supply chain re-design: comparison of benefits of "multiple"improvements with single changes
Type of Model
Tuning the existing policy parameters
Reduction of time delays
Removal of distributor echelon
Improved linear pipeline policy
Improvement via integrated information flow
Improvement via combining strategies 4 and 5
Improvement via combining strategies 1, 2, 4 and 5
Note: The more "x"shown, the greater the improvement in performance in response to a step changes in market demand.
Using the Information Decoupling Point to Improve Supply Chain Performance
In this research study the authors Mason & Towill (1999) have studied the impact of decoupling point in the supply chain in order to enhance its performance. Mason & Towill (1999) proposed that all supply chains have at least two distinct pipeline flows: the order information transfer pipeline, from point of sale through to raw material supplier and the product transfer pipeline from raw materials to end customer.
The traditional organizational supply chain policies discourage the sharing of information because it was perceived, the one who has information has power over others members in the supply chain. Due to which adverse relationship was developed between supply chain members where they regard each other as enemies and does not help each other and the only winner at the end remains competitor.
Traditional supply chains only concentrate on the material flow pipelines because it was quite easier for them to re-engineer the shop floor as it is under their control. Traditional supply chains do not concentrate on the information flow as they have to redesign the whole information flow pipeline. Now in order to enhance the performance, supply chains need to develop integrated strategies for both information and material flow pipelines.
The Material decoupling Point
The decoupling point is a standard term given to the position in the material pipeline where the product flow changes from "push" to "pull". The material decoupling point is formally defined as
"The point in the product axis to which the customer's order penetrates. It is where order driven and the forecast driven activities meet. As a rule, the Decoupling Point coincides with an important stock point - in control terms a main stock point - from which the customer has to be supplied."
(Hoekstra & Romme, 1992)
The strategic position of the material decoupling point depends very much on the product type, consumer demand and supply chain approach adopted by the organization. Figure 1 taken from the research study of Mason & Towill (1999), summarizes the four simplified generic supply chain strategies which are available for organizations. By moving the position of the material decoupling point, these strategies can provide highly customized products, which have high uncertainty (full postponement strategy) through to providing a standard product with low demand uncertainty (full speculation strategy).
Despite the fact that the material decoupling point mentioned in the figure 1, describe two types of postponement and speculation strategies at various points of the supply chain. The governing principle is always to move the material decoupling point as close to the end consumer as possible in order to ensure the shortest lead-time for the consumer.
Figure DEFINITION of differing supply chain postponement strategies
The Information Decoupling Point
The Information Decoupling Point is defined by Mason & Towill (1999) as "The point in the information pipeline to which the market place order data penetrates without modification. It is here where market driven and forecast driven information flows meet".
In traditionally supply chains it is placed at the same point as the material decoupling point and is therefore placed as close to the end consumer as possible. This positioning of the information decoupling point is wasteful and limits the effectiveness of the high value resource of undistorted order information available on the dynamics of the supply chain.
Now in order to maximize the strategic potential of undistorted data within the supply chain, the information decoupling point is being moved as far upstream as possible. The question that needs to be answered here is, how much the information decoupling point should be moved up-stream and what would be the effects on the dynamics of the supply chain.
Simulating the Information Decoupling Point
The use of simulation as a systems engineering analysis tool to research and understand the impact of supply chain dynamics on business performance was established 40 years ago by Jay Forrester.
The information decoupling point simulation model used by Mason & Towill (1999) is based on the well documented Automatic Pipeline Inventory Order Based Production Control System (APIOBPCS). The APIOBPCS based simulation model has been used confidently as a benchmark to demonstrate performance enhancement for a wide range of practical and real world supply chains.
The information enrichment model utilized by Mason & Towill (1999) is a four level supply chain model which constitutes a retailer, distributor, warehouse and factory. For convenience, the material flow lead times are set the same at each stage in the simulation.
In order to analyze the strategic benefits of the information decoupling point and to determine where in the supply chain its optimal position might be, four designs were simulated.
Design 1 simulates the traditional supply chain where only the retailer accesses the actual buying patterns of customer/consumer. This design provided data against which the other designs could be benchmarked and analyzed. Design 2 and 3 test the dynamics of the supply chain as the information decoupling point is moved upstream enabling increasing number of players in the supply chain to utilize the consumer sales information. Finally, Design 4 analyzes the potential dynamic improvements available if the information decoupling point is moved to the furthest point upstream thereby enabling all four members of the supply chain to have a direct line of sight to the consumer.
The simulation model was injected with a 20% step increase in consumer demand for each of the designs to be tested.
Moving the Information Decoupling Point to Maximize Competitive Opportunity
The dynamic behaviour of the supply chain for each of the four designs was assessed and analyzed via the order rate and stock level behaviour patterns at each echelon. Since the factory experiences the worst buffeting in a traditional supply chain. Mason & Towill (1999) used it as benchmark/statistic for measuring the improvement in dynamic behaviour of the whole supply chain.
The percentage of improvement of the factory order rate for each of the four designs is summarized in figure 2 taken from the research study of Mason & Towill (1999). For convenience, the improvement scale selected is linear and in the range of 0% to 100% for the idealization of the best imagined dynamic response of the supply chain.
What is clear from the simulation results is that the further the information decoupling point is moved upstream the better the improvement in the dynamic behaviour of the supply chain observed via factory order rate. This is due to improved sharing of knowledge and information of the actual end consumers buying behaviour for all players in the downstream of the supply chain.
When the information decoupling point is placed at the factory, the potential performance improvement due to this information sharing is maximized and can be seen in the figure 2 which shows a gain of 80%. The theoretical best dynamic performance is attained because the whole chain begins to respond to a consumer change as soon as it happens since the factory can see changing consumer habits as they occur.
Figure Dynamic performance for different information decoupling point designs
Number of methods and strategies has been identified in both the studies to enhance and improve the supply chain performance. Both the studies, proposed that most effective way to improve the supply chain performance is through the better use of information flow.
Industrial dynamics simulations have played a vital role in the supply chain design, especially at the aggregate level. We have seen from the two research studies summarized above, how the simulation method can be utilized to highlight areas of performance improvement, especially when combined with transfer function analysis.
Through simulation analysis both the studies proved that significant performance improvements in the supply chain, when the information flow is increased. The value of the undistorted information about up to date customer demand has helped organizations in their delivery and planning processes also helped in controlling the dynamics of the supply chain. When the information transferred within the supply chain is improved, it reduces bias, noise, and staleness in the supply chain. There are evidences in number of studies that this is now happening on major scale businesses at each echelon.