The Challenge Of Supply Chain Costs Business Essay


3.1. Introduction

The opening years of the 2000 have seen the emergence of new decreasing pressures. Whilst trends toward price reduction may not be worldwide, there can be no doubting that most markets are more price competitive today than they were a decade ago. Prices in the high streets and the shopping places continue to fall in many western countries, and upstream of the retail store, the prices of components, raw materials and industrial products follow the same downward pattern.

Fig 1: SCM Ecosystem (Source:

At the same time some of these depressions of price can be described as the outcome of normal cost reduction through experience effects and learning (Boston Consulting Group, 1972), the quick fall in the price of consumer goods has other causes also. Fig. 1 shows the comparative rate at which DVD and VCR player prices slashed down in the United Kingdom market. The prominent feature is that while it took twenty years for a VCR player to slash in price from 400 British pounds to just over 40 pounds, it only took four years for a DVD player to fall by the same amount. The same concept is found in markets as diverse as home furnishings, clothing and air travel.

A fundamental change in the global competitive landscape is thrusting prices to the levels that in real terms are as less as they could have ever been. Many causal aspects have contributed to this fresh market environment. First of all there are many new international competitors who have entered the market space supported by low-cost manufacturing bases. The dramatic rise of China as a major producer of quality consumer products is a confirmation of this. Secondly, the removal of barriers to trade and the de-regulation of many markets have accelerated this trend enabling new players to rapidly gain ground. One result of this has been overcapacity in many industries (Greider, 1998). Over-capacity implies an excess of supply against demand and hence leads to further downward pressure on price.

A further cause of price deflation, it has been suggested (Marn, Roegner, & Zawada, 2003), is the Internet which makes price comparison so much easier. The Internet has also enabled auctions and exchanges to be established at industry-wide levels that have also tended to drive down prices.

3.2. The challenge of supply chain costs

It has long been recognized by some that the key to major cost reduction lies not so much in the internal activities of the firm but in the wider supply chain. Back in 1929, Ralph Borsodi (1929) expressed it in the following words:

In 50 years between 1870 and 1920 the cost of distributing necessities and luxuries has nearly trebled, while production costs have gone down by one-fifth. What we are saving in production we are losing in distribution.

The situation that Borsodi described can still be witnessed in many industries today. For example, companies who thought they could achieve a leaner operation by moving to just-in-time (JIT) practices often only shifted costs elsewhere in the supply chain by forcing suppliers or customers to carry that inventory. The car industry, which to many is the home of lean thinking and just-in-time practices (Womack & Jones, 1990), has certainly exhibited some of those characteristics. A recent analysis of the Western European automobile industry (Holweg, 2002) showed that whilst the car assembly operations were indeed lean with minimal inventory, the same was not true upstream and downstream of those operations. Fig. 2 shows the profile of inventory through the supply chain from the Tier One suppliers down to the car dealerships.

In this particular case, the paradox is that most inventory is being held when it is at its most expensive, i.e., as a finished product. The true cost of this inventory to the industry is considerable. Whilst inventory costs will vary by industry and by company, it can be argued (Lambert & Stock, 1993) that the true cost of carrying inventory is rarely less that 25% p.a. of its value. In the conditions in which the automobile industry currently finds itself, this alone is enough to make the difference between profit and loss.

This example illustrates the failure that is frequently encountered to take a wider view of cost. For most of the companies, their description of cost is restricted only to those costs that are confined within the four walls of their organization. However, it has been debated that competition in present world takes place not between supply chains but between companies (Christopher, 1992), hence, the appropriate view of costs has to be "end-to-end" since all costs will eventually be replicated in the price of the end product in the market place.

The necessity to take a supply chain view of cost is more emphasized by the major trend that is noticeable across industries all over the world towards out-sourcing. For many companies today, most of their costs lie outside their legal limits. Events that used to be accomplished in-house are now out-sourced to dedicated service providers. The incredible progress of contract manufacturing in electronics bears witness to this development. If the majority of an industries costs lie outside the business then it shadows that the largest openings for improvement in their cost position will also be established in that broader supply chain.

As out-sourcing increases, the supply chain becomes more like a network than a chain (Normann & Ramirez, 1994) and, as a consequence, the number of interfaces between organizations rises. It is our argument that a growing proportion of total costs in the network occur at these interfaces. These costs have sometimes been labeled "transaction" costs (Williamson, 1985), but in truth, they are much more than the everyday costs of doing business. These costs result as much as anything from the lack of transparency and visibility across organizational boundaries. When we talk of visibility and transparency, we mean the ability to see clearly from one end of the supply chain to another and, in particular, to share information on supply and demand issues across corporate boundaries.

Some of the specific areas where we frequently see challenges in global logistics which eventually affects the supply chain cost are found below:-

High overhead costs to manage the global sourcing and logistics function.

High inventories and lost sales as companies struggle to match supply and demand in the long supply chain

High costs for expedited freight

High levels of inbound lead-time variability

Reactive rather than proactive logistics management

Disconnect between inbound international movements and domestic transportation operations

3.3 Basic terms definitions:

Among the objectives most frequently stated in supply chain management is the reduction of cost along the supply chain. 1 Active partnering with suppliers and customers enables companies to achieve optimization potential beyond the factory gate. Often, these cost reductions are achieved rather as a side effect to other measures implemented in supply chain management. Yet, the developments in cost management thought in recent years have proven the importance of the issue. Therefore, the establishment of a stream of research addressing the management of costs in supply chains forms an important development3 influencing both the future development of cost and supply chain management.

3.3.1 Supply Chain Management

Various definitions of Supply Chain Management have been given. Among the most widely used is the one provided by Handfield and Nichols: "The supply chain encompasses all activities associated with the flow and transformation of goods from raw materials stage (extraction), through to the end user, as well as the associated information flows. Material and information flow both up and down the supply chain. Supply chain management (SCM) is the integration of these activities through improved supply chain relationships, to achieve a sustainable competitive advantage."

It is emphasized that this definition brings together the two major issues of supply chain management; the management of material and information flows is combined with the management of relationships. Only the combination of both aspects addresses the full content of supply chain management. Looking at the material and information flows only addresses logistics issues, while covering the relationships only has already been done in other bodies of literature, such as organization, network management or industrial relationships.

Still, the term Supply Chain Management is in its infancy and a general lack of concepts is acknowledged. Few concepts such as the product-relationship-matrix exist, that specially aim to address both dimensions. Future research will have to improve such concepts and prove their validity. In total, Supply Chain Management is not an issue limited to a certain theory or practice, but a rapidly developing field.

3.3.2 Cost Management

What has just been established for Supply Chain Management is also true for Cost Management. In earlier years, both students at universities and practitioners in their companies had a set of instruments that evolved from management accounting. Data was put together and figures were calculated. As the competitive environment of companies changed, it was not sufficient any more, to arrange past data. Instead, accomplished cost information is needed to manage the future. This has led to the introduction of the term cost management, which can be defined in this way: "Cost management encompasses all (control) measures that aim to influence cost structures and cost behavior precociously. Among these tasks the costs within the value chain have to be assessed, planned, controlled, and evaluated."6 The proactive management of costs7 extends much further than management accounting and has lead to the establishment of a full set of new concepts, such as target costing, activity-based costing, life cycle costing and many more.

3.3.3 Cost Management in Supply Chains

As both cost management and supply chain management are rather platforms for a wide variety of methods, concepts and instruments, it cannot be expected, that looking at the intersection will lead to a single, clear concept. This volume brings together many of the exiting approaches to cost management in supply chains. As given by Securing, the issue addressed can be defined as methods or concepts allowing analysis and control of all costs within a supply chain. While this is a wide definition, originally used for Supply Chain Costing, it covers all approaches taken and does not limit practices used to a certain set. In a particular context, it might be necessary to limit the assessment to a certain set of parameters, i.e. costs, resulting in a meaningful analysis of the model.

Taking into account the SCM definition given above, it becomes evident, that costs are not only created by material and information flows along the supply chain, but also by the relationships with the supply chain itself. The papers that are put together in this book aim to illustrate this.

The remainder of this chapter will provide an overview of the papers presented in the book. They are arranged according to four tracks, explained subsequently:

Developing Concepts for Cost Management in Supply Chains

Applying Cost Management Instruments

Building Cost Management Models

Extending the Scope Beyond Cost

Each section contains a set of papers that offer an insightful discussion of recent research. Concerning the practical content of the papers, here too four different approaches can be found in the papers.

Descriptive Examples show how the research findings presented have drawn from or can influence business practice.

Calculated Examples present data either from real world examples or use model data to exemplify the issues addressed.

Case Studies are used to illustrate the concepts or instruments introduced.

Survey Data shed light on the issues presented drawing from a wider analysis.

3.4 Applying Cost Management Instruments

This section contains papers that provide insights on, how specific cost management instruments or other techniques can be used in a supply chain to reduce costs. Most papers are based on existing cost management or accounting techniques, e.g. target costing, life-cycle costing, activity-based costing, transfer pricing or finance instruments. Still, other approaches, such as electronic data interchange (EDI) or virtual enterprises help restructure or control costs. A wide range of issues is addressed showing that no one single approach will be able to solve all arising problems.

Target Costing is one of the most discussed cost management techniques. Securing builds on target costing methodology and integrates the three cost levels of supply chain costing. A case study from the apparel industry gives evidence how this methodology can help to analyze and reduce costs. Rebitzer builds on life-cycle assessment and integrated cost data into this framework to calculate life-cycle costs in two case studies from the automotive and aerospace industry. Transfer pricing plays an important role in internal supply chains. Mehafdi shows how this can be used and extended towards the development of a balanced scorecard. Financial issues play an important role in these. Stemmler provides evidence, how financial instruments can help improve supply chain performance.

Regional production networks can be organized efficiently building on virtual enterprise thought. Information technology assists in fulfilling orders and manages costs, as Teich, Fischer and Käschel present. Bhutta, Huq and Maubourguet look at the same objectives with the use of electronic data interchange (EDI), which facilitates customer centric approach. Distribution performance and costs play a major role satisfying customers’ needs. Bahrami shows how horizontal cooperation can help reduce such costs in a consumer goods case study. The last paper of the section stays with the topic of distribution, as Kotzab and Teller conducted a survey on how logistics costs are managed in small and medium sized Austrian retail companies.


Basic Instrument

Link to Supply Chain Management


Target Costing

The paper shows how target costing in a supply chain helps to analyze direct, activity-based and transaction costs. Case study from apparel industry.


Life-Cycle Costing

Life-Cycle Assessment methodology and data are used for costing issues as case studies from car and aerospace Industry portray.


Transfer Pricing

The importance of internal supply chains in multinational companies is emphasized and linked to the external chain. A balanced scorecard is integrated.



Finance intermediates are used to improve supply chain performance, especially in reducing stock levels.

Sample calculation provides evidence.

Teich, Fischer,


Virtual Enterprise

A competence based approach helps nonhierarchical production networks join forces between SMEs for improved order fulfillment and costing.

Bhutta, Huy,


Electronic Data


Changing to a customer centric approach, where activity-based costing assists in reducing costs and improve service levels.


Distribution Costs

Horizontal cooperation in a distribution network allows reducing costs by restructuring the distribution network, as sample data emphasizes.


Teller Logistics

Costs A survey on Logistic Cost Data Usage in small and medium sized Austrian retail companies reveals that cost management is a neglected function, still.

3.5 Building Cost Management Models

Models play an important role in the management of both costs and supply chains. Consequently, this section brings together a total of seven papers that take a modeling approach. Still, the papers do not contain only formula, but emphasize how models can help improve supply chain solutions.

The papers show how models can help to generalize problems observed. Reference Models play an important part in such solutions, as Voß and Schneidereit as well as Kaczmarek and Stüllenberg present. While the first paper mentioned integrates this with game theory, the second does with simulation, respectively.

While the customer is meant to be the focus of all supply chain activities, it is usually hard to evaluate what effect lost sales have in the supply chain. Perona presents a model to do so in a three stage supply chain and compares the results of his model to survey data.

3.6 Reducing the cash-to-cash cycle time

From an organizational standpoint, a critical performance measure is cash-to-cash cycle time. From the moment when a business spends money with suppliers for materials and components, through the manufacturing and assembly process to final distribution and after-market support, time is being consumed. That time is represented by the number of days of inventory in the pipeline, whether as raw materials, work-in-progress, goods in transit, or time taken to process orders, issue replenishment orders, as well as time spent in manufacturing, time in queues or bottlenecks and so on.

Detailed analysis of logistics pipelines often reveals that the length of these cash-to-cash cycles can be significant often measured in months rather than days. Anything that can be done to refine that end-to-end time clearly means a release of working capital and hence a reduction in cost. The likelihood also is that most of the time in the pipeline will be non-value-adding time and, in particular, it will be idle time or time spent as inventory that is not on the move. Supply chain mapping can enable the identification of opportunities for reducing inventory and hence cost (Scott & Westbrook, 1991). Fig. 3 shows an actual map for a particular product, a clothing item. The vertical lines reflect the average inventory over the period of investigation at each step in the chain.

Examination of the map highlights the fact that most inventory seems to lie at the interfaces between organizational entities in the chain. In fact, there is a duplication of inventory the supplier carries inventory, their customer carries inventory of the same product. Why is this? The reason is that this inventory is held by both parties as safety stock. Because there is no clear line of sight between the two adjacent entities in the chain—no shared information on the rate of orders or usage both parties have to buffer against uncertainty with additional inventory.

Remove the uncertainty and the need for that inventory is removed also. Essentially, the root cause of this excess inventory is lack of visibility caused by lack of communication. Fortunately, there is now a growing recognition of the importance of shared information in the supply chain. In consumer goods distribution, for example, the adoption of Collaborative Planning Forecasting and replenishment (CPFR) is beginning to make a difference. CPFR, as the phrase suggests, involves the joint determination of forecasts through pooled knowledge and information. Based on this agreed view of demand over the forecast horizon, the supplier takes responsibility for the replenishment of supplies based upon the actual rate of sale or usage. Significant inventory reductions have been reported in numerous pilot applications along with simultaneous improvement in sales revenue as a result of improved availability (Ireland & Bruce, 2000).

Essentially, we have found that customers tend to demonstrate a limited number of dominant’ buying behaviors for any given product or service, and that these behaviors may change if the situation changes. Four types of buying behavior that appear to be present in many product/service situations, but they are not the only ones possible. We have given them labels for ease of discussion.

The mix of these four buying behaviors will differ across product/service categories and countries. Clearly, the "Collaborative" buying behavior is more driven by a need for trusting relationships and predictability, rather than price. The "Consistent" buying behavior is concentrated on anticipated low-cost service, and is very price sensitive. The "Dynamic" buying behavior is price aware, but customers demonstrating this type of reaction will pay a premium if their mostly unpredictable and demanding behavior is met, at speed. Finally, the "Innovative Solutions" buying behavior is only attracted in a quick and creative resolution, at practically any price.

So the key task becomes one of understanding the blend of these and any similar behavior sectors for a given product/service category. Once this is accomplished, a pricing strategy by customer-segment type is certainly developed, especially in business-to-business market places. If the preliminary segmentation is well done, then even if a specific customer is enforced to modify their favored or dominant buying behavior for short intervals because of internal or external pressures, they would usually move to known alternative buying behavior options, thereby making the task of responding much easier than the case where exceptions are continually created, often at excessive cost.



4.1 Introduction

Designing of the research is done mainly to solve the problem of getting the various stages of the research under control. This control factor is very important for the researcher during any of the research operation. Preparation of the design for the research forms a very critical stage in the process of carrying out some research work or a research project.

Research Design in general terms can be referred to as the scheme of work to be done or performed by a researcher during the various stages of a research project.

With the help of the research design, one can very easily handle and operate research work as research design acts as a working plan, which is made by a researcher even before he starts working on his research project. By this, researcher gets a great help and guidance in achieving his aims and goals.

According to Russell Ackoff, research design is the process of making decisions before a situation arises in which the decision has to be carried out. It is actually a process of deliberate anticipation directed towards bringing an unexpected situation under control.

Russell Ackoff has in a great way explained about the research design in his book ‘Designs of Social Research’.

Meaning of research design

Like an architect prepares a blue print before he approves a construction – in the same way researcher makes or prepares a plan or a schedule of his own study before he starts his research work. This helps the researcher to save time and also save some of his crucial resources. This plan or blue print of study is referred to as the research design.

Advantages of Research design:

1. Provides satisfaction and confidence, accompanied with a sense of success from the beginning of the work of the research project. 

2. Helps in proper planning of the resources and their procurement in right time.

3. Better documentation of the various activities while the project work is going on.

4. Consumes less time.

5. Ensures project time schedule.

6. Helps researcher to prepare himself to carry out research in a proper and a systematic way.

4.2 Problem Statement

There are many opportunities to reduce total cost in supply chains, which are responsible for many unnecessary overhead costs to generate forecasts, count inventory on-hand, generate purchase order inputs through MRP (Material Requirement Planning) systems, place purchase orders, wait for parts to arrive, expedite those that are late, receive (and maybe inspect) materials, warehouse, group into kits for scheduled production, and distribute within the plant. These costly and time-consuming steps can be avoided with a spontaneous supply chain, which is able to pull in materials and parts on-demand.

Cost saving initiatives need to be shaped and implemented by all departments in the organization; the entire process of planning, monitoring and measuring needs the support of all. Everyone from the top to the bottom must be actively involved, and work towards the new goals set. Expense reports are obviously the most logical place to start. These should be over a relatively long period of time in order to remove any seasonal variations. It is also important to stay focused on the key areas that account for the major 80% of costs.

Many organizations believe in myths like an "informal program for cost reduction is fine"; or even that reducing costs have a negative impact on quality. Nothing could be further from the truth. The most efficient cost reduction programs are those that very formal / specific and have clear objectives & accountabilities attached to it.

Companies that have been successful in cost reduction realized that it’s not enough to just reduce expenses to remain competitive; rather it takes innovative measures to emerge as leaders. This is why the role of knowledge advisory groups is so important. They help provide a much needed innovative & structured program, designed through practice-proven tools and strategies from specialists.

For example, it is easy to see why so many companies choose to downsize their workforce so that employee costs, which often account for more than 40% of a company’s operating budget, can drastically reduce overall expenses. But how many have actually considered outsourcing non-core functions, like outsourcing the entire supply chain. Many auto & chemical companies around the world have outsourced their logistics, and are saving considerable amounts of money.

4.3 Research Objective

The difference between Logistics cost and Supply Chain Cost, what is included in Supply Chain Cost and difficulties measuring Supply Chain Cost are questions that will be discussed in this chapter. According to Schary and Skøjtt- Larsen (2001) revenue and cost describe the Supply chain. In their opinion cost data gives more information regarding the Supply chain than any other source.

Logistics cost versus Supply Chain Cost

Logistics cost and Supply Chain Cost (SCC) are two terms that are used both in the industry and the academic world. SCC cost has a wider definition than Logistics cost in accordance with the wider scope for Supply Chain Management compared to Logistics Management. Logistics cost is normally referred to as cost components related to distribution cost and cost for warehouse as reflected by the definition of logistics according to Lambert et al (1998). SCC is the total cost in the Supply chain. Bowersox and Closs (1996) define SCC as cost components related to:

Order handling


Stock handling

Systems needed to handle the Supply like for example the order system.


Ayers (2001) write that the SCC is sometimes considered being the same as Logistics Cost. Due to this, some misunderstandings regarding these two terms may exist.

Supply Chain Cost

In this thesis, Low cost Supply Chain product is defined as all cost in a Supply chain. Analysis of SCC can be performed in different ways. Different kind of grouping of cost can be found in the literature. Bowersox and Closs (1996), Chen (1997), Sachan et al. (2005) and Byrne and Heavey (2006) have done similar definitions. These definitions use for example different terms for the same thing like Production cost in the definition of Chen (1997) and Manufacturing cost in the Bowersox and Closs (1996) definition. Su et al. (2005) make a general definition without defining the cost types into different groups.

Chen (1997) says that SCC can be placed in the five categories:

Production cost

Transportation cost

Warehousing cost

Inventory carrying cost

Internal material handling cost.

Sachan et al. (2005) have studied the total Supply Chain Cost in the Indian grain chain. They define the total Supply Chain Cost as the sum of farmer’s price, total additional cost, total mark-up and total wastage.

Farmer’s price is the cost of growing and processing the grain and the margin for the farmer.

Additional cost includes:

Inventory holding cost

Materials holding cost

Transportation cost

Order processing cost

Packaging cost

Total mark-up cost is the amount added to the cost price to get the selling price. Each participant in the chain has his or her own mark-up percentage. Total wastage may be due to one or more of the following three reasons:

obsolete losses

transit losses

pilfering losses

Byrne and Heavey (2006) break down the SCC into five different categories:

Transportation cost

Order processing cost

Production setup cost

Inventory cost

Backorder cost.

Transportation cost is the shipment cost between finished stock in Company A and the stocking location of the distributor. Order processing cost is the cost for processing the orders. Production set-up cost is the cost associated with an order being set-up in the processing areas. Inventory cost is the cost for holding stock for one period. The period can for example be one month or one year. Backorder is the cost for backorders for one period.

Su et al. (2005) define the total Supply Chain Cost as the amortized fixed cost and the periodic operating cost.

Measurement of Supply Chain Cost

Solvang (2001) says that cost is one of the most important performances of a Supply chain. When measuring SCC it is important to know what you would like to measure. Quinn (1998) and Hoole (2005) describe measures of SCC that have been performed. Quinn (1998) describes a study the research and consulting firm of Pittiglio Rabin Todd and McGrath has performed. The firm found that companies considered to be best practice companies in moving product to market had a 45-percent Supply-chain cost advantage compared to the average competitor. The order-cycle time was half and their inventory days were 50 percent less compared to their competitors. Further, their delivery precision was 17 percent better.

According to Hoole (2005), the total Supply Chain Cost can vary by 5 percent to 6 percent of annual revenues between companies in the same industry sector. This is based on a benchmarking of more than 500 Supply chains. Hoole found in his research that companies that have a mature Supply chain are reducing cost faster than less mature Supply chains.

Researchers have focused on SCC savings, conflicts between different units and new customers influence on SCC. Byrne and Heavey (2006) write that improved information sharing and forecasting techniques can lead to total Supply chain cost savings up to 9.7 %. Christopher and Gattorna (2005) discuss SCC savings as a result of creative pricing strategies combined with efficient Supply chain management. The SCC savings provide opportunities for increased profits. Hosang and Bongju (2005) discuss the conflict between different units in a Supply chain. They say that each unit tries to minimize its own cost and is not considering the whole Supply chain. An improvement in production that gives a lower production price is positive for the production department or company. The installation cost might increase more than the decrease in production and the total effect for the Supply Chain is negative Kumar and Kropp (2006) found in their study that new customers and new products could drive up the SCC. Product cost calculating is an important part to SCC. Alnestig and Segerstedt (1997) say product calculation is a comparison of revenue and costs. Product calculation is used to set a manufacturing cost, to estimate the value of items in inventory, to check if a product is profitable, to support the decisions of sales prices, and a part in analysis of customer profitability.

SCC is concentrating on the costs connected to the Supply chain as described above. However this cost can in practice be estimated in different ways and with different accuracy. Rough mark-ups can be used to cover for example transportation costs, order-processing costs etc. Actual costs can be reported directly to a customer order or a customer project. The latter is naturally to prefer if an accurate SCC is preferred and supports for correct decisions are wished. But even for the most accurate SCC a mixture of standard costs, from the companies’ budgets and cost accounting systems, and actual invoiced costs is necessary. Some cost drivers must distribute indirect costs. Therefore measuring an accurate Supply Chain Cost can be difficult. One reason for the difficulties in measuring SCC is that the set up of the accounting systems in a company are not adjusted to SCC measurements. According to Christopher (1998), conventional accounting systems group costs into broad aggregated categories which do not allow more detailed analysis which is necessary to identify the true costs of servicing customers. Christopher (1998) describes two principles for logistics costing that also are applicable for SCC. The two principles are:

The system should reflect the flow of materials. It should be capable of identifying the costs that result from providing customer service in the market place.

The system should be capable of enabling separate cost and revenue analysis to be made by customer type, market segment and distribution channel.

Christopher (1998) also summarizes the dissatisfaction with conventional cost accounting related to logistics management as follows:

There is a general ignorance of the true cost of servicing different customers, channels or market segments.

Costs are captured at a too high level.

Full cost allocation still reigns supreme.

Conventional accounting systems are functional rather than output


Companies understand product costs, but not customer costs.

He suggests that activity based costing (ABC) should be used instead of traditional methods to support the logistics management better.

4.4 Methodological Framework

This section presents the general organization of a systematic review of the domain of "methodological frameworks for low cost products in supply chain management". A systematic review is a review following a rigorous, transparent and reproducible procedure aiming to identify, select and make an analysis and a critical summary of all suitable studies that deal with a clearly defined question (Becheikh, 2008). Its origin was in medical science, but it can be adapted to different domains. For example, it has recently been used in software engineering and management science.

Based on Kitchenham et al. (2009) and Becheikh (2005), the following phases were defined for the present work:

Problem formulation:

This study consists of a systematic literature review concerning scientific papers and technical reports published between 2008 and 2010 on the selected topic, i.e. on methodological frameworks for low cost product impact on supply chain management. The last four years were covered to identify only recent advances in the field, as a previous literature review on the domain was provided by Solomon(1999) covering the period from 2002 to 2007.

Search strategy: the search was performed in digital works only and in the English-speaking literature. The inclusion criteria comprised i) scientific peer-reviewed articles, published in a peer-reviewed journal or conference or ii) technical reports, from well-established research groups, companies or professional societies. The databases employed were Academic Search Premier, Business Source Premier, Google Scholar, ABI-Inform, Proquest and SCOPUS. The final result of this stage was a list of potential articles that had to be analyzed.

Selection and evaluation of the articles: The primary literature search (step 1) yielded 15 papers. Of these, 5 were excluded since they did not focus on low cost supply chain planning, and one was eliminated because the reference was found, but not the full paper. A search from the reference lists of relevant studies led to eight additional studies, which were included in the review process in step 2. In addition, two references already known by the authors. But not spotted by the primary search, were included manually. From the 34

Publications that reached step 2, 27 were eliminated because they did not present specific methodologies for modeling the supply chain processes, and seven were further evaluated in previous step. First Step produced a relative table of all systems for SC cost modeling and next step produced a specialized table on modeling frameworks for lower cost product in supply chain optimization.

4.4.1 Major Research Question

Q1: How many works related to effective low cost supply chain initiatives and their methodological aspects have there been in the past years?

Q2: What research topics do they address (e.g. planning, scheduling, control, supply, distribution, etc.)?

Q3: How many papers explicitly employ methodological aspects in their work?

Q4: Do the frameworks explicitly address the SCM functions and modules?

4.4.2 Minor Research Questions

Q7: What are the required research advances in the domain?

Q8: Which methodological aspects are covered and which are not in the literature?

4.4.3 Independent Variables (IV) & Dependent Variables (DV)

In an experiment, the independent variable is the variable that is varied or manipulated by the researcher, and the dependent variable is the response that is measured.

An independent variable is the presumed cause, whereas the dependent variable is the presumed effect.

The IV is the antecedent, whereas the DV is the consequent.

In experiments, the IV is the variable that is controlled and manipulated by the experimenter; whereas the DV is not manipulated, instead the DV is observed or measured for variation as a presumed result of the variation in the IV.

"In no experimental research, where there is no experimental manipulation, the IV is the variable that 'logically' has some effect on a DV. For example, in the research on cigarette-smoking and lung cancer, cigarette-smoking, which has already been done by many subjects, is the independent variable." (Kerlinger, 1986, p.32)

When researchers are not able to actually control and manipulate an IV, it is technically referred to as a status variable (e.g., gender, ethnicity, etc.). Even though researchers do not actually control or manipulate status variables, researchers can, and often do, treat them as IVs (Heppner, Kivlighan & Wampold, 1999).

"The DV refers to the status of the 'effect'(or outcome) in which the researcher is interested; the independent variable refers to the status of the presumed 'cause,' changes in which lead to changes in the status of the dependent variable…any event or condition can be conceptualized as either an independent or a dependent variable. For example, it has been observed that rumor-mongering can sometimes cause a riot to erupt, but it has also been observed that riots can cause rumors to surface. Rumors are variables that can be conceived of as causes (IVs) and as effects (DVs)." (Rosenthal & Rosnow, 1991, p. 71)

Examples of Dependent and Independent Variables

The following is a hypothesis for a study.

"There will be a statistically important difference in commencement rates of at-risk high-school seniors who participate in an intensive study program as opposed to at-risk high-school seniors who do not participate in the intensive study program." (LaFountain & Bartos, 2002)

Participation in intensive study programed: Graduation rates.

The following is a description of a study.

"A director of residential living on a large university campus is concerned about the large turnover rate in resident assistants. In recent years many resident assistants have left their positions before completing even 1 year in their assignments. The director wants to identify the factors that predict commitment as a resident assistant (defined as continuing in the position a minimum of 2 years). The director decides to assess knowledge of the position, attitude toward residential policies, and ability to handle conflicts as predictors for commitment to the position." (LaFountain & Bartos, 2002)

IV: knowledge of position, attitude toward policies, and ability to handle conflicts. DV: commitment to position (continuing in position for 2 years or not continuing).

4.4.4 Moderating Variables

In general terms, a moderator is a qualitative (e.g., race, sex, class) or quantitative (e.g., level of reward) variable that affects the direction and/or strength of the relation between an independent or predictor variable and a dependent or criterion variable. Specifically within a correlation analysis framework, a moderator is a third variable that affects the zero-order correlation between two other variables. In the more familiar analysis of variance (ANOVA) terms, a basic moderator effect can be represented as a communication between a focal independent variable and a factor that specifies the suitable conditions for its operation.

Mediator variables:

"In general, a given variable may be said to function as a mediator to the extent that it accounts for the relation between the predictor and the criterion. Mediators explain how external physical events take on internal psychological significance. Whereas moderator variables specify when certain effects will hold, mediators speak to how or why such effects occur."

-The general test for mediation is to examine the relation between the predictor and the criterion variables, the relation between the predictor and the mediator variables, and the relation between the mediator and criterion variables. All of these correlations should be significant. The relation between predictor and criterion should be reduced (to zero in the case of total mediation) after controlling the relation between the mediator and criterion variables.

Another way to think about this issue is that a moderator variable is one that influences the strength of a relationship between two other variables, and a mediator variable is one that explains the relationship between the two other variables. As an example, let's consider the relation between social class (SES) and frequency of breast self-exams (BSE). Age might be a moderator variable, in that the relation between SES and BSE could be stronger for older women and less strong or nonexistent for younger women. Education might be a mediator variable in that it explains why there is a relation between SES and BSE. When you remove the effect of education, the relation between SES and BSE disappears.

4.4.5 Intervening Variables

An intervening variable is conceptually very different from a variable causing spurious association:


However, from a data analysis viewpoint the two cases are indistinguishable. In each case, the association between A and B will disappear if the analyst controls for C. In the first case, it is because C caused both A and B or is associated with both A and B. In the second, it is because C intervened between A and B; that is, A causes C, which in turn causes B.

The two cases can be distinguished by determining the direction of causation between A and C. If it runs from A to C, then an intervening variable is involved. In the example of Table 15-1, the interpretation is actually rather clear. It is impossible for the advertising during the test period to influence behavior before that period. Further, it is very possible that past usage did not influence attention to, and readership of, the advertisements and, thus, advertising recall. It is not unusual for the advertising exposure to be higher among those in the audience who use and are thus involved with the advertisement. Thus, it was concluded that the most appropriate model was


If the third variable seemed to intervene between the two variables, the association—even though eliminated by the third variable—would not be deemed spurious, because the link between the two variables still would be meaningful. Suppose that three variables of interest were:

A = advertising expenditures O = attitude of opinion leaders G = attitude of the general population

4.4.6 Assumptions

The development of approaches for research on supply chains cost reduction is fairly recent, since they only began to be studied systematically in the late 1980's. This paper begins with an overview of the main assumptions of the Supply Chain Management (SCM) approach. Based on a partial review of the empirical literature of low cost product in effective supply chain on the automotive industry, the paper then examines whether these assumptions can be confirmed in practice. Since the reviewed literature does not indicate that the aforesaid SCM assumptions have been concretized in the automotive industry, we propose that an initial methodological step be developed to help researchers identify the structural and relational characteristics of the supply chain in question. To contribute to the development of this initial methodological step, a brief summary is made of three schools of thought that may provide the basis for analyzing the structural and relational characteristics of the supply chain: Network Theory, Resource Dependence Theory and Transaction Cost Economics. This analysis of structural and relational characteristics helps evaluate the context in which SCM principles and techniques can be proposed and implemented and, thus evaluate the results that may be achieved through the implementation of SCM.

4.4.7 Limitations

In managing the supply chain cost reduction, the following are limited variables:

Production - what to produce in which amenities

Location - of facilities and sourcing points

Transportation - mode of transport, consignment size, routing, and forecast

Inventory - how much to order, when to order, protection stocks

Due to the many players and complexity of supply chains cost reduction, a problem in one link can have increasingly negative effects on the chain as a whole. There are many areas in which incidents, preventable or not, can hinder production.

Even though more and more systems are able to predict the quantity and types of resources or inputs necessary for production, improper forecasting (over- or under-stocking) remains a problem for supply chain management, especially in response to unpredictable market changes. For example, if there is an unexpected surge in demand due to an unpredictable trend and one of a firm's suppliers is out of stock of a particular part necessary to complete a product, there will be negative effect on the firm. There will be at least a slight delay in production, wasted resources or extra costs incurred from any of the possible reactions of waiting on the supplier, finding a new supplier or shifting the allocation of resources to a different product.

By using business intelligence software to streamline and monitor information from a variety of sources could help the firm in this situation in quickly finding the best way to overcome the problem and waste the least amount of time and resources possible. These systems are imperative in helping businesses keep costs down and satisfy customers with timely and efficient service

Another example of an unpreventable pressure on the supply chain would be a natural disaster. For example, among other firms and products affected by the devastating earthquake and tsunami in Japan, Apple’s production of the iPad was hindered because Japan is the only producer of Toshiba’s 16-gigabit NAND flash memory chip which are essential to the production of the iPad as well as other products. The Japan crisis has also affected industry in that any cargo arrivals from Japan have had to be checked for possible radiation contamination.

Some possible transportation complications include delays due to security issues such as passing through customs, additional costs from importing and exporting fees and taxes, determining the most efficient packing technique, tracking of shipments or delays due to carrier errors. Consequences to possible supply chain management incidents include financial penalties, damage to reputation, lost business opportunities, reduced profitability and high cost of capital.

4.5 Research Design

To achieve aforesaid objectives, some methodology has been adopted. The information for this report has been collected through the primary and secondary sources.

4.5.1 Primary sources

It is also called as first handed information; the data is collected through the observation in the organization and interview with officials and staffs of accounts and financial department by asking necessary questions. Apart from these, some information are collected through the seminars, which were held by the industry.

4.5.2 Secondary sources

The secondary data have been collected through the various books, magazines, broachers & websites.

4.5.3 Target Population and Sampling Methods

A sample is some part of a larger body specially selected to represent the whole. Sampling is the process by which this part is chosen. Sampling then is taking any portion of a population or universe as representative of that population or universe. For a sample to be useful, it should reflect the similarities and differences found in the total group. The main objective of drawing a sample is to make inferences about the larger population from the smaller sample.

A poll is a type of sample survey dealing mainly with issues of public opinions or elections, or people’s attitudes about candidates for political office, or public issues. Polls are conducted by large polling organizations such as the Roper poll, the Harris poll, the American Institute of Public Opinion, and the National Opinion Research Center. A census is a survey in which information is gathered from or about all members of a population

A survey of 2 large private manufacturing companies in UK was carried out using a stratified sampling technique. This was necessary to include low cost supply chain products with all the variables of the study for equal chances of selection. At least 10 percent sample of the population was considered generally acceptable method of selecting samples in such a study. In this dissertation, the sample was stratified into industrial sector, engineering and construction sector based on the value added by each sector to the manufacturing industry. For example, industrial sector added 50 percent, engineering and construction sector 50 percent. The respondents in the study were located mainly in UK respectively, which form the bulk of manufacturing sector in UK and this is where most of the supply chain firms are found. The sample size is denoted by:

n= n1 + n2

2 firms = 50 + 50


n is the sample size

n1 is industrial sector

n2 is engineering and construction industrial sector

4.5.4 Data Collection Instrument and Source

One of the most significant steps in writing a report is the collection of data or information. Because the report depends on the quality of the data collected, the report will be good if the data collected is good (Guffey, 2010). When collecting data in research it is important to take into account, what type of data is to be collected and what method of data collection is to be implemented. Data collection can be expensive cost wise, but depends on the nature of the project. However, data collected plays an important role in determining the research problem (Stevensens, Wrenn, Sherwood & Ruddick, 2006). The following sections give a detail description about the types of data and methods of data collection from theoretical point of view and further addresses the data used and the methods of data collection implemented for the research.

Types of Data

Stevensens et al. (2006) state that there are two types of data:

Primary data: Data that is gathered by a researcher for the first time for a particular ongoing research project. According to Guffey (2010), primary data is that collected through firsthand experience. Primary data can be gathered by applying either of the two basic research methods, qualitative or quantitative (Stawarsk & Particia, 2008.)

Secondary data: Data that has been formerly gathered by other researchers for other reasons. Guffey (2010) mentions that secondary data results from reading what others have experimented with and observed. In addition to these, Guffey (2010) adds that secondary data is simpler and has lower cost to develop and to use than primary data which might mean interviewing large groups and distributing questionnaires.

For this research the authors use both, primary data through interviews to get a relevant and reliable data to make a good research and secondary data from different sources, such as books and articles as a supportive data which helps in building the frame of reference for the study and gives a guidance in making analysis with the findings systematically and properly.

Methods of Data Collection

Philips and Stawarski (2008) illustrate that there are different ways of collecting qualitative data among these, the most commonly used ones are three: Interviews, focus groups and observations. Kothari (2004) state that for selecting the appropriate method for data collection, a researcher should keep in mind the following key factors:

Nature, scope and object of enquiry: This is the most important factor that influences or affects making a choice on the particular method to be implemented. This factor also plays an important role in making the decisions on what type of data to be used, primary data or secondary data.

Availability of funds: Availability of funds plays a big role for selecting the appropriate data collection method. When there is limitation of funds the researcher has to select a cheaper method for collection of data even though it might be less efficient and effective method compared to other costly methods.

Time factor: It is important for a researcher to keep in mind the availability of sufficient time before making a decision on what type of method is to be used for the data collection.

Precision required: Being precise is another key factor to be taken into account by researchers when selecting the method of collection of data.

Due to the nature of the research, which is based on conducting the research using qualitative research approach, which needs to make a deep investigation the authors discovered and applied interviews as the relevant data collection method. Therefore the authors used interviews as the main data collection method. Besides these, while gathering the data for the study the means of communication used with the concerned contact person of the firm chosen for the research was through internet by using Skype.



5.1Quantitative Analysis

Having introduced the SCMS implementation schemes, it is feasible to look into the details of how much each scheme will cost by referring to the cost model. In the model sensitivity analyses section, the 13 model variables have already been split into two categories: environmental factors and control factors. For a fair implementation scheme comparison, the environmental factors should be kept identical. While for control factors, the cheap but reasonable choices based on the supply chain environment are specified for the four schemes. Under this premise, the respective cost lines can be drawn along with the progress of process development. This is the plan of the scheme comparison experiments.

5.1.1 Case study of system comparison

The following scheme comparison experiments are still based on the small supply chain scenario specified in the previous table. The control factor values for the four implementation schemes are determined respectively by the price information collected and by experience or assumptions due to their implementation dependency.

It is arguable that more or less personal bias in specifying the values is involved, but the model results are subject to this specific case study only. Apart from the common supply chain environment conditions, it is supposed the COTS has 40% initial process coverage before any customization [wµ = 0.4, which is fairly high) and a open source product is available to have initial process coverage of 20% {lui = 0.2) as the opponent. The COTS in this example is considered well-constructed (which is to say it has less bugs with well-designed maintenance routines) hence it introduces a lower unit running cost (µp = 0.18) than the others. Due to the close-sourced nature, the COTS is probably slower (r = 120) and more costly [dc = 1000, dc' = 3000) to have functional extensions. Variables for other schemes are specified accordingly by referring to their respective strengths and weaknesses as discussed previously.

Table 4.1: Value matrix for implementation scheme comparison

With the implementation scheme conditions specified, SCMS total costs can be calculated in pace with the developing progress W2 to shape a cost trend line for each implementation scheme. Table 4.5 presents the cost result matrix at 10% increment interval of W2. The cost transition can be clearly discovered by filling the cost figures into a curve chart (Figure 4.1). In this way, the cost results are directly comparable at same post-development levels. Considering the objective of cost effectiveness, a "fully automated SCMS" is neither the best choice for end users nor the intention of this case study. In effect, manual handling is more preferable if the overall cost is lower. Based on this perception, the overall minimal cost among the four schemes can be easily discovered together with the condition to achieve it. This result indicates the optimal implementation plan one should follow.

Table 4.2 - Scheme costs comparison (Minimal values highlighted)

The results reveal that for this experiment setting, the COTS is the winner. It reaches the overall optimal cost with no customization at all. The common possible reason is either due to over-expensive developing cost {dc, dc', r) or low total process frequency [D) that prevents computer automation from being the more economic choice. There could be more possibilities subject to respective implementation environment. For instance, a higher labor cost / i^ would encourage the degree of computer automation.

Surprisingly, the open source scheme demonstrates its strong competitiveness at the low iU2 band, despite its much lower initial process coverage (where W1 = 0.2) than the COTS (where W1 = 0.4) . The framework scheme has a U-shape cost trend line. The cost turning point is an important index as it is uneconomical to continue the process development after that point since the same total cost can be achieved by doing less system development. Nevertheless, at high W2 band, the framework scheme shows its best competitiveness. The proprietary scheme loses its point at both low and high W2 band therefore it is not recommended to take this approach unless the supply chain is really simple or small scaled.

Figure 4.1 Curve chart representation of scheme costs comparison

5.1.2 Effect of supply chain size on the four schemes

So far, all the experiments were performed on a small supply chain experimental environment with process type count of F = 150, dramatic discrimination might exist in supply chains of different scales. To have a full picture of the cost trend against supply chain size F and process type share W2, it can be achieved by considering the F and W2 as independent variables to observe the cost transition in a 3-dimensionaI space. Figure 5.2 plots the cost results for each scheme as a surface in the range of F e [0,500], which covers small to large size supply chains.

5.2 Importance of Early Preparation

According to the results of the previous experiments, it is noticeable that the process share wi has a substantial contribution to the final cost. To a SCMS, ivi is not only meaningful to ready-made software packages (COTS or OSS) but also self-developed systems (Framework or Proprietary). In the latter case, wi indicates the share of preliminary development before the supply chain system functioning, if the high frequency processes are already known at the early stage. The significance of early stage preparations (include stages of planning, requirement collection and analysis, system design) has been recognized by most software engineering researches and project management literature (Murch, 2000; Sommerville, 2000; Hedeman et al., 2005). This cost model provides an effective way to assess the weight of W] in a quantitative way.

In the following experiment, the influence of w-[ is evaluated in such a design: keep the manual process share constant (i.e. wy + W2 = 0.9), increase ivi from 0 up to 0.9 to inspect the final cost (the bounded W2 decreases from 0.9 to 0 accordingly). All the other variables remain at average values specified in the value range table (Table 4.1). As the implementation schemes basically imply different set of values of the cost model variables, the conclusion is therefore universally applicable.

5.3 Influences of Developing Team

The developing team is another important "manageable" aspect to the SCMS planner. Regardless whether the project team comprises of internal, contracted or combined developers, some elements are common in successful SCMS practices.

The key points and techniques have been well stated in software engineering literature (Brooks, 1975; Sommerville, 2000). A SCMS, as it still falls in the scope of software products, should be able to inherit these research outcomes directly. Further details in this area are out of this research scope but easily attainable by referring to software engineering research publications, such as the literature mentioned above.

For a complete SCMS implementation guidance, some key points have to be briefly discussed to establish the links between the proposed cost model and traditional software engineering research outcomes.

Experience The experience of a SCAIS project team indicates not only technical skills but also knowledge of the particular supply chain environment. Therefore a hired developing team with high technical skills is not necessarily the best choice. The degree of experience can influence model variables of the average process develop time r and also the unit system operating cost fXj,. A lower fip in a well implemented SCMS has remarkable influence to the total cost reduction. Priority The cost model takes the proper process developing priority by occurrence rate of respective process types as an implementation premise. Failure to follow this condition incurs unnecessary high cost in the end.

Team-size One aspect that deserves careful leverage is the size of the developing team: resource consumption of a developing team (salary, management overheads, computers, workspace, etc.) increases along with its size but not necessary the productivity. It is also a waste to maintain a large team on a small scale supply chain project where uncertainty is substantial. Literature research is strongly recommended to achieve a good balance between the team size and its cost.

5.4 Analysis summary:

In this chapter the prime SCM implementation related cost effective analyses, i.e. implementation scheme, developing team size and early stage preparation are performed by exploiting the low cost model. In the implementation scheme section, it has been stated that there is no absolute best solution to all SCM - The total cost is a combined effect of technical, environmental and user-specific conditions.

In order to obtain reasonable outputs from this cost model, SCM planners need to have a deep understanding of the introduced cost model variables as well as their own supply chain environments. With the provision of this quantitative low cost model, planners are encouraged to carry out further experiments in addition to the ones already introduced, to satisfy their own supply chain demands.



This chapter reviews the research work in association with relevant research initiatives discussed in the literature review to show what have been achieved. It also summarizes the advantages and limitations that have been discussed throughout this research.

6.1 Research Summary

The ultimate intention of this study is to assist in determining the best practice of a supply chain management system from the cost effective point of view. The research results confirmed it was achievable by using appropriate technologies and plans. This study achieved the objective by developing a mathematical temporal cost estimation model which was suitable in the context of supply chain management since commercial software systems were mostly elicited by potential profit returns. This model facilitated the information system cost estimation in the supply chain environment by paying prime attention to its uncertainty and flexibility. This cost model considered the manual work as part of the whole "system" in addition to software applications, therefore a complete projection of the actual benefits against costs over the time was shaped. This study inherited a few ideas and methods from the information system cost model of Gebauer and Schober, but resolved the problem from a different perspective. The primary reasons for designing a new cost model instead of reusing or modifying other cost models in the supply chain context were subjected to the following considerations:

Change is the nature and advantage of supply chains. It is not realistic to get the SCMS fully ready in the beginning and keep it invariant afterwards. To obtain a precise estimation, the information system development should be treated as a persistent activity along the system lifetime.

This cost model assumes that the system development is progressed in a sequential manner. It is due to the following reasons:

Firstly, it is the common developing pattern of bespoke systems since the team size in most cases is limited and fixed. A stable team size is recommended by software engineering researches as change of developing team incurs many management difficulties;

Secondly, supply chain related changes occur throughout its whole life time, which turns the system development into a persistent developing loop as the details of changes have to be captured before proceeding software development. This is the prime reason to develop a new cost model instead of inheriting from existing methods.

Performance measurement and KPI based approaches are dependent on personal experience. The complexity increases exponentially in large supply chain environment when cross-referencing with business demands.

This leads to the problem of incomparable or meaningless performance indicators. This temporal cost estimation model is a more systematic solution.

This cost estimation model construction was started from a single generic process cost analysis, followed by the multi-process cost composition, where the developing work was arranged for processes one after another. Based on the multi-process cost trend line chart and its mathematical representation, the total cost was split into several cost elements, each of which was reviewed and simplified by means of the Lorenz Curve and mathematical theorems.

During the course of model construction, a set of variables were introduced to convert the cost model from discrete process cost composition into statistical abstraction. In this way, the supply chain system planners were relieved from technical prerequisites, or excessive implementation details which were barely known at the early stage of the supply chain projects.

The sole cost estimation model did not provide sufficient guidance on how to achieve cost effectiveness for actual supply chain exercises. To overcome this problem, several analytical experiments were performed to establish random experience of mapping actual supply chain environment onto the model. By identifying the variables from fixed characteristics of a particular supply chain, the cost saving task was turned into a mathematical exercise of finding the minimal value of a multi-variable function (or a single-variable function in simple cases). In addition, to help cost model practice, the cost sensitive variables that are worth planners' extra attention were also assessed in the model analysis sections.

6.2 Advantages Of The Low Cost Production In SCM

First of all, as a mathematical quantitative model, it is superior in areas of cost estimation compared to empirical performance measurement methods, particularly when there are only few similar research initiatives to cross-reference with (Creswell, 2003). Considering the 13 model variables and their interactions, hundreds or even thousands of guidelines and performance indicators might be needed to achieve the same effect, provided that users are still able to follow. This model is universally applicable since demands of local knowledge or information technology background are minimized.

6.3 Limitations Of The Study

The major limitation of this research as a whole, lies in the lack of large amount of industrial case studies to verify its feasibility. Supply chain management system implementation is usually a long term process which requires continuous accounting tracking. It is rather difficult to conduct an effective case study for this type of research. A convincing conclusion from case studies requires not only sufficient amount of studies, but also a wide coverage of various sized low cost SCM implementations. This, however, requires a long term continuous research.


There is only a small amount of cost model variables for the system planners to balance at the planning stage, in accordance with their own supply chain environment. The model variables (Table 3.1), derived from supply chain process cost composition and statistic abstraction, have pragmatic meanings hence are easy to be assigned. In addition to the cost model, analytical experiments were also performed to address the prime SCMS planning issues before system development.

As a result of the time-dependency of this cost model, the cost trend at each project stage can be investigated for accurate financial arrangement. This cost visibility is a very beneficial feature in reality. After all, the supply chain system host company's major concern is how it achieves savings in the end.

This cost estimation model managed to avoid excessive empirical elements and implementation details as required in typical VBSE approaches (the COCOMO II for instance). This model might not be superior in terms of accuracy but it is more intuitive and practical to apply. In addition, with VBSE approaches, users may get very different results due to the diversity of understanding of empirical factors. This should not occur to the proposed cost estimation model, which mostly encompasses variables with pragmatic meanings.


It is important for a company dealing with Low Cost Product to have the followings structure in their organization in order to attain the best result

Negotiation of the right price for the product- A seller or the Buyer dealing in Low value commodity should always ensure that his product is sold at the right price fetching him a reasonable profit margin. Many times competition in either selling or buying a Low Value product compels either of the party to conclude a price level in haste which ultimately results in a huge loss to the organization. Over production of a product which is of Low value compels a manufacturer to sell his product at a very thin margin hence concentration is to be given in this area by the manufacturer.

Verifying and determining the availability of right shipping line- When finalizing a purchase of a product it is important for the buyer to ascertain all details about movement of the cargo from the place of procurement. If the buyer does not have a proper control on movement of the product it is always wiser or him to negotiate a Cost and Freight pricing leaving the choice of shipping the product to the relevant destination in the hands of the Exporter / Shipper. There are cases where a product intended for procurement may be cheap in a particular area. The fact that the cost of the raw material is cheap gets defeated if such an area does not have proper transportation connectivity. It is very important that the place of procurement has enough number of Lines providing service to the intended destination as only then a consignee can get in to negotiation of a volume based competitive price.

Organized Professional Staffing

1. Administration team- They should coordinate on the time of dispatch or receipt of document such as Bills of Lading, Packing List and Invoice. These play an important role in clearance of a shipment on time. Many times non receipt of documents on time results in delayed processing of papers with the relevant authorities brings an ultimate result in payment of a huge sum toward Detention and Demurrage which ultimately brings down the profitability of the low cost cargo

2. Operation team- plays an important role in filing necessary papers on time and coordination with the concerned authorities to emphasis rapid clearance of a low cost product to the factory or ware house. Fragile operation teams with lack of experience lands an organization in delayed process thus resulting in huge cargo Detention and Demurrage.

3. Finance Team is in charge of preparing a shoe string budget and brings in a total control on all logistic movements. It prompt payment of duties and governmental fees, on selecting the most economical shipment Shipping related charges and Cargo related charges reserves the right amount of funds payouts. Finance planning is an important factor while dealing with the clearance of low cost cargos.



In this study, it has been proved that the supply chain management system implementation cost can be estimated, despite the high uncertainty and flexibility of supply chains. The prime challenges at the low cost SCM planning stage have been resolved by a mathematical cost model, with associated system implementation analysis and discussion.

The low cost SCM planners should be able to cross-reference the benefits against costs to make appropriate decisions by means of this model. In addition, low cost SCM planners can also assess the feasibility, scale and implementation scheme of their own low cost SCM without much difficulty.

As already stated in the literature review, the majority of information system cost estimation methods either require excessive details and blurred adjustment factors, or lack solid evidences of the correlation between individual practices and the empirical guidelines. The steep demand of experience and technical skills also obstructs the successful application of those methods.

This study has constructed a new temporal cost estimation model that can satisfy the objectives without the shortfalls of both empirical guideline-based and software engineering-centric approaches. This cost model adheres to the practicality by focusing on the coarse characteristics of a supply chain. The weak relation with information technologies also benefits the feasibility and durability of this cost model.

This study is a step forward towards sophisticated low cost product supply chain management system implementation. With no doubt there are still areas to be refined. This, however, depends on availability of resources and in-depth surveys.