Keywords

1 Introduction

Nowadays the emerging smart business emphasizes deliver the overall service quality considering the aspects from better security, outcome consistency, professional attitude, task completeness, specific conditions, available as needed, and comprehensive training [4]. These services, apply and integrate a number of components, play as the conveyer to deliver the continuous values to the recipients. The unique features of these components are the cornerstone to differentiate with the rivals. The common core of these smart businesses, illustrated in Fig. 1, who provides a number of customer-centric touch-points to the customers; each touch-point incorporates service components collaborated by machines and people. The backend support is a composite functional unit, covering the social—understanding the needs, technological—facilitating the business processes, economic—scheming the revenue and profit models, and strategic—positioning the competitive service in the marketplace—perspectives [5] to identify and create value to the customers. The customer service maintains the intimacy and collects the complaints and the potential needs of the customers. Lastly, the quality measurements are applied throughout the processes to evaluate the performance and the effectiveness of the initiatives and recommends the proactive improvement amendments.

Fig. 1.
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Smart business operation

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These smart business innovative services adopt the technology to strengthen the interoperability among their value chain though: (1) more complex, bundled, and fast delivered products and services; (2) adopting boundary spanned value co-creation model; (3) systematically orchestrating the coordination and control; (4) endeavoring the information and knowledge sharing; (5) building a business operation supportive infrastructure; and (6) always incorporate the customer experiences into the heart of the service design and delivery [6]. Obviously, the successfulness of collaboration determines the quality of the service owing to the effectiveness of establishing the shared vision about the market positioning and the efficiency of group problem-solving proactive actions taken. In order to pertain the customers, not just delivering the products and the services, but also giving the confidence of using them by providing the material traceability as a significant mean of improving the branding.

It is an agreeable strategy for smart business that the technology-enabled interoperability-strengthen initiatives are a part of smart business experiments in which it is an exploratory journey in creating the rare, imperfectly imitable, and non-substitutable competence as resources, from the resource-based view perspective [7], against the rivals. Many innovative concepts—applying the out-of-box thinking and measuring everything that matters—have injected into the new business model, such as using the analytics to find the tacit knowledge of business activities or employing the smart sensors to give a new customer experience [8]. But how to effectively build a value chain, cultivating the non-imitable resources, to maintain the products and services are at consistent quality level through the material traceability system as a business experiment to improve branding?

This paper, aiming to the perfection of supply chain management, presents the feasible approach of conducting the material traceability project through a rigorous requirement soliciting process, it introduces a novel perspective of supply chain competition dynamic model in which it disclosed why such a value chain is not easy to build because of there is potential business completion within the chain; and from those conflict factors, it proposes a better value co-creating model for the supply chain. Most importantly, this paper arguably suggests a more efficient data model of the material traceability system to simplify the design in contrast with the current commonly used schema-oriented approach.

2 Supplier Competition

There are two simple business logics of firms, shooting for either the profit maximization or/and cost minimization [9]. It seems to be a duality problem—same purpose but different angles to cut in, but their essences are different. In fact, the profit maximization goal is more related on the sales end, for example, the firm places a higher pricing strategy by delivering a product with unique features, better design and quality to the customers is a common approach; on the contrast, the cost minimization goal is more on the supply end, under the current production configuration—the execution efficiency and the product structure, the firm acquires the material from the qualified vendor list and asking for lower price. Under the cost minimization model, when the material is not from a single source and it can be provided by multiple suppliers, it will cause supply chain competition.

If cost is the major concern, the suppliers have no better way to win the competition but keep pushing downward the material price. No supplier has the definite confidence to will the order. During the multiple order biddings of various buyers, the total quality of these material requisitions might exceed the supplier’s production capability. That is one of the reasons why, from time to time, the production is suspended awaiting the arrival of the required material. When the material is emergently short during the production cycle, the firm has to solicit the material from the market in time, the price and the quality might not be expected as it should.

The supply chain partners will be motivated by the firm’s business logics, seeking for customer perceived value—profit maximization or the higher quality/cost benefit—cost minimization. As mentioned before, the supplier competition is inevitable under the cost minimization scenario. Supposedly, illustrated in Fig. 2, a factory is going to produce the product X, it procures the materials in order to build it. The factory invites a couple of qualified suppliers from the approval vendor list, say they are three suppliers, S, A, and D in this game; then the factory releases the material specifications and requesting the invited suppliers for bidding. These three suppliers are seeking the opportunity to maximizing their profits, also bidding for the product Y which competes against X with some product differentiated features of another factory at the same time. Because the three suppliers are on the same approval vendor list, it implies that their quality levels are also above the specifications; therefore, the price dominates the factory’s choice. Luckily for the supplier D who wins both bids for better quality/cost; however, these material needs will impose the material delivery pressure—might be less expected by its planner—to its production.

Fig. 2.
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The supply chain competition dynamic model

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Since the model is valued for lower cost, the winning supplier is also looking for its cost minimization; the potential risk for the procurer is either the delivery is delayed, or/and the quality is compromised. When business is booming during the hot season, the suppliers have less motivation of joining this less confident bidding opportunities; this will cause the procurer to provision the material with higher buying prices and the incurred extra inventory staging costs.

To avoid the potential side-effect of the supplier competition, many firms are seeking for increasing the customer perceived value through innovation as the mean of profit maximization [10]. A product Z applying the cost minimization contrast model, instead of releasing the material specifications to a couple of suppliers after the product design, the firm encourages the selected suppliers to participate the design in the early phase and closely collaborating in production. The innovation comes from the synergy of all participants; since this model putting the product differentiation in the first place, the supplier’s competition game rule has been changed from the lowest price to who can offer better value to the product. The innovation always prevails, thus the true profit winner in the market will go to the product Z; and it expels the other products X and Y out of the high profit market segment. The relentless cutting the cost scenario causes low profit margin; this is the nightmare that no firm would want to have.

3 Material Traceability

The material traceability is a process about recording the source of where the material came from and how the component was built appropriately. The information system makes the objective of material traceability achievable. Under the current business model, the product and the service delivery are synergies efforts of the integrator and the component suppliers making. There are non-technical critical challenges must be resolved before such a system can be in place: (1) asymmetric bargain power—not all integrators have the dominating power to ask their suppliers to comply with the instructions for improvements; from time to time, the key component suppliers hold the calling cards at hand that makes them superior during the negotiation; (2) credible proof—the integrity is above all; the whole system depends on the correct and non-manipulative data reported; (3) shareable data repository—many firms are still using less efficient ways of exchanging the data, such as sending the spreadsheet files over the emails; it is very hard to track and maintain the versions of data especially when multiple parties involved in the communication loop; (4) collaboration—the value of traceability depends on the degree of information visibility and the disclosure in depth; the traceability involves all parties to participate the improving process; the participants have different business priority when a jointly-communication is needed, this will make the collaboration more difficultly and less effectively; and (5) obligation to comply—in many occasions, the integrator procures the components majorly according to their lower prices; the suppliers will hesitate to comply the costly quality improvement instructions under such a short-term and no-commitment business relationship.

Effectively tracking the material sources is not as simple as it appears to be but more complicated rather. A product is made through a series of steps; each step requires the associated components to complete the process. These components were procured by purchase orders from various suppliers. From the components supplier’s view, the components were also made through a series of steps; each step adopted a number of materials to build. It is worth noted that these components and materials may come from different suppliers at different times. The goal of traceability is not just giving the information about the material sources; it is very important that in case of the defect occurred, the system will reveal the responsible components and the associated materials information sufficient enough to support the following amendment process can be undertaken.

The finish good is built based on the production steps; each step may employ a number of materials to produce the final or the semi-product. The Fig. 3 illustrates a general case about the material traceability. A finished good is made of a series steps from P1 to Pn. The step P1 requires the material M11 and M12 in order to build the intermediate product Pb1 which will be used in the following step P2 as the input. The step P2 requires M21 and M22 in order to build the intermediate product Pb2 which will be used in the following step P3 as the input; and so on to the step Pn. The material suppliers are also taking the similar processes to fulfil the production. Obviously, the traceability data schema is not easy and efficient to be described as common two-dimensional—simple spreadsheet-like table—approach, it has to use several master-and-detail tables to serve the purpose. This will make data traversing recursively in order to track a suspicious material usage.

Fig. 3.
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The complexity of material traceability

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4 Data Model

The production is lot-driven; in the just-in-time model, when a sales order is received, the planner assigns a/several lot number(s) to fulfil the order. Each lot number represents a production order and triggers material procurement if the stock quantity is shy. The supply chain department proceeds the procurement process; some certain criteria are in place to qualify the suppliers, such as price, quality, and delivery time, etc. There is no guarantee that the material is procured from the same supplier as before. In fact, it is a common practice that the material came from various suppliers at different times within the single production lot. Therefore, the data model for the traceability is not a row-based record—each row at least contains the following fields: (1) material identifier; (2) quantity needed; (3) lot identifier; and (4) supplier identifier—this model fails to keep tracks on the suppliers, but a graph/tree one in rather [11].

While in the graph/tree data model, a sample material requisition graph illustrated in Fig. 4, each lot is a node containing: (1) lot identifier; (2) production date time; (3) product quantity required; and (4) a sub-tree of material sources. Each material source has its children nodes, each child node contains: (1) lot identifier; (2) production date time; (3) supplier identifier; (4) quantity needed; and (5) material procurement order identifier. And these material source nodes link to their associated procurement order details in another table.

Fig. 4.
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Sample material requisition graph

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By observing the above sample graph, the start node, marked as 100, contains the production lot information. The start node links to four material nodes, marked from 100-K100 to 100-K400, contain the material information required in this lot. Each material node, marked with their associated supplier identifier with the suffix from -01 to -07, contains the requisition information. Another worth-noted point is that in this sample model, the lot 100, material K200 only has one supplier -05 and the supplier -02 provides the material of K100 and K300 in this lot.

The benefits of using the graph model are: (1) readability—the planner can easily visually understand how the material requisition is in the lot; (2) preference—a derived supplier perspective view, also a graph, can reveal who the critical suppliers are; (3) tracking—since each material node links to the associated procurement orders, in case of quality issue occurs, the material requisition graphs can be extracted to show the production lots were using this material and to calculate the potential impact imposed from this supplier; (4) alternative—when product changes its configuration due to cost/quality preference or design simplification reason, the planner can calculate the cost saving and the stock provision level for the coming sales orders; and (5) management—once the material supply routes are clear, many operations can also be optimized, for example, the warehouse can re-arrange the material bins to fulfil the production smoothly; the logistic staffs can make a better shipping schedule in terms of delivery time and saving the transportation costs.

5 Smart Business Experiment

The empirical case, an OEM firm of a giant sporting shoe-maker began their innovation journey to promote the idea of material traceability to the supply chain participants. By closely collaborating with the participants, setting up the goal, co-creating the requirements of the system, and implement it. The firm and the participants had positioned this innovative initiative as the leading project toward the smart business—transforming their business logic from current cost-minimization to a profit-maximization model; it is a business experiment—a value exploratory process of supply chain initiative scale aiming to increase the customer perceived value—in essence. There are several major challenges in implementing such a traceability scheme:

  1. (1)

    What is the best way to collaborate among the supply chain? The traditional ways were for transactions and clarification, such as EDI (Electronic Business Document Exchange), email, and recently commonly uses—network shared storage. The goal should be set for a higher purpose above the business transactions, to co-create and co-produce the value aiming to better quality assurance.

  2. (2)

    What kind of data, in terms of schema, that will serve the traceability diverse purposes? At least the traceability should meet both business transaction and the quality assurance needs. Such a data schema contains structure information and the non-structural objects, such as the detail non-functional specification, the images of the items, or the audio effect during the reliability tests.

  3. (3)

    Recording the production history—from the customer order taking, via procurement, to the distribution—is a complicated process. The product inventory serves the customer orders first; if it is insufficient, then places further production schedule to build in a cost-effective way. This implies that a customer order may contain the information from several production lots, and each lot may also contain the material from various procurement orders and even from different suppliers.

  4. (4)

    How to extend this traceability value to benefit the customers—turning the investment into potential revenue? What kind of the traceability information that the customers matter the most? What will the service model be to increase the brand equity through disclosing the material traceability?

To reach the consensus about the aforementioned challenges among the supply chain members is not an easy task; this paper presents a requirement solicitation framework, an external expert team shall facilitate the whole process.

6 Implementation

The project implementation framework adopted the methodology of the Enterprise Architecture iterative approach [12], illustrated in Fig. 5. This framework consists of three parts, the first part (the left-top portion) is to identify the problem frame—the boundary of the mission to accomplish; the second part (the right-top portion) is to outline the top-down layers, from business, operation, to the system, described in a consistent modeling semantics (the architecture description language, ADL) so that them can be used throughout the journey; the third part is the execution planning (the bottom portion), in which it embeds with an outcome measurement scheme to see if the initiative is heading the expected direction and to acquire the findings as the baseline to the next phase improvement.

Fig. 5.
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The requirement solicitation framework

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First, the project manager invited several participants playing the key roles in the product production cycle, from the bottom of raw material supply to the top of whole-shoe assembly. A project executive board was formed with the help of the selected consulting firm as the steering committee regularly shared the thoughts, discussed the managerial tasks, resolved the issues, and monitored the project progress. The executives defined the service scope as: (1) positioned this was a pilot project; (2) picked the product models with minimal suppliers involved; (3) limited the material tracking level to three—product, components, and row material; and (4) focused on the material that the customers would concern the more. The initiative goal had three folds: (1) to design a material traceability system; (2) to set up the standard operation procedures for the system; and (3) to train the staffs the best practice.

Deriving the tasks from the service scope and the initiative goal, the executive board defined the problem frame—a requirement soliciting terminology, setting up the role and the responsibility facing toward the potential problems as follows: (1) service—elaborating the value, supply chain awareness, promoting the system, and conducting the training; (2) science—designing the system architecture, data schema, efficient ways of adding and querying the traceability data; (3) management—managing the project schedule, resources allocation, making reports; and (4) engineering—based on the design blueprint writing the programs, interfacing with the sensing devices to facilitate the inputs of tracking data, sustaining the system, and deploying the system.

The project team, grouped into the aforementioned four subject matters, cooperatively presented the whole picture of the material traceability in three hierarchical layers: (1) business architecture—describing the context of the system, the perceived value to the customers and the supply chain, the return of investment; (2) operation architecture—setting the corresponding procedures from the sales order taking, procurement process, component/material delivery, to the fingerprints and certificates of the source; and (3) system architecture—designing the information system architecture, including the servers, data storage, networking, and the budget/time estimation. Based on these blueprints, the team made recommendations to the executive board so that they could discuss with, reach the consensus, adjust the content of these architectures, and come out with tangible decisions. The executives brought these architectures back to their firms to conduct further evaluation and came out the gap analysis respectively. The consulting team consolidated these gap analysis reports and design a series of sequencing plans to mitigate these gaps and deliver to the project team to execute. An outcome measurement scheme was in place to ensure the plans had been well conducted by the principles and meeting the set expectations. Finally, by examining the open issues of the problem frame, a strategy alignment analysis was brought out to the executive board to see if those missions were met in what degree after the project completion. The board set separate initiatives for individual participants to keep up with the goal and continuously to improve the precision of the material traceability.

7 Conclusion

Although the material traceability is not a new story; from the simplest form of the material traceability just stating the origin of the material to few products being willing to disclose their components’ manufactured dates; most material traceability systems are for in-house tracking purpose not in supply chain scale as the empirical case was. Establishing a shared vision and optimizing the collaboration, setting up the material traceability, across loose-coupled firms is a challenging task.

There are much to learn from the case: (1) leadership—it is common that the material suppliers lack of motivation to initiate the optimization, awaiting the brander to call on the coalition; but the enthusiasm came from the key component suppliers to take the lead is rare; (2) priority—each supplier has its own hidden agenda and business priority especially when its model falls into the cost-minimization scenario is reluctant to participate this business experiment unless the benefit is obvious; has multiple; (3) method—the participants were from various disciplines and the knowledge backgrounds; it was very difficult in consolidating their described facts and elaborated ideas into a systematic form until the Enterprise Architecture methodology was introduced in; (4) knowledge—the participating suppliers did not have all the experiences and knowledge that the traceability initiative required; it was necessary to expand their boundary by recruiting the consulting team to guide the initiative; to assemble a cross-firms virtual teams—the knowledge circle—to deal with the problem frame needed strong commitment from their executives; (5) training—it was the most critical core of the business experiment, not just disseminating the knowledge and the value of the traceability, but also realigning the different perspectives into a clear and executable initiative; and (6) awareness—the optimal goal of the traceability is to increase the customer perceived value of the product; it is evenly important than the system itself to let the customers aware the profound meaning—safe to use, green to Earth, commitment in quality perfection—of this investment.

The supply chain was meant to optimize the overall processes and to reduce the inefficiency waste in the 20th century. Unfortunately, the harsh business environment forced some manufacturers to play the cost minimization game, especially, the relentlessly seeking for the lowest labor cost region caused the bad name of exploitation. In the recent years, many firms began the business transformation journey pursuing another angle of doing the business—profit maximization. The continuous innovation and persistent in quality to make the product better than ever creating the customer perceived value becomes the proven solution of business survival competition. The material traceability is one of these value generators.