The use of an ERP system for new product development: a logistic perspective

Transcription

1 Marcin Relich, Paweł Kużdowicz, Lilianna Ważna University of Zielona Góra Logistyka - nauka The use of an ERP system for new product development: a logistic perspective Introduction In recent years, the advancement of information technology in business management processes has placed Enterprise Resource Planning (ERP) system as one of the most widely implemented business software in various enterprises. ERP software promises significant benefits to organizations. Some of these benefits include lowering costs, reducing inventories, increasing productivity [10], improving operational efficiency [2,5], attaining competitive advantage [1], and bettering the reorganization of internal resources [9,14]. ERP is a system for the seamless integration of all the information flowing through the company such as finances, accounting, human resources, supply chain, and customer information [4]. The goal of an ERP based integrated information system is to make the system effective, efficient and user friendly. The performance of software depends on the interaction between the software and users. The primary task of an integrated system is to maintain the data flow of an organization and to reduce the redundancy [6]. The present information and communication technologies have become one of the most important factors, conditions and chances of the firm development. These technologies enable the collection, presentation, transfer, access and using of enormous amount of data. The data are a potential source of information that in connection with manager skills and experience may influence on the choice of the correct decision. ERP systems help to collect, operate, and store data concerning daily activities of an enterprise (e.g. client orders), as well as the results of previous projects (development of products). One of the functionalities of an ERP system concerns project management that company can use to develop new products. To obtain a project schedule, there is required data specification concerning resources and activities, including their sequence, duration and cost. Project parameters can be specified by the experts or estimated with the use of an ERP database. First approach is suitable for the projects that have very unique form, e.g. for the construction projects. In turn, if an enterprise develops new products and a new version of product is connected with the superficial modification of a product specification, then there is opportunity to acquire the knowledge from the ERP database and to use it for the improvement of estimation quality of project parameters. Intense competition on the market forces the enterprises to develop simultaneously a few new products. Moreover, the enterprise usually acts in the framework of constraints concerning time and resources (financial, human, logistic), and it has to choose an optimal set of new products (investment portfolio) [3]. This set can be determined with the use of market surveys and time-cost analysis of new products that requires the estimates of project parameters. Improper choice of a set of new products can lead to decreasing the market share, profitability and liquidity, and as a consequence to bankruptcy of enterprise. In addition, the failed projects are costly, not only in financial point of view, but also they can hurt the spirits of team members, damage an organization s reputation, and there is also the opportunity cost of delaying work on other (potentially much more successful) projects [7]. Hence, there is a need to try to use the past experiences that are stored in the ERP database for improving estimation quality of project parameters. The goal of this paper is to present the possibility of the use of the ERP database for seeking the relationships between the logistics parameters (e.g. delay of material delivery by suppliers, number of subcontractors) and the project parameters (e.g. project cost). The sought relationships can support the user in the assessment of project parameters, and as a consequence to obtain the more relevant estimates. It is unrealistic to expect very accurate estimates of project effort because of the inherent uncertainty in development projects, and the complex and dynamic interaction of factors that influence on its development. However, even a small improvement in the estimation quality can influence positively on planning and monitoring the project, for instance, in project cost, resource allocation, and schedule arrangement [12]. Logistyka 5/

2 Logistic processes in new product development Logistics can be characterized by a through flow nature of implemented tasks. It means that it can be considered as a dislocation of goods since materials, semi-finished goods, through manufacturing processes up to a delivery of finished products to a final customer. Functional fields include materials management, transport, storage, completion of orders, and packing [8]. The implementation of the above functions can be supported with the use of information systems. Three main logistics fields contain supply logistics, production logistics, and distribution logistics. Each logistics field can be considered as an order cycle, i.e. it includes some documents that are repeated for each order and are registered in an ERP system. For instance, for supply logistics there are purchase order, order confirmation, and stock receipt. In turn, distribution logistics includes customer s order, shipping document, and packaging receipt. According to the conception of integrated control of materials streams flow in an enterprise, the inventory needs requires products demand awareness. One of well-known methods of stock management and schedule development is Materials Requirements Planning (MRP). The MRP concerns especially the supply of materials and production parts, according to the demand depends on the final products. The market requirements and intensive development of Information Technology determined the further evolution of the MRP systems. These systems have been extended towards financial resources planning, and the class of systems was finally named Enterprise Resource Planning. An ERP system allows the integration of supply, production, distribution, marketing and finance, including cost accounting and controlling functions. An ERP system as an integrated IT management system can also support an electronic/internet-based business (e-business) that can be developed towards Customer Relationship Management (CRM) and Supply Chain Management (SCM) systems. An ERP system tends to reflect the business processes in the enterprise, including logistic processes. The performance of these processes can be measured using indicators that are built on the basis of parameters stored in an ERP database. A sample of parameters in the context of new product development is as follows: a number of human resource (e.g. in person-hour), machine-hour, supplies with complaints, materials withdrawn from a production process as a result of the bad quality, project activities, as well as financial means, delay in client s payment and material delivery by suppliers, consumption of materials, transport cost, etc. Method for estimating project cost The proposed method is dedicated for new product development in an enterprise that uses an ERP system. New product development is often connected with the superficial changes in design and/or functionality of past products. Thus, data of completed projects can be used to identify relationships between the parameters of past projects and their costs. New product development is usually connected with the uncertainty that concerns both internal (e.g. communication in project team, planning techniques, cash flow) and external environments (e.g. social, economic, political, technological conditions) [13]. The uncertainty nested in a project implementation is the reason for using techniques that can describe an imprecise form of data, e.g. fuzzy neural system. The proposed method consists of the following stages: 1. extracting data from an ERP system; 2. identification of critical factors that significantly influence on new product development; 3. learning fuzzy neural system in order to obtain rule base; 4. estimating cost of new product development; 5. loading data (cost estimate) to an ERP system. Database of an ERP system comprises an enormous number of parameters that can be considered as potential variables to identify the project cost. The second stage in the above-presented procedure concerns the identification of critical factors that influence on the project cost, and indirect on new product development. If the relationship between a variable and the project cost is significant (greater than a level defined by the user), then the variable is considered as the critical factor. 369 Logistyka 5/2013

3 Logistyka 5/ Logistyka - nauka The third stage in the proposed method concerns obtaining rule base with the use of the adaptive neuro-fuzzy inference system (ANFIS). ANFIS model is a universal approximator, which has the nonlinear modelling and forecasting function [11]. It is an effective technique that combines the ability for learning and processing inaccurate data that occurs in assessment of project parameters. The identification of rules and the initial parameters of membership function of fuzzy sets are obtained with the use of e.g. grid partition or subtractive clustering. The learning stage requires the declaration of optimisation weights method and stop criterion. After learning phase, the testing data are led to input of system to compare the results with target. Next section presents an example concerning the use of the above procedure. Example of project cost assessment The output variable is the cost (c i in monetary unit m.u.) for the i-th project. In turn, the input variables include: t i duration of the i-th project (in person-hours); a i number of activities in the i-th project; s i number of subcontractors in the i-th project; tm i number of project team members in the i-th project; md i average delay of material delivery by suppliers in the i-th project (in days). Table 1 presents data of twelve past projects that has been applied to the cost assessment in the proposed approach. Table 1 Data for cost assessment. Variable \ Project P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 Duration Number of activities Number of subcontractors Number of team members Delay of material delivery Cost The results have been obtained with the use of ANFIS tool that is Matlab software. The application of fuzzy neural system requires the declaration of variables (Figure 1). Figure 1 Specification of fuzzy neural system. After the declaration of input variables in the fuzzy neural system, the initial parameters of membership functions of fuzzy sets are estimated. As a result, the structure of fuzzy neural system is determined. In next stage, the fuzzy neural system is learnt to determine finally the shape of membership functions. To eliminate too strictly function adjustment to data and to increase the estimation quality, the data set is divided into learning (P1-P9) and testing set (P10-P12). The learning phase requires the declaration of method of weights

4 optimisation and stop criterion (e.g. a number of iteration). After learning phase, the testing data are led to input of system to compare the error between different models. Root mean square error (RMSE) for various models is presented in Table 2. It is noteworthy that the least error in testing set for the cost estimation has been generated with the use of ANFIS with subtractive clustering method. Table 2 Comparison of RMSE for different models. Model RMSE Average Linear model ANFIS - grid partition ANFIS - subtractive clustering 9.55 The membership functions and rules are the basis to evaluate the cost of an actual project. Let us assume that for the actual project are considered the following values: the planned duration in person hours equals 670, number of activities equals 25, number of subcontractors equals 4, number of team members equals 8, and planned average delay of material delivery equals 8. According to these parameters, the cost of project phase has been calculated at 575 m.u. (Figure 2). Figure 2 Estimation of project cost. There is also possibility to conduct what-if analysis, for instance, if the project duration will be increased to 700, then the project cost will be increased to 609 m.u. The obtained estimates can be further used to evaluate cash flow, working capital, financial reserves, product launch, and other critical factors of an enterprise activity in the context of new product development. Conclusion Competition in quality, design, cost of new products, and time their launching into the market forces more frequent and larger-scale changes in contemporary companies, also changes in the use of new information technologies. One of the technologies concerns a fuzzy neural system that is used in this paper to evaluate the project cost. More exact identification of project cost enables more precision of cash flow planning and finally, decreases the risk of lack of liquidity. If in the enterprise is a database of past projects, then there is the possibility to gather additional information in the form of conditional rules. The application of the proposed approach encounters some difficulties, among other things, by the collecting enough amounts of data of the past similar projects. Moreover, the lack of uniform rules that concern the development of fuzzy neural systems may cause an acceptance problem for the decision-makers. However, the presented approach seems to have the promising properties for acquiring information from an ERP system. 371 Logistyka 5/2013

5 Further research focuses on the development of the presented approach towards identifying a set of key performance indicators according to their influence on the success/failure of completed projects. Moreover, future research can be aimed at adjusting the proposed approach in the context of risk management in the project. Abstract Nowadays, the development of new products is supported by the use of an ERP system in an increasing number of companies. An ERP system reflects business processes in an enterprise, including the field of logistics concerning supply, production and distribution. A typical ERP system comprises of an enormous amount of data that can be used for the improvement of project parameters estimation, such as project duration and cost. The ERP database includes data from previous projects, which is also connected with the logistics processes, e.g. the delay of material delivery by suppliers. The paper investigates the use of an ERP database to identify the factors in the field of logistics that significantly influence on new product development. Literature [1] Beard J., Summer M.: Seeking strategic advantage in the post-net era: viewing ERP systems from resource-based perspective. Journal of Strategic Information Systems, 2004, vol. 13, [2] Benders J., Batenburg R., Van der Blonk H.: Sticking to standards; technical and other isomorphic pressures in deploying ERP systems. Information & Management, 2006, vol. 43, [3] Budík J., Doskočil R.: Soft computing as a tool to optimize an investment portfolio. Intellectual Economics, 2011, vol. 5(3), [4] Davenport T.: Putting the enterprise into the enterprise system. Harvard Business Review, 1998, July-August, [5] Häkkinen L., Hilmola O.: ERP evaluation during the shakedown phase: lessons from an aftersales division. Information Systems Journal, 2008, vol. 18(1), [6] Imtiaz A., Kibria M.G.: Modules to optimize the performance of an ERP based integrated information system. In: IEEE International Conference on Informatics, Electronics & Vision, 2012, [7] Kormancová G.: Project success and failure. In: Theory of Management 6: The Selected Problems for the Development Support of Management Knowledge Base, Žilinská univerzita v Žiline, EDIS vydavateľstvo ŽU, Žilina, 2012, [8] Kulińska E.: Fundamentals of logistics and supply chain management. Wyd. MS, Opole, [9] May J., Dhillon G., Caldeira M.: Defining value-based objectives for ERP systems planning. Decision Support Systems, 2013, vol. 55, [10] Olson D.: Managerial Issues of Enterprise Resource Planning Systems. McGrawHill/Irwin, Boston, [11] Relich M.: A decision support system for alternative project choice based on fuzzy neural networks. Management and Production Engineering Review, 2010, vol. 1(4), [12] Relich M.: An evaluation of project completion with application of fuzzy set theory. Management, 2012, vol. 16(1), [13] Relich M., Kużdowicz P.: A declarative approach to project risk management. In: Global Crises - Opportunities and Threats - CO-MA-TECH 2012: 20th international scientific conference, [14] Stratman J.: Realizing benefits from enterprise resource planning: does strategic focus matter? Production and Operations Management, 2007, vol. 16(2), Logistyka 5/